M.Com RM Ch.1.pdf

Module - I Introduction to Research Research Methodology in Business M.Com Sem-I Dr. Vinod H. Kamble  RESEARCH - CONCEPT The word ‘Research’ is derived from the French word ‘recherche’ meaning ‘to go about seeking’. Research is a...

Module - I Introduction to Research Research Methodology in Business M.Com Sem-I Dr. Vinod H. Kamble  RESEARCH - CONCEPT The word ‘Research’ is derived from the French word ‘recherche’ meaning ‘to go about seeking’. Research is a careful and detailed study of a specific problem using the scientific method. Also, research is a systematic investigation to search for new facts in any branch of knowledge. It helps to find solutions to certain problems and arrive at new conclusions  RESEARCH - CONCEPT DEFINITIONS ❑William C. Emory defines “research is any organized inquiry designed and carried out to provide information for solving a problem.” ❑Robert Ross defines “Research as essentially an investigation, a recording, and analysis of evidence to gain knowledge.” ❑Clifford Woody: Woody defines research as "a careful, unbiased investigation of a problem, based on the systematic collection, analysis, and interpretation of data to gain new knowledge."  RESEARCH - FEATURES 1) Systematic Process Research is a systematic process. No research can be conducted haphazardly. Each step must follow the other. There are set of procedures that have been tested over some time and are thus suitable to use in research: The steps are as follows: ❑Formulating the research problem ❑Review of Literature ❑Define Research objectives ❑Preparing Research Design Define Collect Arrive at ❑Collection and analysis of data Problem Data conclusion ❑Interpretation of data ❑Preparation of report ❑Follow-up of report  RESEARCH - FEATURES 2) Objective and Logical / Empirical Objective research is unbiased and based on observable and measurable evidence rather than personal feelings, interpretations, or opinions. It aims for neutrality and reliability in findings. Logical/Empirical research relies on empirical evidence derived from observations, experiments, and real-world data, which are systematically collected and analyzed. It involves logical reasoning, often using a scientific method to test hypotheses and validate theories. Example: if a company wants to study how a new advertising campaign affects its stock price, the research should be objective, avoiding any personal opinions about the campaign. It should use a logical approach, like tracking stock price changes before and after the campaign to see if there's a direct link. Additionally, the research should be empirical, using actual stock price data and campaign details to analyze whether the campaign had a measurable impact.  RESEARCH - FEATURES 3) Development of Principles and Theories Systematic research helps to develop new principles and theories. Such principles and theories can be useful to several organizations to manage and deal with people and things in a better way. Eg. Prof. Alfred Marshall used the inductive method of economics research. On the basis of the market analysis, he framed the ‘Law of Demand’. According to this law, there exists a negative relationship between the price and quantity demanded. When the price increases, demand falls, and vice versa.  RESEARCH - FEATURES Another example could be, the ‘14 Principles of Management’ by Henry Fayol. They are developed gradually with thorough research work. Systematic observation and experiments are conducted in various organizations before developing them.  RESEARCH - FEATURES 4) Multi-purpose Activity Research is a multipurpose activity. It helps to achieve multiple purposes such as: ❑Discover new facts or verify old facts ❑Develop new scientific tools, concepts, and theories ❑Predict future events and control such events ❑Establishes relationship between variables Use of Marks in Mobile Relationship Exam Phone  RESEARCH - FEATURES 5) Basic and Applied Research Fundamental or pure research is a research approach that is entirely theoretical and aimed at improving or expanding the knowledge base of a particular field of study. The main motivation in basic research is to expand man’s knowledge, not to create or invent something. There is no obvious commercial value to the discoveries that result from basic research. It does not have a direct commercial objective  RESEARCH - FEATURES Applied research is designed to solve practical problems of the modern world, rather than acquire knowledge for knowledge’s sake. In other words, the purpose of applied research is to know more about a certain real-world problem and take steps to solve it. It has a direct commercial objective. Researchers in this field try to find immediate solutions to existing problems facing a society or an industrial or business organization  RESEARCH - FEATURES 6) Quantitative and Qualitative Research Quantitative research refers to a systematic investigation of phenomena by gathering quantifiable data and performing statistical techniques. Eg. Research is undertaken to find out the number of unemployed graduates. This type of research is usually done by using surveys, experiments, and so on. Qualitative research is used to gain an understanding of human behaviour, intentions, attitudes, experience, etc. It is based on the Behaviour observation and the interpretation of the people. Eg. Research is Intention Attitudes undertaken to find out reasons why employees remain absent Experience from work  RESEARCH - FEATURES 7) Generalization When the researcher conducts research, he/she selects a target population and from this population, a small sample is selected for collecting data. So the sample selection must be done systematically so that it represents the whole population or the universe. The findings with this sample are generalized to the entire population/universe of research. Eg. research is undertaken on ‘Consumer behavior towards electronic goods of Samsung Company in Mumbai region’ among 500 sample size. The findings of these 500 samples may be generalized for people residing in the entire Mumbai region  RESEARCH - FEATURES 8) Reliability It is a subjective term that can not be measured precisely, but today some instruments can estimate the reliability of any research. Experiment Experiment Reliability is the extent to which the outcomes are 1 2 consistent when then the experiment is repeated more than once. If research is undertaken with a similar population and with similar procedures If it yields similar results each RESULT is same time it is called to be reliable research.  RESEARCH - FEATURES 9) Validity Validity in research refers to the extent to which the instruments that are used in the experiment measure exactly what you want to measure. It is the degree to which an instrument measures what it is supposed to measure. REFERENCES shorturl.at/eETUY shorturl.at/iyRWZ shorturl.at/glH46 shorturl.at/cikDR shorturl.at/ceE06 shorturl.at/jptFT shorturl.at/aisCO shorturl.at/ekBNY shorturl.at/dDIT1 shorturl.at/kwEX1 shorturl.at/insJ9 shorturl.at/gzBLP shorturl.at/xQ136 shorturl.at/fuIMP shorturl.at/lzAV6 shorturl.at/sOPU6 shorturl.at/acdjH shorturl.at/lCTY5  IMPORTANCE OF RESEARCH IN BUSINESS 1) Helps to predict changes in business environment Business management is witnessing constant changes due to changes in the external business environment such as: ❑Consumer preferences ❑Competitor’s strategy ❑Society expectations ❑Economic environment ❑Technological environment ❑Legal environment This change in a business environment can adversely affect a business organization. So the manager can timey predict such changes and save a business from heavy losses. For example, DMart uses consumer research to anticipate shifts in purchasing behavior, allowing them to stock high-demand products efficiently and maintain competitive pricing  IMPORTANCE OF RESEARCH IN BUSINESS 2) Launching a new product Business research helps in the successful launching of a new product in the market. This is because, research enables one to know the likes, dislikes, preferences, and choices of consumers relating to products. Accordingly, a business firm can design and launch new products. Such product has a lower rejection rate and higher acceptance from consumers. When customers are offered products as per their preferences, it results in customer satisfaction. For example, before introducing the Tata Nano, extensive research was conducted to understand the need for an affordable car in the Indian market.  