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Variable * is a characteristic or attribute that can be measured in a study or experiment * is any property or characteristic that can take on different values * is the basic unit of the information studied and interpreted in research studies * is a measurable factor that can be observed, controlled...

Variable * is a characteristic or attribute that can be measured in a study or experiment * is any property or characteristic that can take on different values * is the basic unit of the information studied and interpreted in research studies * is a measurable factor that can be observed, controlled, or manipulated * is an attribute of an item of analysis in research * also called a study variable, is an informal term that means any factor used in research that has some kind of cause and effect relationship Types of Variables 1. independent variable * a condition in a research study that causes an effect on a dependent variable * the factor that a researcher can alter during a study * essential to effective experimental design because they allow researchers to identify cause-and-effect relationships * used when conducting an experiment * helps to gather evidence and draw conclusions about a topic in more formal experiments 2. dependent variable * a factor in an experiment that can change depending on the independent variable * used to determine how the independent variable directly affects it 3. control variable * characteristics that are constant and do not change during a study * has no effect on other variables and are often kept the same throughout an experiment to prevent bias 4. quantitative variable * is in the form of numerical values, allowing to perform mathematical calculations with it * aims to answer questions such as how many, how much, and how often * beneficial for being objective (relies on concrete numbers and fewer variables) * helps to remove biases from the research and make the findings more accurate * categorized into 2 types: a. discrete variable - any numerical variable that can be realistically counted, such as the coins in your wallet or the money in your savings account; isolated element that doesn't have a relationship with other numbers b. continuous variable - takes an uncountable set of values or infinite set of values; collected through measurements rather than simply counting 5. qualitative variable (categorical variable) * non-numerical information that can be observed and recorded * categorized into 3 types: a. binary variable – consists of only two parameters, such as male or female, red or blue; used to create statistical models that aim to predict if a specific subject will act one way or another b. nominal - can be labeled or classified into multiple categories without using numbers; used to create relevant categories for a research, such as colors, names, nationalities and flavors c. ordinal - can be organized in a certain order or on a scale; used to assess a group of respondents' views on a particular matter by offering them multiple levels of measurement to choose from; can also be used to classify variables or subjects by groups, such as child, teenager, adult and senior 6. intervening variable * theoretical variable used to explain a cause or connection between other study variables * also known as a mediator or mediating variable, explains the process through which two variables are related 7. moderating variable * changes the relationship between dependent and independent variables by strengthening or weakening the intervening variable's effect * variable that affects the strength and direction of that relationship 8. extraneous variable * factors that affect the dependent variable but that the researcher did not originally consider when designing the experiment 9. confounding variable * extra variables that the researcher did not account for that can disguise another variable's effects and show false correlations 10. composite variable * two or more variables combined to make a more complex variable  * often made up of two or more variables that are highly related to one another conceptually or statistically IMPORTANCE OF QUANTITATIVE RESEARCH ACROSS FIELDS 1. in psychology/social science research * quantitative psychologists study and develop the methods and techniques used to measure human behavior and other attributes; their work involves the statistical and mathematical modeling of psychological processes, the design of research studies, and the analysis of psychological data * a psychology researcher may develop a study to understand how early childhood attachment influences anxiety level in adults 2. in economics * with the application of quantitative methods, models, and adequate algorhythms, the more complex phenomena and processes in economics can be studied more efficiently and more precisely, as well as their interrelationship, in order to reach decisions and predicts movements of economic phenomena and processes * a researcher may develop a study about tax on commodity 3. in communication * quantitative research in communication helps to learn more about the patterns, trends, effects, and relationships of communication phenomena * a researcher may wish to investigate which expressions (syntagms (syntagma), idiomatic expressions, paradigms, n-grams in general) characterize certain kinds of communication 4. in gender studies * applying the diversity continuum shows that quantitative techniques offer gender scholars a means to increase our knowledge of differences, make scientific progress and simultaneously enable scholars to relate to existing knowledge outside gender studies * a researcher may study on gender-stereotypical perception of women’s leadership styles 5. in medical research/community health * quantitative research in healthcare involves the systematic collection and analysis of numerical data to uncover patterns, trends, and associations within a specific population or sample * in pharmacy research, scientists use clinical studies to evaluate the effectiveness and safety of new medications 3. in marketing research * quantitative market research is a technique to ask questions to the target audience in an organized manner using surveys, polls or questionnaires; received responses can be analyzed to make well-thought decisions for improving products and services, that will in turn help increase respondent satisfaction levels * business' goal is to make the page layout more efficient and to reduce the time that customers need to spend to complete their transactions 4. in the workplace research * the human resources department of a business conducts a study to assess the effectiveness of its current policies and plan revisions to improve workflows Quantitative Research Method * is the process of collecting and analyzing numerical data; it is used to test hypotheses and makes predictions through measured amounts Types of Quantitative Research (observational studies) 1. Descriptive Research * used to explain the current state of a variable or topic * can answer what, when, and how, but not why questions * researchers do