In any research, there must be a variable to be measured or related to each other to determine their relationship. Faulkner & Faulkner, therefore, define a variable as fields that researchers find it difficult to measure and thus collect data about them to assist in measurement. In research, a researcher conceptualises variables by converting a theory into a measurable or tested hypothesis. Variables must be identified, developed and analyzed in research for the objectives of the study to be obtained. Faulkner & Faulkner (2016), in their book, describe how to use variables and identifying different types of variables.
Variables are viewed and used differently depending on the kind of data that it defines and represent. A variable termed sex, for example, can be used to mean different things depending on the type of data that the researcher has collected about it. Faulkner & Faulkner includes that there are three types of variables; the dependent, independent and control variables that can exist in research. The dependent variable is that which exist on its own and is not affected by other variables while independent variables are those who are influenced by the other external factors for example plant growth is affected by the sun. Control variable, on the other hand, is that which remain constant through the experiment helping in setting the standards of the data to be obtained.
A measure, according to Faulkner & Faulkner is any tool that a researcher can develop that will assist him or her in collecting the most appropriate data for the research. Measures can be in levels, for instance, the level of alcohol consumption. The book talks about how levels of action can either are discrete or standardised. The separate measure also referred to as pure level measure is a type of data that can be represented by actual value while graded test has a given range of figures with which a respondent can choose from. Data validity and reliability is the measure of how accurate the collected data under the variables are. This will enable the researcher to know if the data collected can be used to represent the real information as it is in the field.
In any research, there must be a variable to be measured or related to each other to determine their relationship. Faulkner & Faulkner therefore define a variable as fields that researchers find it difficult to measure and thus collect data about them to assist in measurement. In a research, a researcher conceptualizes variables by converting a theory into a measurable or tested hypothesis. Variables must be identified, developed and analyzed in a research for the objectives of the research to be obtained. Faulkner & Faulkner (2016), in their book describe how to use variables and identifying different types of variables.
Variables are viewed and used differently depending on the kind of data that it defines and represent. A variable termed sex, for example, can be used to mean different things depending on the type of data that the researcher has collected about it. Faulkner & Faulkner includes that there are three types of variables; the dependent, independent and control variables that can exist in a research. The dependent variable is that which exist on its own and is not affected by other variables while independent variables are those which are affected by the other external factors for example plant growth is affected by sun. Control variable on the other hand is that which remain constant through the experiment helping in setting the standards of the data to be obtained.
A measure, according to Faulkner & Faulkner is any tool that a researcher can develop that will assist him or her in collecting the most appropriate data for the research. Measures can be in levels for instance the level of alcohol consumption. The book talks about how levels of measure can either are discrete or standardized. Discrete measure, also referred to as nominal level measure is a type of data that can be represented by actual value while standardized measure has a given range of figures with which a respondent can choose from. Data validity and reliability is the measure of how accurate the collected data under the variables are. This will enable the researcher know if the data collected can be used to represent the real information as it is in the field.
References
Faulkner, S. S., & Faulkner, C. A. (2016). Ethical Considerations. In Research Methods for
Social Workers (2nd ed)
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