IMPORTANCE OF RESEARCH IN BUSINESS 3) Helps to design an effective marketing strategy Business research helps to design an effective marketing strategy. Research enables a business organization to: ❑Design quality product ❑Decide the right price ❑Effective promotion ❑Proper distribution For example, in India, Flipkart used market research to understand consumer behavior during festive seasons, allowing them to tailor promotions and product offerings for maximum impact  IMPORTANCE OF RESEARCH IN BUSINESS 4) Achieve organizational goals Systematic business research helps to achieve organizational goals such as: ❑Customer Satisfaction ❑Increase in sales and profits ❑Expansion of Business ❑Enhance Corporate image ❑Face competition and so on For example, Flipkart uses customer feedback and market analysis to optimize its product offerings, achieving better sales and customer satisfaction.  IMPORTANCE OF RESEARCH IN BUSINESS 5) Studying the competition Companies often use business research to study key competitors in their markets. The company may want to know the percentage of customers in the market who purchase its products versus competitor’s products. Also, it enables us to know the marketing strategy of competitors. Accordingly, a business firm can design its marketing strategy to survive and grow in the highly competitive market. For example, Coca-Cola regularly analyzes Pepsi's marketing strategies to adjust its campaigns and maintain its competitive edge  IMPORTANCE OF RESEARCH IN BUSINESS 6) Facilitates decision making With the help of research data available, businessmen can make the right decision at the right time. Research provides a business with a chance to update itself on the latest market trends. Such knowledge will prove helpful in the formulation of useful tactics for success in the market. It is through research that a business can make educated and informed decisions. For example, a retail company can use market research to identify consumer preferences and tailor its product offerings to boost sales.  IMPORTANCE OF RESEARCH IN BUSINESS 7) Helps to measure business progress Business research enables us to gauge (measure) how well the business is performing. Early research may highlight problems in services and shortfalls in the products. Regular market research will show if improvements are being made and if positive, will help to motivate a team. For example, a company can use market research to track improvements in customer satisfaction scores and sales figures after implementing a new product line  IMPORTANCE OF RESEARCH IN BUSINESS 8) Availability of competent manpower Research also helps in the recruitment and selection of competent manpower. Proper recruitment and selection of employees with the right skills and attitudes help the firm to increase its productivity levels. Further effective training and compensation packages can improve the morale of employees and motivate them to work with dedication and commitment. For Example, Research on automation and process improvements helps manufacturers recruit engineers and technicians adept at implementing cutting-edge production technologies  IMPORTANCE OF RESEARCH IN BUSINESS 9) Helps to get the right suppliers Research helps the firm to get the right supplier who offers raw materials at the right price and right time. A proper supplier selection enables the firm to get or acquire high-quality raw materials which results in the production of high-quality products that are consumed by end users. For example, a company conducting thorough research might choose a supplier with a proven track record of timely deliveries and high-quality products, minimizing risks and ensuring smoother operations.  IMPORTANCE OF RESEARCH IN BUSINESS 10) Improves productivity Productivity refers to the ratio of output to the input i.e. with one unit of input, how much output is produced. Productivity can be increased with the help of: ❑Training to employees ❑Research and Development ❑Use of Modern Technology Business research makes realize to the business firm undertake these activities which result in improvement in the productivity of the business REFERENCES shorturl.at/aruAN shorturl.at/aeyBZ shorturl.at/cnoIK shorturl.at/vDIQV shorturl.at/ckmKV shorturl.at/buGMU shorturl.at/sI789 shorturl.at/hjxX9 shorturl.at/nsCER shorturl.at/hqxXZ shorturl.at/mxzM2  OBJECTIVES OF RESEARCH 1) To find solutions to problems Research can be undertaken to find solutions to solve a specific problem. Data is collected on the problem faced by an organization. Such data is analysed and interpretation is made to find out solution to solve the problem. Eg. An organization may initiate research to find a solution to the problem of declining sales of their product in the market. So the data is collected to find out reasons for declining sales and analysis of such data may provide a solution to the problem  OBJECTIVES OF RESEARCH 2) To obtain Information Research is undertaken to obtain information, which may not be easily available. A variety of information can be collected such as: ❑Consumer preference ❑Competitor’s strategy ❑Demand ❑Economic conditions and so on. Such information is vital for a marketer to make crucial marketing decisions.  OBJECTIVES OF RESEARCH 3) To make future predictions Research enables a businessman to collect past and present data. Based on such data, the researcher can make future predictions about the business situation and business stand shortly. Eg. A marketer wishes to launch a new product in the market. With the help of research, he can predict the future of that product and then decide whether to come up with that product or not  OBJECTIVES OF RESEARCH 4) To develop new tools and concepts Research helps to develop new tools and concepts for better study of an unknown phenomenon. For this purpose, exploratory research is undertaken to achieve new insights into such phenomenon. Use of Marks in Mobile Relationship Exam Phone  OBJECTIVES OF RESEARCH 5) To verify and test existing laws or theories Research may be undertaken to verify and test existing laws or theories. Such verification and testing of existing laws and theories are required to know their relevance in the present time. REFERENCES shorturl.at/koBDR shorturl.at/lqsGL shorturl.at/lAJK2  TYPES OF RESEARCH 1) Basic Research Basic or fundamental or pure research is a research approach that is entirely theoretical and aimed at improving or expanding the knowledge base of a particular field of study. The main motivation in basic research is to expand man’s knowledge, not to create or invent something. There is no obvious commercial value to the discoveries that result from basic research. It does not have a direct commercial objective. Eg. examining the theoretical relationship between the riskiness of an investment and the potential return it offers, such as researching the Capital Asset Pricing Model (CAPM) to understand how different levels of risk are expected to be compensated by higher returns  TYPES OF RESEARCH 2) Applied Research Applied research is designed to solve practical problems of the modern world, rather than acquire knowledge for knowledge’s sake. In other words, the purpose of applied research is to know more about a certain real-world problem and take steps to solve it. It has a direct commercial objective. Researchers in this field try to find immediate solutions to existing problems facing a society or an industrial or business organization. Eg. “Researching how different factors, like company earnings reports and economic indicators, can be combined to build a more effective portfolio management strategy.”  TYPES OF RESEARCH 3) Exploratory Research Exploratory research is a type of research conducted to gain a deeper understanding of a problem, issue, or phenomenon PROBLEM that has not been well-defined or understood. In other words, Exploratory research is used to investigate a problem that is not clearly defined or understood. It is therefore conducted to gain a deeper understanding of a research problem and its context, rather than to gain an understanding of its solution or result. Its primary purpose is to explore and identify the key factors, variables, and relationships involved, often when there is limited prior information available.  