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UNIT 1: NATURE OF QUANTITATIVE RESEARCH L1: Qualities of Quantitative Research LARGE-SCALE RESEARCH CAN BE UNDERTAKEN Due to many data collection methods that can be...

UNIT 1: NATURE OF QUANTITATIVE RESEARCH L1: Qualities of Quantitative Research LARGE-SCALE RESEARCH CAN BE UNDERTAKEN Due to many data collection methods that can be QUANTITATIVE RESEARCH employed in quantitative research that are relatively From its root word quantity, which means the “amount easy to administer, a research with a large number of of” or “number of,” quantitative research deals with samples is possible. numerals and how it can describe a phenomenon or This also allows researchers to make a more infer a relationship. comprehensive and generalizable conclusion for the It is the go-to approach for scientific inquiry because of entire population. its ability to test hypotheses. The relationship of different factors that we see creates DATA CAN BE PRESENTED IN GRAPHICAL OR TABULAR FORM a clearer picture of what is happening around us. Other than statistical analysis, researchers can analyze These factors can also be called variables, which are the data using graphical or tabular representations. basis for formulating and testing hypotheses. Numerical data summarized in tabular or graphical form aid researchers in making sense of them better. VARIABLES are an important concept in research. WEAKNESSES OF QUATITATIVE RESEARCH They are the ones that are usually identified, examined, A LARGE SAMPLE SIZE REQUIRES A LOT OF TIME AND EFFORT described, or correlated with answering a scientific The goal to generalize the results of quantitative studies inquiry. requires a larger sample size which can be an issue for Variables are traits that numerically describe or give many researchers. meaning to an object, phenomenon, or group of people This requirement increases the cost of research, and its These variables vary or change from one thing to time frame becomes longer. another. STATISTICAL ANALYSIS OF DATA REQUIRES AN EXPERT TO Examples of variables are the height of a chair, the PERFORM weight of a person, test scores of a student, or the Poor knowledge or inadequate skills in statistics might speed of a car. negatively affect the outcome of a study. CHARACTERISTICS OF QUATITATIVE RESEARCH QUANTIFYING AND REDUCING OBSERVATIONS TO JUST CONTROLLABILITY PIECES OF NUMERICAL VALUES MAKES IT TOO SIMPLISTOC To understand a specific relationship or phenomenon, Numerical values can only answer the questions of what quantitative research should be in an environment and it is often difficult to use these values in answering where all variables are identified and can be controlled the whys and the hows of the phenomena. GENERALIZABILITY TYPES OF QUANTITATIVE RESEARCH It is from larger sample sizes that the results are based Quantitative research can generally be categorized into on as a representative of the population. two: experimental and non-experimental types. OBJECTIVITY EXPERIMENTAL RESEARCH The results of the data are observable and measurable TRUE EXPERIMENTAL using structured instruments. The primary objective of a true experimental research Sets aside the opinions and feeling of the researchers. design is to identify a cause-effect relationship between REPLICABILITY the variables where the samples are randomized. The research study should be replicable by other teams NON-EXPERIMENTAL RESEARCH of researchers that will eventually come up with similar DESCRIPTIVE RESEARCH outcomes. The focus of this research design is to describe factors, STRENGTHS OF QUANTITATIVE RESEARCH variables, or phenomena that occur in nature. The factual quality of quantitative research and its For example, you want to identify the factors that generalizability to a population becomes the basis of its contribute to the spoilage of food. We know that there strengths. Queiros, Faria, and Almeida (2017), who are might be a thousand reasons why food spoils, but the researchers from Portugal, published a paper evaluating best way to narrow it down is to survey people that the strengths and limitations of qualitative and know about food spoilage. quantitative research approaches. From there, one can analyze the data by using descriptive statistics by calculating the mean, median, or ANALYSIS OF DATA IS ASSISTED WITH STATISTICAL METHODS mode. These are mathematical tools in which numbers can be processed to become more meaningful. COMPARATIVE RESEARCH Simple statistical measures such as determining the The primary objective of comparative research (also mean, median, and mode of a data set can also assist called causal-comparative research) is to compare two researchers in reducing the bulk of data to make it variables in order to identify whether there exists a easier to understand. causative relationship between them. Analysis using statistics also provides unbiased results. This kind of research usually involves two or more groups and one independent variable. 