not control or manipulate the variables, they just observe and measure them Sample Designs a. Surveys are often used to gather a large amount of data that can be analyzed for frequencies, averages, and patterns. For example, surveys can be used to describe the demographics of a given region, gauge public opinion on political topics, and evaluate customer satisfaction with a company’s products. b. Observations are often used to gather data without relying on survey respondents' honesty or accuracy. This method of descriptive research is used to understand how individuals act in real-life situations. c. Case studies can also be used to gather detailed information to identify characteristics of a narrowly defined subject. They are frequently used to generate hypotheses and theories. Goal The goal of descriptive research is to understand the current status of an identified variable. When to Use Descriptive research is used to identify categories and trends, form hypotheses, arrange comparisons, confirm existing phenomena, and outline sample characteristics. Sample Research Studies a. An athletic shoe brand conducts a demographic survey to understand the shoe purchasing trends among customers in New York. b. Find out where young adults aged 16-20 get their online news with a survey listing popular news sites. c. Discover how often working people take vacations by sending surveys asking how many vacations the target population has taken in the last year. 2. Correlational Research * examines the relationships between (two or more) different variables applied to the same group of subjects * relies on the scientific method and hypotheses * does not look at the differences between groups, rather, it looks for relationships within a single group Sample Designs a. Surveys are fast, easy ways to measure your variables of interest. It is essential to ensure that your questions are formulated correctly and your questions are free of bias. b. Naturalistic observation allows you to gather data about a behavior or phenomenon in its natural environment. This may include measuring frequencies, durations, scales, and amounts. Goal The goal of correlational research is to identify variables that have some sort of relationship to the extent that one creates a change in the other. When to Use Correlational research is used to gather data quickly from natural settings so you can generalize findings to a real-life situation. Sample Research Studies a. Find out if there is a relationship between Facebook shares of your website link and a higher Google ranking. b. Discover if there is a correlation between gender and class participation in college classes by observing seminars, tracking the frequency and duration of students’ contributions, and categorizing them by gender. c. Find out if videos on your website improve dwell time and increase conversions. 3. Quasi-Experimental Research * “resemblance” is the definition of “quasi” * Individuals are not randomly allocated to conditions or orders of conditions, even though the regression analysis (statistical method for investigating the connection between variables) is changed Sample Designs a. Nonequivalent groups: groups are similar, but only one experiences treatment or variable and participants have not been randomly assigned to conditions. b. Pretest-posttest: where the dependent variable is measured once before the treatment is implemented and once after it is implemented. c. Interrupted Time Series: a variant of the pretest-posttest design, wherein a set of measurements are taken at intervals over a period of time interrupted by a treatment. d. Combination Design: combines elements of both nonequivalent groups design and pretest-posttest design Goal The goal of quasi-experimental is to evaluate the effectiveness of a treatment. It also aims to demonstrate causality between an intervention and an outcome. When to Use  Quasi-experimental is often used when experimental research is deemed infeasible, unethical, or prohibited. True experimental design may be too expensive, particularly for researchers without access to large funding streams. At other times, too much work is involved in recruiting and properly designing an experimental intervention for an adequate number of subjects to justify a true experiment. In either case, quasi-experimental designs allow the researcher to study the question by taking advantage of data that has previously been paid for or collected by others (often the government). Sample Research Studies a. Your hypothesis is that sixth-grade students who attend an afterschool program will achieve better grades. You choose two similar groups of sixth-graders who attend different schools—one with an afterschool program and one without. b. You discover that a few of the psychotherapists in the clinic have decided to try out the new therapy, while others who treat similar patients have chosen to stick with the normal protocol. You can use these pre-existing groups to study the symptom progression of the patients treated with the new therapy versus those receiving the standard course of treatment. c. Some high schools in the United States are set aside for high-achieving students, who must exceed a certain score on a test to be allowed to attend. Those who pass this test most likely differ systematically from those who do not. 4. Causal-Comparative Research (Ex-post Facto) (Explanatory Research) * used to identify the cause and effect relationship between two or more groups and one independent variable * used to study the reasons behind a change/phenomenon that has already occurred and the researcher does not have control over active manipulation of variables * examines existing differences between or among groups to derive potential causes Types of Causal-Comparative Research Types of Causal-Comparative Research a. Retrospective: where the researcher investigates a particular question after the effects have occurred, attempting to identify what might have caused the current differences between groups. b. Prospective: where the researcher initiates a study, beginning with the cause and determined to analyze the effects of a given condition. The goal is to see how the conditions in the beginning change and affect each other. Sample Designs a. Achievement Tests b. Survey Questionnaires c. Interviews d. Observations Goal The goal of causal-comparative research is to identify how different groups are affected by the same circumstance. When to Use Causal-comparative research is often used to achieve research goals by comparing two groups in order to explain existing differences between them on a variable of interest. Sample Research Studies a. A researcher wishes to compare the body composition of persons who have only trained with free weights versus persons who have only trained with exercise machines. b. To find out the difference in wages between men and women, researchers have to make a comparative study of wages earned by both genders across various professions, hierarchies and locations. c. To determine the difference in leadership styles between men and women. 