TYPES OF RESEARCH EXAMPLE A company wants to develop a new product but is unsure about customer needs and preferences. The company conducts focus groups and in-depth interviews with potential customers to understand their pain points, desires, and reactions to initial product concepts. Insights gained help the company refine product features and target the right market segments before proceeding with more detailed market research and product development.  TYPES OF RESEARCH 4) Conclusive Research Conclusive research is designed to provide a final and definitive answer to a research question or problem. It aims to offer clear, actionable insights and is typically used to make informed decisions or recommendations. This type of research is often conducted after exploratory or descriptive research has identified and defined the problem or issue. Exploratory research seeks to understand and clarify a problem or issue, while conclusive research provides definitive answers and actionable insights based on that understanding.  TYPES OF RESEARCH 5) Descriptive Research Descriptive research is a type of research that provides an in-depth description of the situation, phenomenon, or population under study. In other words, To provide a detailed and accurate description of a phenomenon or population. Examples of Descriptive Research Market researchers want to observe the habits of consumers or the frequency of shopping A company wants to evaluate the morale of its staff.  TYPES OF RESEARCH 6) Analytical Research Analytical research is a critical evaluation based on information or facts that is already available. Analytical research involves examining and interpreting data to understand relationships, identify patterns, and draw conclusions based on evidence. It often uses existing data or research findings to analyze and make sense of complex issues, typically involving statistical or qualitative techniques. The researcher analyse these to make a critical evaluation of the material. It is primarily concerned with testing hypotheses. Eg. A company wants to understand the impact of marketing campaigns on sales performance. Gather sales data, marketing campaign details, customer feedback, and demographic information.The company can use these insights to allocate marketing resources more effectively, focusing on digital advertising strategies that have proven to be more successful. The opposite of analytical research is descriptive research  TYPES OF RESEARCH 7) Empirical Research Empirical research is based on collecting and analyzing data from the real world to conclude. This research relies on data obtained through direct observation, experiments, or experiences, and conclusions are drawn based on this data. For example: a company surveying to evaluate the effectiveness of a recent advertising campaign. The company collects data from a sample of customers who were exposed to the campaign, asking them about their awareness of the campaign, their attitudes towards the advertised product, and their purchasing behavior. This data is then analyzed to assess whether there was an increase in brand recognition and sales directly associated with the campaign. The results provide concrete evidence of the campaign's impact, allowing the company to make data-driven decisions for future marketing strategies. The opposite of empirical research is theoretical/conceptual research.  TYPES OF RESEARCH 7) Experimental Research Experimental Research is a specific type of empirical research that involves manipulating variables to determine cause-and-effect relationships. It typically includes controlled experiments where one or more variables are altered to observe the effect on other variables. For example: a company testing the impact of different promotional strategies on customer purchases. The company sets up an experiment where it randomly assigns different promotional offers—such as discounts, buy-one-get-one- free deals, and free shipping—to separate groups of customers. By comparing the sales performance and customer response across these different groups, the company can determine which promotional strategy most effectively boosts sales. This experimental approach helps identify the causal effect of each promotional tactic, providing actionable insights for optimizing future marketing campaigns. Group -1 Group -2 The opposite of empirical research is observational research. REFERENCES shorturl.at/lmFQS shorturl.at/tvwAF shorturl.at/mFHKP  RESEARCH PROBLEM IDENTIFICATION PROCESS 1) Review of Existing Literature Begin by reviewing current literature and research in finance to understand existing knowledge and identify gaps or areas needing further investigation. This involves analyzing recent studies, academic journals, financial reports, and industry publications to identify trends, unresolved questions, and emerging issues in finance. This review helps frame the research problem within the context of existing knowledge and pinpoints specific areas where new research could make a valuable contribution 2) Define the Research Scope Clearly outline the scope of the research to focus on a specific aspect of finance, such as risk management, investment strategies, or financial regulation. Narrow down broad topics to more specific areas of interest and define the boundaries and objectives of the research. This ensures that the research problem is manageable and well-defined, making it easier to investigate effectively.  RESEARCH PROBLEM IDENTIFICATION PROCESS 3) Assess Relevance and Importance Evaluate the significance of the research problem about current financial issues, challenges, or opportunities. Consider how the problem impacts stakeholders, such as investors, companies, or regulators, and assess whether addressing it will provide valuable insights or solutions. This evaluation ensures that the research problem is meaningful and relevant to the field of finance 4) Evaluate Feasibility Determine whether the research problem can be studied effectively within the constraints of time, resources, and data availability. Assess the availability of data and resources needed for the research and consider the practical aspects of conducting the study, such as data collection methods and the time required. This step ensures that the research problem is feasible and that you can realistically conduct the study.  RESEARCH PROBLEM IDENTIFICATION PROCESS 5) Formulate Research Questions or Hypotheses Develop specific research questions or hypotheses based on the identified problem to guide the investigation. Create clear, focused research questions that address the core issues and develop hypotheses that can be tested through empirical research. This structured approach ensures that the study has a clear direction and that the research problem is investigated comprehensively. 6) Design the Research Methodology Plan the methods and procedures for conducting the research, including data collection and analysis techniques. Choose appropriate research methods, such as surveys, experiments, or financial modeling, and develop a detailed plan for how data will be collected, analyzed, and interpreted. This ensures that the research is conducted systematically and that the findings will be reliable and valid.  RESEARCH PROBLEM IDENTIFICATION PROCESS 7) Seek Feedback and Refine Obtain feedback from peers, mentors, or experts in the field to refine and validate the research problem and approach. Present the research problem and proposed methodology to colleagues or advisors for review and incorporate their feedback to improve the clarity and focus of the research problem. This step enhances the quality of the research and ensures that it is well-defined and feasible.  REVIEW OF LITERATURE – SIGNIFICANCE A review of literature is a comprehensive survey of existing research and scholarly articles on a particular topic. It summarizes, evaluates, and synthesizes previous studies to identify trends, gaps, and key findings, providing a context for new research or an understanding of the current state of knowledge in that field.  REVIEW OF LITERATURE - CONCEPT Author Year Name of Journal ISBN / ISSN Volume and Page Name No. Issue No. The Second International Conference on Social Eco- 979-10-95546- Georgieva 2014 1 (3) 100-106 Informatics 12-2 Title of Objective Research Findings and Suggestions Research Methodology Conclusion used To study challenges Digital Inclusion The significant factors that are faced by the and the Elderly: affecting usability was older generation in the The Case of less experience with digital world Online Banking use of online banking  REVIEW OF LITERATURE – SIGNIFICANCE 1) Helps to identify gaps in research Research gap refers to the areas which are not explored in the past researches. ROL enables the researcher to identify the gap in the past research. The researcher can attempt to fill this gap by undertaking research activity.  