1|STEPH UNIT 1: NATURE OF QUANTITATIVE RESEARCH CORRELATIONAL RESEARCH L2: Types of Quantitative Research Its primary objective is to compare two variables then identify the relationship between them. QUANTITATIVE RESEARCH For example, you want to know if there is a relationship is defined as “a means for testing objective theories by between the length of sleep and student productivity. examining the relationship among variables” according to Creswell (2009), a famous book author and QUASI-EXPERIMENTAL researcher. Quasi-experimental research mirrors experimental In general, quantitative research focuses on the research, but it is not true experimental research where following: a causal relationship can be determined with the use of - collection of observable and measurable data dependent and independent variables. - standardized data collection instruments Quasi-experiments differ because the random selection - statistical techniques in data analysis of samples is not possible due to innate or ethical deals with empirical, observable, and measurable data reasons. that are often expressed in numbers and analyzed For example, you want to know the effect of height on through statistical techniques. milk brand preference. True experiments would have to CORRELATIONAL RESEARCH randomly assign participants to groups where they would be subjected to taste tests in order to know is “a statistical measure of association between two which brand they prefer. However, because height is an variables” as explained by Vanderstoep and Johnston innate characteristic of a person, participants cannot be (2009), two well-known communication and social randomly assigned to groups. Instead, you have to sciences researchers. group participants based on their height. Correlational research may look at the following: 1. whether an association exists between variables 2. the magnitude of the existing association between Remember: two variables Independent variable is the variable that is manipulated. 3. the direction of the association between two variables Dependent variable is the variable that is ‘dependent’ on the Although it is not exclusive to the field, correlational independent variable and this is the value being measured. research is often used in quantitative research in the social sciences. In psychology, different types of correlational research are used to look at patterns and associations of human behavior. In economics, correlational research may also be used to determine what affects (or is affected by) certain economic variables. In politics, correlational research may also be used to study whether an association exists between different political variables. While quantitative correlational research can determine whether a relationship is significant between two variables, it does not say that one variable causes the other. CAUSAL RESEARCH looks at causes and effects. Causation refers to the claim that a change in one variable creates a change in another variable. An example of causal research is looking at the cause and effect relationship between a food ingredient and the rate of decay of a food sample. Similar to correlational research, causal research is also applicable in different fields. Causal research is often used in studying the natural sciences, but it is not exclusive to this field. For example, in chemistry, causal research is applied in the conduct of chemical experiments to see whether a change in the quantity of one substance affects the characteristics of another substance. 2|STEPH UNIT 1: NATURE OF QUANTITATIVE RESEARCH TYPES OF QUANTITATIVE RESEARCH Self-classification - e.g., Do you consider There are two main types of quantitative research: yourself socially aware of current events survey research and experimental research. and issues? According to Creswell (2009), survey research “provides Knowledge - e.g., Who is your student a quantitative or numeric description of trends, council batch representative? attitudes, or opinions of a population.” 4. Data analysis and interpretation On the other hand, experimental research “tests the - A data analysis and interpretation plan is also part impact of a treatment (or an intervention) on an of the survey design. outcome, controlling all other factors that might - The analysis may either be descriptive or influence that outcome.” inferential. Both types of quantitative research draw findings by - A descriptive analysis provides a numerical report studying a sample population. of the results of the survey, which may include Both types of quantitative research use statistical frequencies or average scores. techniques to process and analyze the information - An inferential analysis makes comparisons among acquired from their respective data collection the survey results to establish and explain techniques. relationships. SURVEY RESEARCH EXPERMINETAL RESERACH a correlational type of quantitative research. is a type of quantitative research aimed at causation. This design makes use of a questionnaire as its main With the use of the cause and effect logic, an data collection tool. experimental research looks at whether the application According to Neuman (2014), a well-known sociologist, of a treatment, otherwise known as an intervention, the survey is “the most widely used social science data- causes an effect on the sample being experimented on gathering technique.” (Creswell, 2009; Leavy, 2017). The contents of a questionnaire correspond to the COMPONENTS OF EXPERIMENTAL RESEARCH objects or concepts whose correlations are being 1. Respondents analyzed. - The respondents in experimental research are COMPONENTS OF SURVEY RESEARCH called groups. Samples are selected and then 1. Survey research differentiated into groups. - There are two main types of survey designs: cross- - There are two main subgroups in an experimental sectional and longitudinal. research: experimental and control groups - A cross-sectional survey acquires information at The experimental group is the group that one point in time. receives the experimental treatment or - A longitudinal survey acquires information at intervention. multiple points in time to compare, contrast, and The control group is the group that does assess changes in responses. not receive the experimental treatment 2. Population and sample or intervention. While the control group - Survey research involves getting a sample from a does not receive an intervention, it is