variables and measures in thesis

Explanations > Social Research > Measurement > Variables in research Definitions | Type | Independence | Control | Correlation | Cause | See also When doing social research, variables are both important and tricky. Here's a few words about them. Definitions A variable is something that can change, such as 'gender' and are typically the focus of a study. Attributes are sub-values of a variable, such as 'male' and 'female'. An exhaustive list contains all possible answers, for example gender could also include 'male transgender' and 'female transgender' (and both can be pre- or post-operative). Mutually exclusive attributes are those that cannot occur at the same time. Thus in a survey a person may be requested to select one answer from a list of alternatives (as opposed to selecting as many that might apply). Quantitative data is numeric. This is useful for mathematical and statistical analysis that leads to a predictive formula. Qualitative data is based on human judgement. You can turn qualitative data into quantitative data, for example by counting the proportion of people who hold a particular qualitative viewpoint. Units are the ways that variables are classified. These include: individuals, groups, social interactions and objects. Types Descriptive variables are those that which will be reported on, without relating them to anything in particular. Categorical variables result from a selection from categories, such as 'agree' and 'disagree'. Nominal and ordinal variables are categorical. Numeric variables give a number, such as age. Discrete variables are numeric variables that come from a limited set of numbers. They may result from , answering questions such as 'how many', 'how often', etc. Continuous variables are numeric variables that can take any value, such as weight. Independence An independent variable is one is manipulated by the researcher. It is like.
Understanding the types of variables you are investigating in your dissertation is necessary for all types of quantitative research design, whether you using an experimental, quasi-experimental, relationship-based or descriptive research design. When you carry out your dissertation, you may need to measure, manipulate and/or control the variables you are investigating. In the section on Research Designs, you can learn more about the various types of quantitative research design. In this article, we present and illustrate the different types of variables you may come across in your dissertation. First, we discuss the main groups of variables: categorical variables and continuous variables. Second, we explain what dependent and independent variables are. This will provide you with one of the foundations required to tackle a dissertation based on a quantitative research design. Categorical and continuous variables There are two groups of variables that you need to know about: categorical variables and continuous variables. We use the word groups of variables because both categorical and continuous variables include additional types of variable. However, there can also be some ambiguities when deciding whether a variable is categorical or continuous. We discuss the two groups of variable, as well as these potential ambiguities, in the sections that follow: Categorical variables Categorical variables are also known as qualitative (or discrete) variables. These categorical variables can be further classified as being nominal, dichotomous or ordinal variables. Each of these types of categorical variable (i.e., nominal, dichotomous and ordinal) has what are known as categories or levels. These categories or levels are the descriptions that you give a variable that help to explain how variables should be measured, manipulated and/or controlled. Take the following example.
In the course of writing your thesis, one of the first terms that you encounter is the word variable. Failure to understand the meaning and the usefulness of variables in your study will prevent you from doing good research. What then are variables and how should these be dealt with? I explain the concept below with examples of variables commonly used in research.You may find it difficult to understand just what variables are in the context of research especially those that deal with quantitative data analysis. This becomes much more confusing when you encounter the phrases “dependent variable” and “independent variable” as you go deeper in studying this important concept of research as well as statistics.Understanding what variables mean is crucial in writing your thesis proposal because you will need these in constructing your conceptual framework and in analyzing the data that you have gathered. Therefore, it is a must that you should be able to grasp thoroughly the meaning of variables and how these are measured. Yes, the variables should be measurable in order that you will be able to use your data for statistical analysis.I will strengthen your understanding by providing examples of phenomena and their corresponding variables below.Definition of Variables and ExamplesVariables are those simplified portions of the complex phenomena that you intend to study. The word variable is derived from the root word “vary”, meaning, changing in amount, volume, number, form, nature or type. These variables should be measurable, i.e., they can be counted or subjected to a scale.The following examples of  phenomena from a global to a local perspective and the corresponding list of variables are given to provide a clear illustration of how a complex phenomena can be broken down into manageable pieces for better understanding and to subject the phenomena to research.Phenomenon.
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