REVIEW OF LITERATURE – SIGNIFICANCE 2) Help to formulate research hypotheses The hypothesis is an assumption made to explain certain facts or provide the basis for further investigation. It is tentative in nature and it may prove to be correct or incorrect. Past studies or ROL help researchers to frame hypotheses for his/her current studies. The researcher collects data that may prove or disprove the hypothesis. Based on the result of hypothesis testing a conclusion can be drawn.  REVIEW OF LITERATURE – SIGNIFICANCE 3) Get familiar with the methodology adopted by other researchers Research methodology is the specific procedures or techniques used to identify, select, process, and analyze information/data about a research problem. ROL enables researchers to get familiar with a methodology that is used by other researchers in their research. Accordingly, he/she can decide his/her methodology in terms of the target population, sample size, method and technique of data collection and analysis, and so on.  REVIEW OF LITERATURE – SIGNIFICANCE 4) Prepare research design Research design is a logical and systematic outline of a research project prepared for directing, guiding, and controlling a research work. With the help of ROL, a researcher can prepare his/her research design. Research design keeps research work on the right track and helps to complete research in time.  REVIEW OF LITERATURE – SIGNIFICANCE 5) Prepare sample design A sample design is a framework, or road map, that serves as the basis for the selection of a survey sample. In research, it is not possible to collect data from the entire population/universe due to constraints of time, money, and energy on the part of the researcher. So researcher needs to select samples from the population/universe of research. The sample selected must be true representative of the population/universe of research. ROL helps researchers to prepare a proper sample design.  REVIEW OF LITERATURE – SIGNIFICANCE 6) Get familiar with data collection sources and data analysis techniques For the researcher primary or secondary data can be used by a researcher. The primary data can be collected by observation, survey, or experiment method. Secondary data can be collected from libraries, the internet, reports, etc. Collected data needs to be analyzed to conclude it. Various statistical tools can be used such as correlation, measures of central tendency, and so on for data analysis. ROL facilitates getting familiar with data collection sources and data analysis techniques used by other researchers.  REVIEW OF LITERATURE – SIGNIFICANCE 7) Understand the findings of other researchers and their conclusions ROL helps researchers to understand the findings of other researchers and their conclusions. It can be the basis for the researcher’s further research activity. Findings and Conclusion  REVIEW OF LITERATURE – SIGNIFICANCE 8) To compile bibliography The bibliography is a list of sources used in our research. The main purpose of a bibliography entry is to give credit to authors whose work the researcher has consulted in his/her research. ROL helps researchers to refer to bibliographies of other researchers to find out more about the topic by exploring their research.  REVIEW OF LITERATURE – SIGNIFICANCE 9) Understand the structure of the research report A research report is a written document containing key aspects of the research project. After the research work is completed, the findings along with recommendations are presented in the form of the research report to the authority for further decision-making. So ROL enables the researcher to understand the structure of the research report. REFERENCES shorturl.at/uyDF4 shorturl.at/hRW13 shorturl.at/qtSY9  SEARCH Techniques 1. Keyword Search Description: Uses specific words or phrases related to the topic. Example: Searching "impact of policy changes on stock market volatility" in a search engine or database. 2. Boolean Operators AND: Narrows the search by including only results that contain all specified terms. Example: "policy changes AND stock market volatility" OR: Broadens the search by including results that contain any of the specified terms. Example: "policy changes OR regulatory changes" NOT: Excludes results containing specified terms. Example: “Policy changes NOT fiscal"  SEARCH Techniques 3. Phrase Searching Description: Searches for exact phrases by using quotation marks. Example: "impact of policy changes" 4. Wildcard Characters Description: Symbols used to represent unknown or variable characters. Asterisk (*): Represents multiple characters. Example: "volatil*" might return "volatility" or "volatile." Question Mark (?): Represents a single character. Example: "polic? changes" might return "policy changes" or "police changes."  SEARCH Techniques 5. Truncation Description: Uses a symbol (often an asterisk) to search for variations of a root word. Example: "econom*" might return "economic," "economics," and "economy." 6. Field Searching Description: Searches within specific fields of a database (e.g., title, author, abstract). Example: Searching within the title field for "market volatility." 7. Advanced Search Description: Uses filters and advanced options to refine searches (e.g., date range, publication type). Example: Limiting search results to articles published in the last 5 years.  SEARCH Techniques 8. Citation Searching Description: Uses references from known sources to find related literature. Example: Finding papers that cite a key article on policy changes. 9. Subject Headings/Thesaurus Description: Uses controlled vocabulary or subject headings to find relevant topics. Example: Searching "stock market volatility" under subject headings like "Financial Markets" or "Market Fluctuations." 10. Snowball Sampling Description: Starting with a few relevant sources and using their references to find additional sources. Example: Finding a seminal paper on policy impact and then examining its references.  SEARCH Techniques 11. Meta-Search Engines Description: Aggregates results from multiple search engines or databases. Example: Using tools like Google Scholar or academic databases that search across multiple sources. 12. Natural Language Search Description: Queries in natural language, rather than using specific keywords. Example: "How do policy changes affect stock market volatility?"  HYPOTHESIS – CONCEPT Hypothesis is an assumption made by the researcher to explain certain fact or provide basis for further investigation. It states what the researcher thinks the outcome of the study will be. The researcher makes hypothesis and collects data that either support the hypothesis or do not support it. So the hypothesis may be proved to be correct or incorrect. Hypotheses are essential to all research studies with the possible exception of some descriptive studies whose purpose is to answer certain specific questions.  