still population. a part of the experimental research to - A population is a general group of people with assess similarities or differences with the similar characteristics. results drawn from the experimental - A sample is a subgroup of the population that is group. chosen either randomly or purposively to 2. Variables participate in the survey research. - There are two main types of variables used in 3. Survey instrument. experimental research, and their interaction - The survey instrument, otherwise known as the constitutes the cause-and-effect relationship. questionnaire, is the main data collection tool of a - These two main types are the independent and survey research. dependent variables. - It contains closed-ended questions with fixed The independent variable is the answers that will be given to the selected sample. treatment variable. It causes and - The responses of the participants will be used in explains the effect. The independent analyzing the relationships of interest. variable may be manipulated in order to - According to Neuman (2014), survey questions may see changes in the produced effects. belong to the following categories: The dependent variable is the outcome Behavior - e.g., How frequently do you variable. It is the effect. It is the response use social media applications? to the application of or changes in the Attitudes/beliefs/opinions - e.g., What independent variable. The dependent do you think about animal therapy? variable may reflect different outcomes Characteristics - e.g., What is your depending on the conditions of the highest educational attainment? independent variable. Expectations - e.g., Do you plan to visit a coffee shop in the next two weeks? 3|STEPH UNIT 1: NATURE OF QUANTITATIVE RESEARCH 3. Stages of the experimental procedure 6. Data analysis and interpretation - Experimental research may undergo three stages of - Similar to survey research, the results of the experimental procedure: the pretest stage, the experimental research may be analyzed in a actual intervention stage, and the posttest stage. descriptive or inferential manner. - The actual intervention stage is the execution - The inferential analysis of experimental research phase of the planned experimental procedure/s. may vary according to the appropriate statistical - It is the phase where the interaction between the tests used in the study. variables of the study occurs. - What sets experimental research apart from survey - There are two main stages of procedure between research is the overall goal of causation and not the actual intervention: the pretest and the post- correlation. test. The pretest is the stage prior to the conduct of the experiment or the intervention. There is no interaction yet between the variables of the study. The posttest is the stage after the conduct of the experiment or the intervention. It is the stage after the interaction of the independent and dependent variables. The results of the posttest reflect whether there have been changes in the dependent variable based on the conditions of the independent variable. 4. Instrumentation and materials - Experimental research also makes use of different instruments and/or materials in the pretest, posttest, or actual intervention stages. - The research instruments and materials may differ according to the nature of the experiment. - Generally, an instrument in experimental research is used to record the observations at any stage of the experiment. 5. Experimental procedures - Experimental procedures differ according to which group is studied and the actions done with the group(s). - There are four main experimental procedures, which are as follows: A pre-experimental design studies and provides an experimental intervention to a single experimental group. It does not make use of a control group. A true experiment makes use of both experimental and control groups, whose respondents are randomly assigned. Variants of true experiments differ according to the participation of the experimental and control groups in the different stages of procedure. A quasi-experiment uses both experimental and control groups. It differs from a true experiment in that the participants of the quasi-experiment are not randomly assigned into groups. An example of a quasi-experiment is in medical research such as the effects of a developing drug. A single-subject design only has a single individual as the lone respondent of the experiment. The experiment proceeds by observing the individual at different experimental stages and over time. 4|STEPH UNIT 1: NATURE OF QUANTITATIVE RESEARCH L3: Variables in Quantitative Research For example, a researcher wants to know the effects of working for seven days a week on the employee’s VARIABLES IS QUANTITATIVE RESEARCH productivity level. In this given hypothesis, a researcher The focus when writing research, whether qualitative or might see job satisfaction as a possible intervening quantitative in nature, is the study of different variables. variable, ensuring that the employee is motivated Variables are anything that can be observed by enough to come to work every day. researchers, such as a person, thing, place, situation, or - Independent Variable: 7-day work week even a phenomenon. - Dependent Variable: Productivity level Such variables can be changed or can inflict change. - Mediating Variable: Job satisfaction Thus, as researchers, we must know about our variables because research mainly revolves around them. MODERATING VARIABLES Failure to understand the meaning and use of the are variables that may have a strong conditioned effect variables in our own research can result in a poorly done on the relationship between independent and research. dependent