Thursday, September 26, 2019
What are variables Essay Example | Topics and Well Written Essays - 1500 words
What are variables - Essay Example A variable is anything whose value can vary. For instance age is a variable as age varies for different persons. Variables need not be numerical always. Gender is a variable as it consists of two text values ââ¬Ëmaleââ¬â¢ and ââ¬Ëfemaleââ¬â¢. An attribute refers to specific values of the variable. For example, the variable gender has two attributes- male and female. The variable agreement may have five attributes- (a) strongly agree, (b) disagree (c) neutral (d) agree and (e) strongly agree (Trochim, 2006).Every variable has some attributes.For studying cause- effect relationship, the distinction between independent variable and dependent variable must be clear. The independent variable is what the researcher manipulates. The dependent variable is that which is affected by the independent variable. The independent variable is the cause or treatment and the dependent variable is the effect or outcome. For example, while studying the effects of traffic rule awareness campai gns to reduce accidents, the program is the independent variable and the achievements are dependent variables. A variable should be exhaustive and mutually exclusive. Exhaustive means that a variable should include all possible responses. For this purpose, list all the important attributes and use a general category like ââ¬Å"otherâ⬠to represent remaining ones. Also, variables should be mutually exclusive. It means that no one should be able to have two attributes simultaneously. Operationalization The meaning of a research study depends on how objectively the phenomena under consideration are observed. So developing a reliable and valid set of procedures for measuring the variables is crucial for the validity of research study (Operational Definitions, 2005). The first step for an operational definition is to specify the constructs. How observations are made, what is observed, how observations are to be recorded have to be specified accurately. Sample Sampling is the proces s of selecting units from a population so that by studying the sample, it would be able to generalise results back to the population. Related to generalisation is the concept of external validity. Validity refers to the approximate truth of conclusions (Trochim, 2006). External validity refers to the degree to which conclusions in the study would hold for other persons in other places at other times (Trochim, 2006). There are two major methods for selecting sample for generalisation. One is called sampling model. In it, the population to be generalised is identified and a fair sample is drawn to conduct the research. Since the sample is representative of the population, the generalisations are applicable to the population. The second approach is called proximal similarity model. The term proximal similarity was suggested by Donald T. Campbell. In this approach, several generizability contexts are considered and theories are developed as to which situation or context is more similar to the study and which are less similar. By doing so, it is possible to generalise the results of the study to other persons, places or times that are more like the study (Trochim, 2006). The population to be generalised is called theoretical population. The population that is accessible to the study is called accessible population. The list of accessible population from which sample is drawn is known as sampling frame. For example, if a phone survey is to be done with a phone book, the phone book is the sampling frame. The sample is the group of people, who are selected for the study. But, the group that actually completes the study is the sub sample of the sample only. There is a distinction between random selection and random assignment. Random selection refers to how sample is selected. Random assignment refers to how different treatments are assigned to the sample selected for study. In sampling, the units are usually people and they supply responses. A response is a specific m easurement value. A statistic is used to look at the responses of the entire sample. Mean, median,
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