HYPOTHESIS – CONCEPT Example - Companies that implement comprehensive Higher stock corporate social responsibility (CSR) programs experience CSR price higher stock price performance compared to companies that do not. Transparency Less Stocks of companies with high levels of transparency in in financial volatility in financial reporting will exhibit lower volatility compared to reports stocks stocks of companies with low transparency. Webster’s Dictionary defines hypothesis as “an unproved Unapproved theory, proposition, supposition theory, proposition, supposition etc. tentatively accepted to Tentatively accepted to explain explain certain facts or to provide a basis for further certain facts investigation, argument, etc.” provide a basis for further investigation, argument,  HYPOTHESIS – FORMULATION 1) Identification of the Research Problem and its causes The researcher must identify the research problem which needs to be investigated. Also, he/she needs to identify the cause of such a problem. Eg. The research problem could be “Decrease in Profit Margins for Retail Banking Services in Urban Areas”. The possible causes of such a decline in sales could be: ❑ Increased Competition ❑ Higher Operating Costs ❑ Changing Consumer Preferences  HYPOTHESIS – FORMULATION 2) Formulate the Hypotheses The researcher may undertake an extensive Review of Literature (ROL) to discuss with an expert or by his/her own experience formulate the hypothesis. Eg. Hypotheses relating to the above problem can be formulated as: ❑ Profit margins for retail banking services are declining due to increased competition from fintech companies offering lower fees and innovative financial products ❑ Profit margins for retail banking services are declining due to a shift in consumer preferences towards online and mobile banking, reducing the demand for traditional banking services  HYPOTHESIS – FORMULATION 3) Pilot Test the Hypotheses The researcher may conduct a pilot study to test the hypothesis. Small sample respondents are selected and data is collected from them to conduct the pilot study. All the hypotheses are put to the test. The pilot study may indicate the most probable cause of the problem. This may help to select the best hypothesis for detailed investigation. Suppose the pilot study states that the most probable cause of the problem is the poor quality of the product.  HYPOTHESIS – FORMULATION 4) Select the Best Hypothesis After selecting the best hypothesis based on the pilot study, the researcher proceeds to investigate of the problem and find out the validity of the hypothesis. The researcher may specify the null hypothesis and alternative hypothesis. ❑ Null Hypothesis: It states that there is no relationship between two or more variables. A researcher hopes to reject or disprove the null hypothesis. Eg. There is no significant relationship between the increase in competition from fintech companies and the decline in profit margins for retail banking services. ❑ Alternative Hypothesis: It states there is a relationship between two or more variables. Eg. There is a significant relationship between the increase in competition from fintech companies and the decline in profit margins for retail banking services.  HYPOTHESIS – FORMULATION 5) Conduct the Research After formulating the final hypothesis, the researcher proceeds to conduct the research. He/she may prepare research design to conduct research in right direction. The researcher collects data and analyse the same to draw conclusion. He may use T-test, Z-test, Chi-Square, ANOVA, Correlation etc. tests for the purpose for testing hypothesis.  HYPOTHESIS – FORMULATION 6) Acceptance or Rejection of Hypothesis After testing the hypothesis, the researcher may reject the null hypothesis or the researcher may fail to reject the null hypothesis. Generally, when the researcher rejects the null hypothesis, the researcher may accept the alternative hypothesis. At times, the alternative hypothesis may also be rejected. REFERENCES shorturl.at/uEGH2 shorturl.at/gxOPR shorturl.at/eEST5  HYPOTHESIS – TYPES 1) Simple Hypothesis It reflects the relationship between one dependent variables (DV) and one independent variable (IDV). Examples: Higher credit card interest rates are associated with a decrease in consumer spending One One independent dependent variable variable  HYPOTHESIS – TYPES 2) Complex Hypothesis It reflects the relationship between two or more dependent variables and two or more independent variables. Examples: The impact of higher credit card interest Two or more Two or more rates on a decrease in consumer spending and the independent dependent discontinuation of credit card use. variable variable  HYPOTHESIS – TYPES 3) Directional Hypothesis A directional hypothesis is a prediction made by a researcher regarding a positive or negative change, relationship, or difference between two variables of a Positive or population. Positive negative change, Negative relationship or This prediction is typically based on past research, difference accepted theory, extensive experience, or literature on the topic. For example- “The introduction of a new financial technology platform will increase customer engagement in retail banking services”  HYPOTHESIS – TYPES 4) Non-Directional Hypothesis This form of hypothesis is used in studies where there is no sufficient past research available on which prediction can be made about the relation between variables. Positive or It does not stipulate the direction of the relationship. Positive negative change, Negative relationship or difference It is a statement that a relationship exists between two variables, without predicting the exact nature (direction) of the relationship. Eg. “The introduction of a new financial technology platform will affect customer engagement in retail banking services”  HYPOTHESIS – TYPES 5) Null Hypothesis This is a hypothesis that proposes no relationship or difference between two variables. It involves a statement that says there is no relationship between two groups that the researcher compares on a certain variable. It is denoted by “H0”. Example – Variable 2 ❑ There is no difference in average annual returns between mutual funds and exchange-traded funds (ETFs) Variable 1  HYPOTHESIS – TYPES 6) Alternative Hypothesis This hypothesis proposes a relationship between two or more variables. An alternative hypothesis is denoted by “H1”. Example – ❑ There is difference in average annual returns between Variable 2 mutual funds and exchange-traded funds (ETFs) Variable 1  HYPOTHESIS – TYPES 7) Causal Hypothesis Causal hypotheses propose a cause-and-effect interaction between two or more variables. This hypothesis predicts the effect of the independent variable on the dependent variable. Eg. ‘Increasing the interest rates set by central banks will directly lead to a reduction in corporate borrowing and investment levels.’  HYPOTHESIS – TYPES 8) Associative / Relational Hypothesis These hypotheses aim to determine if relationships exist between a set of variables. Do not indicate cause and effect. Example: There is a positive relationship between the level of corporate social responsibility (CSR) activities and the Variable long-term stock performance of companies. 2 Variable 1  HYPOTHESIS – TYPES 9) Testable Hypothesis These hypotheses predicts relationship between the independent variable and the dependent variable Positive or Positive negative change, Negative These variable are testable or measurable. relationship or difference  HYPOTHESIS – SOURCES 1) Intuition or Hunch A person may get ideas to develop a hypothesis due to one’s intuition or hunch. Ideas can strike like a flash. Eg. The story of the Laws of Gravitation propounded by Newton at the sight of a falling apple is the case of intuition.  HYPOTHESIS – SOURCES 2) Past Researches Findings of past research done by others can be used for framing the hypotheses. Eg. A researcher found in past research that a rise in the rate of commission of salesman increased sales of the company. A researcher may use this finding to formulate his research hypothesis as “Increase in rate of commission of salesman leads to increase in sales.”  HYPOTHESIS – SOURCES 3) Consultations The researcher can hold discussions with experts to develop a hypothesis. In academic research, the research students can take the help of a research guide who is an expert in his/her subject. In applied (commercial) research, the researcher may take the help of a marketing manager. In social research, the researcher may take the help of an NGO.  HYPOTHESIS – SOURCES 4) Observation The hypothesis can be developed through observation. Eg. One can observe the general pattern of buying behavior in the market, and develop a hypothesis such as “Educated customers prefer branded items as compared to illiterate or less educated customers.”  HYPOTHESIS – SOURCES 5) Continuity of Research Some researches are carried on for several numbers of years. The research may be divided into different phases. At each phase the researcher may get different findings based on which he/she develops a hypothesis for the next phase.  HYPOTHESIS – SOURCES 6) Theory Logical deduction from the theory leads to a new hypothesis. The hypothesis must be valid if the theory holds. Eg. The theory of human relations in management states that effective human relations help to improve productivity. Based on this theory, a hypothesis can be developed that “Effective management-labour relations facilitate higher productivity.”  