variables. Research studies use different kinds of variables that They may also portray how the relationship between the vary depending on their role and level of independent and the dependent variables may change, measurement. given different circumstances. Once you know how to identify them, you can also easily This kind of variable may also modify the strength of the identify the variables everywhere, which will serve as original causal relationship between the independent your starting point for your research inquiry. and the dependent variables. ROLES EXTRANEOUS VARIABLES Researchers, who focus on cause and effect Extraneous variables are variables that may be treated relationships between variables, need to understand the as independent or moderating variables but should be differences among the roles of variables, which are as excluded from the research study itself since it may follows. interfere with the research process. It is important that researchers know how to identify INDEPENDENT VARIABLE extraneous variables as they may compromise the Independent variables (also called causal variables) are validity of the experiment. variables that are presumed to cause the change in the For example, a researcher wants to know the effect of setup. poor garbage disposal on pollution. All other variables These are also factors or phenomena that may influence that a researcher should take note of, such as another variable to change. environmental factors and people, among others, may In experimental research, independent variables may have a direct impact on the dependent variable, which is also be manipulated to examine the specific effect an pollution. The researcher must identify all these so that independent variable may have toward another the extraneous variable can be controlled immediately variable. and not compromise the validity of the research. For example, a researcher is determining the effects of - Independent Variable: Poor garbage disposal motivation on the performance of employees. - Dependent Variable: Pollution The level of one’s motivation is measured and related to - Extraneous Variables: Environmental factors, its possible effects on an employee’s performance. people Therefore, motivation is considered as the independent variable. Tip DEPENDENT VARIABLES Is it a Mediator Variable or a Moderator Variable? Dependent variables (also called outcome variables) are A mediating variable should act as a dependent variables that change because of another variable. variable with respect to the independent variable These are variables that are also measured by but may also cause change to the dependent researchers using standardized tools. variable, thus acting as an independent variable in For example, a researcher is trying to determine the some way. effectiveness of the different coaching styles on A moderating variable must not be directly affected volleyball teams. The winning streak of the teams may by the independent variable and should not be a be measured and may change depending on the result caused by the independent variable in any coaching style employed by their coaches. Therefore, way. the winning streak is considered as the dependent variable. MEDIATING VARIABLES LEVEL OF MEASUREMENT Mediating variables (also called intervening variables) Level of measurement, also called scales of measure, show the connection between the independent and the gives you an idea of the type of data that you have and dependent variables. how the variables are measured. It can also be a mechanism by which the independent Understanding this will greatly help you in deciding on variable can effect change on the dependent variable. the statistical analysis that you could use in your research. 5|STEPH UNIT 1: NATURE OF QUANTITATIVE RESEARCH The level of measurement can be divided into two: categorical and continuous levels of variable. Categorical variables are variables that are qualitative in nature, which could either be nominal or ordinal. Continuous variables are variables that are quantitative in nature, which could either be interval or ratio. NOMINAL VARIABLE A nominal variable is any variable that represents different types of data that can be categorized or may be divided into groups. There is no specific order; hence, the frequencies for each category are only counted. Examples are race, ethnicity, and hair color. ORDINAL VARIABLE An ordinal variable is any variable that can also be categorized or may be divided into groups, but it has a specific order or rank. Hence, the frequencies for each category or group can be counted or ranked. However, the distance between categories when ranked is not equivalent. Examples are year of graduation, brands of bags, and food preferences. INTERVAL VARIABLE An interval variable is any variable that has numerical value. Hence, the numerical values can be counted and ranked. In addition, the difference between ranked categories is meaningful. For example, you know that the difference or interval between 25°C and 35°C is the same between 10°C and 20°C. However, there is no true zero when determining the interval in this kind of variable. If you say, -6°C, then that means below freezing point. RATIO VARIABLE A ratio variable is an interval variable, but unlike the interval variable, it has a true zero. Hence, it can be counted, ranked and has a meaningful difference between values. True or absolute zero means that nothing exists for that variable, that zero simply means none. For instance, a person’s weight can be counted, ranked, and you can determine the equivalent distance between a person’s weight and another person’s weight. Moreover, if you say that there is 0 kg, then there is no weight measured at all. 6|STEPH