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The process of examining a research problem in the social and behavioral sciences is often framed around methods of analysis that compare, contrast, correlate, average, or integrate relationships between or among variables. Techniques include associations, sampling, random selection, and blind selection. Designation of the dependent and independent variable involves unpacking the research problem in a way that identifies a general cause and effect and classifying these variables as either independent or dependent. Nội dung chính Discover How We Assist to Edit Your Dissertation Chapters What are the categories of the independent variable? What are the 4 variable types? What numbers are independent variables? What other names refer to the independent variable? The variables should be outlined in the introduction of your paper and explained in more detail in the methods section. There are no rules about the structure and style for writing about independent or dependent variables but, as with any academic writing, clarity and being succinct is most important. After you have described the research problem and its significance in relation to prior research, explain why you have chosen to examine the problem using a method of analysis that investigates the relationships between or among independent and dependent variables. State what it is about the research problem that lends itself to this type of analysis. For example, if you are investigating the relationship between corporate environmental sustainability efforts [the independent variable] and dependent variables associated with measuring employee satisfaction at work using a survey instrument, you would first identify each variable and then provide background information about the variables. What is meant by “environmental sustainability”? Are you looking at a particular company [e.g., General Motors] or are you investigating an industry [e.g., the meat packing industry]? Why is employee satisfaction in the workplace important? How does a company make their employees aware of sustainability efforts and why would a company even care that its employees know about these efforts? Identify each variable for the reader and define each. In the introduction, this information can be presented in a paragraph or two when you describe how you are going to study the research problem. In the methods section, you build on the literature review of prior studies about the research problem to describe in detail background about each variable, breaking each down for measurement and analysis. For example, what activities do you examine that reflect a company’s commitment to environmental sustainability? Levels of employee satisfaction can be measured by a survey that asks about things like volunteerism or a desire to stay at the company for a long time. The structure and writing style of describing the variables and their application to analyzing the research problem should be stated and unpacked in such a way that the reader obtains a clear understanding of the relationships between the variables and why they are important. This is also important so that the study can be replicated in the future using the same variables but applied in a different way. Fan, Shihe. “Independent Variable.” In Encyclopedia of Research Design. Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 592-594; “What are Dependent and Independent Variables?” Graphic Tutorial; “Case Example for Independent and Dependent Variables.” ORI Curriculum Examples. U.S. Department of Health and Human Services, Office of Research Integrity; Salkind, Neil J. “Dependent Variable.” In Encyclopedia of Research Design, Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE, 2010), pp. 348-349; “Independent Variables and Dependent Variables.” Karl L. Wuensch, Department of Psychology, East Carolina University [posted email exchange]; “Variables.” Elements of Research. Dr. Camille Nebeker, San Diego State University. To understand the concept of independent and dependent variables, one should understand the meaning of variables. Variables are defined as the properties or kinds of characteristics of certain events or objects. Independent variables are variables that are manipulated or are changed by researchers and whose effects are measured and compared. The other name for independent variables is Predictor(s). The independent variables are called as such because independent variables predict or forecast the values of the dependent variable in the model. Discover How We Assist to Edit Your Dissertation Chapters Aligning theoretical framework, gathering articles, synthesizing gaps, articulating a clear methodology and data plan, and writing about the theoretical and practical implications of your research are part of our comprehensive dissertation editing services. Bring dissertation editing expertise to chapters 1-5 in timely manner. Track all changes, then work with you to bring about scholarly writing. Ongoing tư vấn to address committee feedback, reducing revisions. The other variable(s) are also considered the dependent variable(s). The dependent variables refer to that type of variable that measures the affect of the independent variable(s) on the test units. We can also say that the dependent variables are the types of variables that are completely dependent on the independent variable(s). The other name for the dependent variable is the Predicted variable(s). The dependent variables are named as such because they are the values that are predicted or assumed by the predictor / independent variables. For example, a student’s score could be a dependent variable because it could change depending on several factors, such as how much he studied, how much sleep he got the night before he took the test, or even how hungry he was when he took it. Usually when one is looking for a relationship between two things, one is trying to find out what makes the dependent variable change the way it does. Let us identify independent and dependent variables in the following cases: In the case of a linear model, we have the general equation as: Here, Y is the variable dependent on X, therefore, X, is an independent variable. Similarly, in cases of the regression model, we have Here, the regressors, ßij (j=1, p.) are the independent variables and the regressands Yi are the dependent variables. Independent variables are also called “regressors,“ “controlled variable,” “manipulated variable,” “explanatory variable,” “exposure variable,” and/or “input variable.” Similarly, dependent variables are also called “response variable,” “regressand,” “measured variable,” “observed variable,” “responding variable,” “explained variable,” “outcome variable,” “experimental variable,” and/or “output variable.” A few examples can highlight the importance and usage of dependent and independent variables in a broader sense. If one wants to measure the influence of different quantities of nutrient intake on the growth of an infant, then the amount of nutrient intake can be the independent variable, with the dependent variable as the growth of an infant measured by height, weight or other factor(s) as per the requirements of the experiment. If one wants to estimate the cost of living of an individual, then the factors such as salary, age, marital status, etc. are independent variables, while the cost of living of a person is highly dependent on such factors. Therefore, they are designated as the dependent variable. In the case of time series analysis, forecasting a price value of a particular commodity is again dependent on various factors as per the study. Suppose we want to forecast the value of gold, for example. In this case the seasonal factor can be an independent variable on which the price value of gold will depend. In the case of a poor performance of a student in an examination, the independent variables can be the factors like the student not attending classes regularly, poor memory, etc., and these will reflect the grade of the student. Here, the dependent variable is the test score of the student. What are the categories of the independent variable? The two main types are: Quantitative Predictors, which have a numerical value (i.e. 5.5,800,2K) for categories like age, height, test scores or weight. Qualitative Predictors, which do not have numerical values. Used for categories like gender, socioeconomic status, political affiliation or geographic location. What are the 4 variable types? You can see that one way to look at variables is to divide them into four different categories ( nominal, ordinal, interval and ratio). These refer to the levels of measure associated with the variables. What numbers are independent variables? An independent variable is a variable that does not depend on any other variable for its value. For example, in an expression, 2y = 9x + 1, x is an independent variable. So, for each value of x, there will be a different value of y. What other names refer to the independent variable? Independent variables are also called: Explanatory variables (they explain an sự kiện or outcome) Predictor variables (they can be used to predict the value of a dependent variable) Right-hand-side variables (they appear on the right-hand side of a regression equation).

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