HYPOTHESIS – SOURCES 7) Personal Experience Based on personal experience, the researcher uses his mind and suggests a hypothesis. Eg. A researcher experienced poor services in Government hospitals. He/she may develop a hypothesis “Poor quality of services results in less footfall in Government Hospitals.” REFERENCES shorturl.at/aovSU shorturl.at/ilBQV shorturl.at/CHVY6 shorturl.at/amAL9 shorturl.at/lCJNO shorturl.at/mMOQ1 shorturl.at/atOQ1  HYPOTHESIS – IMPORTANCE 1) Helps to explore unknown facts The hypothesis provides the researcher with the most efficient instrument for exploring and explaining the unknown facts. It stimulates the researcher for further research studies.  HYPOTHESIS – IMPORTANCE 2) Enables to prepare research design The hypothesis helps in preparing the research design. It may suggest : ❑Research Objectives ❑Sample Design ❑Data Requirement ❑Techniques Of Data Collection, Data Analysis, etc.  HYPOTHESIS – IMPORTANCE 3) Identifies the need for data A hypothesis specifies the need for data i.e. whether research will require primary data or secondary data. Hypothesis would enable to collection of required data. Without a hypothesis much useless data may be collected and important data would be omitted.  HYPOTHESIS – IMPORTANCE 4) Identifies sources of data A Hypothesis also specifies the source of data i.e. ❑Survey and Interview ❑Experimentation ❑Observation ❑Library ❑Reports ❑Internet etc. Therefore, the researcher would consider only the relevant source of data, which in turn would speed up the research activity.  HYPOTHESIS – IMPORTANCE 5) Development of theory and principles The hypothesis also facilitates the development of theory and principles. Eg. The theory of consumer behavior pre-supposes that no two consumers think and behave alike. Similarly, 14 Principles of Management by Henry Fayol, states that practicing these principles in an organization results in increasing organizational efficiency.  HYPOTHESIS – IMPORTANCE 6) Provides specific direction When a hypothesis is finalized a definite direction is provided for the research work. It makes way to the progress of the investigation. In the absence of a hypothesis, it becomes extremely difficult to focus on the research problem.  HYPOTHESIS – IMPORTANCE 7) Prevents blind research Hypothesis lights up the path of research. It distinguishes between scientific and unscientific inputs. It acts as a guide. Accuracy and precision are possible through hypothesis. Therefore, the hypothesis prevents blind research.  HYPOTHESIS – IMPORTANCE 8) Economical Developing hypotheses in business research is economical. It saves time, money, and energy for a researcher because it guides the researcher in the right direction. The hypothesis provides the basis for proper data collection. Relevant and correct information collected by a researcher through a properly formulated hypothesis proves resource saving. REFERENCES shorturl.at/bozFL shorturl.at/guLU5 shorturl.at/vzCNU shorturl.at/jCKT3 shorturl.at/gjIY9 shorturl.at/fntvG  CENSUS METHOD The census method is a data collection technique where information is gathered from every member of the entire population. It involves a complete enumeration, meaning every individual, household, or unit of the population is surveyed or studied. This method is used to achieve highly accurate and detailed data, as it covers the entire population without any sampling or estimation. The census method involves collecting data from every member of the population. This method provides comprehensive and complete data, as it does not rely on sampling. Objective: The main goal of the census method is to gather accurate, reliable, and detailed data that can be used for policy-making, research, and other purposes.  CENSUS METHOD - SUITABILITY The census method is most suitable when: ✓ The population size is manageable. ✓ High accuracy is required. ✓ It is necessary to avoid sampling errors or biases. ✓ The variability within the population is high, necessitating a full enumeration. (there is a significant degree of difference or diversity among the members of the population)  CENSUS METHOD - EXAMPLES A population census is one of the most common examples of the census method. Conducted by governments (such as the decennial Census of India, the U.S. Census, etc.), it involves collecting demographic data from every individual in a country. Information gathered includes age, sex, education, employment, income, family size, and housing conditions. This data is crucial for planning and implementing government policies, allocation of resources, and representation in government. An agricultural census collects comprehensive data from all farms, agricultural households, and entities engaged in agricultural activities within a country. This census collects data on farm size, crop production, livestock numbers, farming practices, and use of agricultural resources. This data helps in agricultural planning, development, and formulation of policies. An economic census collects data from all business establishments within a certain geographic area or sector. This census covers data on employment, revenue, expenses, products, and industry-specific information. It provides a detailed overview of economic activity and helps in understanding the structure of an economy  CENSUS METHOD - EXAMPLES A school census collects data on all students, teachers, and facilities in educational institutions within a specific region. This data helps in planning educational policies, allocating resources, and understanding student demographics. A housing census collects information about every housing unit in a country. This census collects data on the number of households, types of dwelling units, availability of basic amenities, and living conditions. It helps in urban planning, development of housing policies, and infrastructure development.  CENSUS METHOD – ADVANTAGES & DISADVANTAGES ADVANTAGES 1) Accuracy and Reliability: Provides the most accurate data as it covers the entire population. 2) Comprehensive Data: Offers detailed and in-depth data, making it useful for comprehensive analysis and decision-making. 3) No Sampling Error: Since every unit is studied, there is no risk of sampling bias or errors. DISADVANTAGES 1) Costly and Time-Consuming: Conducting a census requires a significant investment of time, money, and resources. 2) Complex Management: Handling and processing large volumes of data can be challenging and may require advanced technological support. 3) Not Feasible for Large Populations: For extremely large populations or when frequent data collection is needed, the census method may not be practical.  SAMPLING – CONCEPT Sampling is a technique of selecting a subset (part) of the population to make statistical inferences (conclusions) from them and estimate the characteristics of the whole population. It is difficult for a researcher to study the whole population due to limited resources such as time, cost, and energy. Hence, the researcher selects a part of the population for his study, rather than studying the whole population. This process is known as sampling. It makes the research activity manageable and convenient for the research. A sample should be representative of the population to ensure the results are accurate and reliable  SAMPLING METHOD - SUITABILITY The Sampling Method is suitable when: 1) Population Size is Large: It's impractical or impossible to study the entire population. 2) Limited Resources: There are constraints on time, budget, or manpower for data collection. 3) Need for Quick Results: Faster data collection and analysis are required. 4) Acceptable Level of Accuracy: Estimations rather than exact data are sufficient for decision- making. 5) Low Variability within Population: The population is relatively homogeneous, reducing the risk of bias in the sample.  SAMPLING METHOD - EXAMPLES 1. Market Research: A company launching a new product might use stratified sampling to survey potential customers from different age groups to understand their preferences and buying behavior. 2. Healthcare Studies: Researchers studying the effectiveness of a new drug might use simple random sampling to select patients from a hospital to participate in a clinical trial, ensuring every patient has an equal chance of being chosen. 3. Political Polling: Polling agencies often use systematic sampling or multistage sampling to predict election outcomes by selecting a representative sample of voters across different regions, ensuring diverse representation.  