5. (True) Experimental Research * guided by a specific hypothesis or hypotheses * very useful for guiding decision-making * any research conducted using the scientific method uses experimental research methods Includes Three Basic Steps 1. The researcher measures the variables. 2. The researcher influences or intervenes with the variables in some way. 3. The researcher measures the variables again to ascertain how the intervention affected the variables. Sample Designs a. Pre-experimental: a researcher observes a group or multiple groups after implementing a treatment or introducing a factor that is assumed to lead to changes in the groups. This is used to understand if further research is necessary for the observed groups. Three Types of Pre-experimental Design 1. One-shot Case Study Research Design 2. One-group Pretest-Posttest Research Design 3. Static-group Comparison b. True experimental: depends on statistical analysis to support or refute the hypothesis. The participants must be chosen in random sampling. It is one of the most accurate forms of research because it provides specific scientific evidence. However, in a true experiment, a researcher must satisfy these three factors: 1. there is a control group that is not subjected to changes and an experimental group that will experience the changed variables 2. a variable that can be manipulated by the researcher 3. random distribution of the variables  Goal The goal of experimental research is to prove or disprove a specific hypothesis. When to Use Use experimental research when you need to compare two or more groups that are experiencing different conditions. Sample Research Studies a. Your company wants to market your new product. You choose to run two different versions of your advertisement as part of your marketing plan. You track the performance of each ad to determine which is the most effective. b. A researcher gathers plant samples and then randomly assigns half the samples to photosynthesize in sunlight and the other half to be kept in a dark box without sunlight, while controlling all the other variables (nutrients, water, soil, etc.) c. A company wants to identify the right demographic for its new service and gathers different groups of consumers based on age, location and other factors. The company then examines which groups produce the best results when exposed to the advertising campaign for the service. Key Characteristics of Quantitative Research 1. Use of measurable data 2. Use of statistical analysis 3. Use of a large sample size 4. Use of standardized research instruments 5. Use of objective measurements 6. Focus on causality 7. Use of deductive reasoning 8. Emphasis on objectivity Strengths and Weaknesses of Qualitative Research Major Strengths 1. Objectivity and Accuracy Quantitative research is strong and more preferable because it explains phenomena according to numerical data which are analyzed by means of mathematically based methods, especially statistics. In this way, biases are reduced to the minimum and analysis and interpretations are more objective and accurate. In fact, another important point to remember in quantitative research is that it is informed by objectivist epistemology, that is, it seeks to develop explanatory universal laws, for example, in social behaviors, by statistically measuring what it assumes to be a static reality. Reality should be studied objectively by the researchers who should put a distance between themselves and what is being studied. The researchers let the “object” speaks for itself by objectively describing rather than giving opinions about it. The researchers play a neutral role in the research process. 2. Sample Size A broader study can be made with quantitative approach which involves more subjects and enabling more generalizations of results. Scholar and researchers argue that one major advantage of qualitative research is that it allows to measure the responses of a large number of participants to a limited set of questions. Also, it allows the researchers to obtain a broad and generalizable set of findings from huge sample size and present them concisely and carefully. 3. Efficiency in Data Gathering Quantitative research allows researchers to use a pre-constructed standardized instrument or pre-determined response categories into which the participants’ varying perspectives and experiences are expected to fit, making data gathering faster and easier. Data gathering can be automated via digital or mobile surveys which, for example, allows thousands of interviews to take place at the same time across multiple countries, hence, the process is efficient and requires less effort. 4. Cost Efficiency Since data gathering is efficient and requires less effort, then the cost of conducting quantitative research is typically far less than in qualitative research. NOTE: quantitative research often seeks to gather large quantities of data points since this is beneficial for the purposes of testing, however, the grander the scope of the test and the more thorough researchers are in its methodology, the more likely it is to be spending a sizable portion of the marketing expenses on research alone) Major Weaknesses 1. Results are Less Detailed Since results are based on numerical responses, then there is a big possibility that most results will not offer much insight into thoughts and behaviors of the respondents or participants, however, may lack proper context. 2. Does Not Consider Meaning Behind Phenomena In every phenomenon, there are always important points that cannot be fully captured by statistics or mathematical measurements. Indeed, not all phenomena can be explained by numbers alone. 3. Issue of Artificiality Quantitative research can be carried out in an unnatural environment so that controls can be applied, which means that results may differ from “real world” findings. 4. Improper Representation of the Target Population This hinders the researchers from achieving its desired aims and objectives. Despite the application of an appropriate sampling plan, still representation of the subject is dependent on the probability distribution of observed data which may lead to miscalculation of probability distribution and falsity in proposition. 5. Limiting Quantitative research employs pre-set answers which might ask how people really behave or think, urging them to select an answer that may not reflect their true feelings. Also, it involves structured questionnaire with close-ended questions which leads to limited outcomes outlined in the research proposal. In this way, the results expressed in a generalized form, cannot always represent the actual occurrence or phenomenon. 6. Difficulty in Data Analysis Quantitative studies require extensive statistical analysis, which can be difficult to perform for researchers from non- statistical backgrounds. Statistical analysis is based on scientific discipline and, hence, difficult for non-mathematicians to perform. Quantitative research is a lot more complex for social sciences, education, sociology, and psychology. Effective response should depend on the research problem rather than just a simple yes or no response.