SAMPLING METHOD - EXAMPLES 4. Education Research: In studying the academic performance of students, researchers might use cluster sampling by selecting certain schools randomly and then surveying every student within those schools for more manageable data collection. 5. Finance-Research: A financial institution researching investment behavior might use stratified sampling to survey investors across different income levels, age groups, or risk preferences. This helps in understanding how different demographics invest, what financial products they prefer, and what factors influence their decisions. For instance, the institution might survey a sample of young professionals, middle-aged individuals, and retirees to compare their investment patterns and risk appetites.  SAMPLING – SIGNIFICANCE / ADVANTAGES 1) Time Saving Since using a sample reduces the number of people that have to be reached out to, it reduces time. Sampling helps to collect data and its analysis at a faster rate. Therefore, the researcher can get quick research results and accordingly can take timely action.  SAMPLING – SIGNIFICANCE / ADVANTAGES 2) Economical Since using a sample reduces the number of people that have to be reached out to, it also reduces cost. For any research, the availability of funds is a constraint. A smaller sample requires less funds not only for data collection but also for processing and interpretation of data.  SAMPLING – SIGNIFICANCE / ADVANTAGES 3) Reduced resource deployment It is obvious that if the number of people involved in a research study is much lower due to the sample, the resources required are also much less. The workforce needed to research the sample is much less than the workforce needed to study the whole population.  SAMPLING – SIGNIFICANCE / ADVANTAGES 4) Convenient Sampling offers convenience to the researcher to collect the data. The work of data collection becomes easy, quick, and economical. A researcher can complete his research project in time. 5) Reduce Complexities Sampling helps to reduce complexities in research work. If a limited sample is used, then fewer respondents are required to collect data. As a result, the researcher may require less time for editing, coding, and interpretation of data. Therefore, analysis can be quick and without complexities.  SAMPLING – SIGNIFICANCE / ADVANTAGES 5) Quality of Research Work The quality of research work may be improved due to sampling. The field staff will get sufficient time to collect the data from sample respondents. They need not to rush through the collection of data. Also, data analysis staff gets sufficient time for data analysis purposes. Therefore, the overall quality of research work improves.  SAMPLING – SIGNIFICANCE / ADVANTAGES 6) Motivation to Research Staff The limited sample size brings relief to the research staff. They get motivated to collect the right information. This is because they get sufficient time for collection and analysis of data. They may also get higher rewards due to good quality research work.  SAMPLING – SIGNIFICANCE / ADVANTAGES 7) Detailed Information Due to sampling, the researcher can collect detailed information from the sample respondents. They can ask more questions than questions in the questionnaire. Since there are fewer respondents, the data collected from a sample is intense and thorough. More time and effort is given to each respondent rather than having to collect data from a lot of people.  SAMPLING – SIGNIFICANCE / ADVANTAGES 8) Infinite Population If the population is too larger then the sampling method is the best way to find out solution. 9) Feasibility Sampling is practical when dealing with large populations where a full census is impossible due to resource constraints.  SAMPLING – DISADVANTAGES 1) Sampling Bias: If the sample is not properly selected, it may not accurately represent the population, leading to biased results. This is especially problematic in non-probability sampling methods. 2) Less Accuracy than a Census: Even with well-designed sampling, there is always some level of uncertainty or error that wouldn't exist if data from the entire population were used. 3) Limited Scope for Rare Cases: Sampling may miss rare or unique cases, which could be important for the study. A full census would include such cases. 4) Difficulty in Determining Sample Size: Deciding the correct sample size to ensure reliable and valid results can be challenging and requires careful consideration and statistical knowledge. 5) Requires Skilled Personnel: Designing a representative sample and interpreting the results correctly requires expertise in statistics and sampling techniques. 6) Not Suitable for Highly Diverse Populations: When the population is highly heterogeneous, ensuring that the sample accurately represents the entire population can be difficult and may require complex sampling methods. REFERENCES shorturl.at/sAJY3 shorturl.at/gAQT6 shorturl.at/tBPRU shorturl.at/gzAD2 shorturl.at/rvzO7 shorturl.at/awCP0 shorturl.at/wT045 shorturl.at/uAHJS  SAMPLING – METHODS Probability Methods Non-Probability Methods - Simple Random Sampling - Convenience Sampling - Systematic Sampling - Judgement Sampling - Stratified Random Sampling - Quota Sampling - Cluster Sampling - Snow-Ball Sampling  SAMPLING – METHODS PROBABLITY SAMPLING METHOD Probability sampling is a method of deriving a sample where the objects are selected from a population-based on the Theory of Probability. This method includes everyone in the population, and everyone has an equal chance of being selected. Hence, there is no bias whatsoever in this type of sample. The selection criteria are decided at the outset of the market research study and form an important component of research. The various probability sampling methods are discussed as below:  SAMPLING – METHODS PROBABLITY SAMPLING METHOD 1) Simple Random Sampling This is the most popular method which is normally followed to collect research data. This technique provides every member an equal chance of being selected in the sample. The members are selected randomly and purely by chance. There are two sub-methods: ❑Lottery Method: Where each member is given a number and then the numbers are mixed and by drawing of lots, the sample is selected. ❑Random Tables: The members are given numbers and the numbers are placed in rows. The sample is selected from rows at random.  SAMPLING – METHODS PROBABLITY SAMPLING METHOD Example: A financial advisory firm wants to understand the investment preferences of its clients. To achieve this, they decide to use simple random sampling: ❖ Population: The firm's entire client base, which consists of 10,000 clients. ❖ Sampling Method: The firm uses a random number generator to select 500 clients from the 10,000. ❖ Data Collection: They then survey these 500 randomly selected clients to gather data on their investment preferences.  SAMPLING – METHODS PROBABLITY SAMPLING METHOD 2) Systematic Sampling Systematic sampling is a sampling method where the researcher chooses respondents at equal intervals from a population. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals. Example: If the total population is 100 and the sample size is 10. Each respondent is given a number from 1 to 100. A certain number is selected say no. 3. So a number consisting of 3, 13, 23, 33, 43, 63, 73, 83, 93 will be selected as a sample.  SAMPLING – METHODS PROBABLITY SAMPLING METHOD Example: A telecommunications company wants to assess the quality of its customer service. To do this, they use systematic sampling: ❖ Population: The company received 15,000 customer service calls in the past month. ❖ Sampling Method: The company decides to review 5% of these calls, which is 750 calls. To ensure systematic sampling, they select every 20th call from a sorted list of all calls. ❖ Data Collection: Starting from a randomly selected point in the list, they review every 20th call to evaluate service quality, agent performance, and compliance with service standards.  SAMPLING – METHODS PROBABLITY SAMPLING METHOD 3) Stratified Random Sampling This sampling method is appropriate when the population has mixed characteristics, and the researcher wants to ensure that every characteristic is proportionally represented in the sample. The researcher divides the population into subgroups (called strata) based on the relevant characteristics (e.g. gender, age range, income bracket, job role). The strata are formed by researcher. Then he/she uses random or systematic sampling to select a sample from each subgroup.  SAMPLING – METHODS PROBABLITY SAMPLING METHOD Example: A bank wants to analyze investment preferences among its customers. It uses stratified sampling by dividing its customers into strata based on investment amounts (e.g., low, medium, high). Then, it randomly selects customers from each stratum to ensure the representation of different investment levels in the study.  SAMPLING – METHODS PROBABLITY SAMPLING METHOD 4) Cluster Sampling In cluster sampling, the population is divided into clusters (usually based on geographical or natural groupings). A random sample of clusters is then selected, and all members within those selected clusters are surveyed. The clusters are naturally formed. Instead of sampling individuals from each subgroup, the researcher randomly selects entire subgroups. If the clusters themselves are large, the researcher can select a sample from each cluster using a simple random or systematic sampling method  SAMPLING – METHODS PROBABLITY SAMPLING METHOD Example : A financial institution wants to study customer satisfaction among its clients across multiple branches. It uses cluster sampling by selecting a random sample of branches and then surveying all clients within those selected branches.  SAMPLING – METHODS NON-PROBABLITY SAMPLING METHOD Non-probability sampling is defined as a sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection. It is a less stringent method. This sampling method depends heavily on the expertise of the researchers. It is carried out by observation, and researchers use it widely for qualitative research.  SAMPLING – METHODS NON-PROBABLITY SAMPLING METHOD 1) Convenient Sampling It is a type of where samples are selected from the population only because they are conveniently available to the researcher. Selecting a sample based on ease of access and availability. It involves choosing individuals who are easiest to reach or most convenient to study. Example: A researcher surveys people in a shopping mall simply because they are readily available.  SAMPLING – METHODS NON-PROBABLITY SAMPLING METHOD 2) Judgement or Purposive Sampling In this method of sampling, researchers select the samples based purely on the researcher’s knowledge and judgement. In other words, researchers choose only those people who they deem fit to participate in the research study. This method is used when specific individuals with particular characteristics are needed. Example: A study on expert opinions in a specific field might involve interviewing industry experts chosen for their specialized knowledge.  SAMPLING – METHODS NON-PROBABLITY SAMPLING METHOD 3) Quota Sampling Population Under this method, the researcher allocates a certain quota to certain groups under study. Sample The quotas may differ from each area depending upon certain factors like age, occupation, income etc. Eg. A researcher studying the newspaper reading habits of college students may select 10 colleges for data collection. He may fix quota for each college based on certain criteria. He may select 100 students from one college, may be because the number of students is more in that college; and he may select only 20 students from another college because of less number of students in that college.  SAMPLING – METHODS NON-PROBABLITY SAMPLING METHOD 4) Snow-Ball Sampling Snowball sampling helps researchers find a sample when they are difficult to locate. Researchers use this technique when the sample size is small and not easily available. This sampling system works like the referral program. It is a sampling design in which respondents selected earlier are asked to identify other sample members.  SAMPLING – METHODS NON-PROBABLITY SAMPLING METHOD Example A financial research firm seeking to study unique investment strategies among high-net-worth individuals (HNWIs) uses snowball sampling to access this hard-to-reach population. They start by identifying and interviewing a few HNWIs known for their unconventional investment approaches. During these interviews, participants are asked to refer other HNWIs with similar strategies. This referral process continues, creating a "snowball" effect as each new participant provides additional referrals, allowing the researchers to expand their sample and gather insights into innovative investment practices within this exclusive network. REFERENCES shorturl.at/lvJY3 shorturl.at/efpwP shorturl.at/moC39 shorturl.at/deyV8 shorturl.at/hrFZ1 shorturl.at/inEPR shorturl.at/cANP1 shorturl.at/kuCP4 shorturl.at/atCQY shorturl.at/jnuQ2  FACTORS DETERMINING SAMPLE SIZE 1) Area of Research The number of sample respondents depends on the area of research. If the research is conducted at national level, it may require more number of respondents If the research is conducted at local level, it may require less number of respondents.  FACTORS DETERMINING SAMPLE SIZE 2) Availability of Funds Generally, the researcher may be constrained by the limitation of funds to conduct the research. Therefore, when the researcher has limited amount of funds allocated to the research activity, the sample size would be lesser as compared to when the researcher has larger amount of funds.  FACTORS DETERMINING SAMPLE SIZE 3) Availability of Manpower The researcher may require manpower to conduct surveys, interviews or for conducting experiments, observation etc. Eg. If the researcher has a good number of filed staff to conduct interviews, he may select the larger sample size of respondents and vice-versa.  FACTORS DETERMINING SAMPLE SIZE 4) Time Frame The sample size may depend on the time frame of the research. If the researcher has a lot of time available to conduct the research, he may select a large sample size of respondents and vice-versa.  FACTORS DETERMINING SAMPLE SIZE 5) Nature of Research The nature of the research may influence the sample size of respondents. Eg. In case of academic research, the researcher may be constrained with the limitations of funds, and therefore, he may select a smaller sample size. However, in the case of census survey of population, the sample size will be the entire population of the country.  FACTORS DETERMINING SAMPLE SIZE 6) Method of Sampling The method of sampling may influence the sample size of respondents. Eg. If the convenience sampling method is used, the researcher may consider a smaller sample size to obtain responses. However, in the case of stratified sampling or cluster sampling, the researcher needs to select a larger sample size of respondents.  FACTORS DETERMINING SAMPLE SIZE 7) Judgement of the Researcher At times, the researcher may use his judgment in deciding in the sample size. He may consider a smaller sample size if he is confident in getting adequate data from a smaller sample size. However, if the researcher feels that he needs to select a larger sample to collect responses, he may select a larger sample size. REFERENCES shorturl.at/orFL6 shorturl.at/nvLWY shorturl.at/rDJRU shorturl.at/joGST shorturl.at/jtyzA shorturl.at/lqrDU  SAMPLE SIZE CALCULATION Cochran's Formula when population size is unknown n = sample size Z = found in Z-table value at a given confidence level (1.96) p = estimated proportion of an attribute that is present in the population (50%) E2 = Margin of error (5%) SAMPLE SIZE CALCULATION  SAMPLE SIZE CALCULATION Problem – 1 : A public health survey aims to estimate the proportion of people who use a specific health service. The margin of error is set at 1%,. Calculate the sample size needed with 99% confidence. Problem – 2 : An educational institution wants to determine the proportion of students who support a new curriculum. The margin of error is 10. Calculate the sample size with 90% confidence.  SAMPLE SIZE CALCULATION Cochran's Formula when population size is known n = sample size n0 = initial sample size calculated as per larger population criteria N = Population size  SAMPLE SIZE CALCULATION Problem: You want to estimate the sample size needed to survey a population of 5000 with a 95% confidence level and a 5% margin of error. OR  SAMPLE SIZE CALCULATION Problem: For a population of 50,000, you want a 99% confidence level with a 1% margin of error. Problem: You need to determine the sample size for a population of 2000 with a 90% confidence level and a 10% margin of error.