Сorrelational Research Method | Discussion

Abstract

Week 4 Discussion 2 asks the following: “Assume that you applied the method proposed in the research study you designed for the first discussion activity this week and now have the data. Which of the methods used for analyzing survey data would you use and why? Be sure to explain why the approach that you are proposing to use for data analysis is consistent with the survey research method that you employed. In addition, identify the measurement scale (nominal, ordinal, interval, or ratio) of the data you obtained and differentiate the research terminology used”.

Keywords: quantitative research, data analysis.

Data Analysis

Week 4 Discussion 1 states that “my proposed study will explore the relationship between the match of partners’ values and marital satisfaction. This will be a correlational research study that will collect information about partners’ key values and attitudes and their marital satisfaction, and evaluate the association between the difference in values and the level of marital satisfaction”. Thus, I applied correlational research method.

A correlation research study is a quantitative method of research in which you have two or more quantitative variables from the same groups of subjects, and you try to determine if there is a correlation between two variables (Curtis, 2013). Quantitative research data analysis provides the quantifiable and easy to understand results (Newman, 2011). I consider that calculation correlations with the use of excel program method is probably the simplest way of analyzing survey data, where you can set three columns (subject, variable one, variable two), enter data, select a cell for correlation to appeal in, label it, and receive your correlation.

After data analysis, I identify the measurement scale (nominal, ordinal, interval, and ratio) of the data I obtained and differentiate the research terminology used. It includes nominal (basic classification data), ordinal (logical order, but the differences in value are not constant), interval (data has logical order but has differences between values), and ratio (continuous ordered data, differences between values) scales (Ary, Jacobs, & Sorenson, 2010). The nominal scale is the easiest level of measurement that is used for labeling variables, but without any quantitative value. Ordinal scales are used for measurement non-numerical concepts such as happiness or discomfort. Interval scale is numerical scale where we can know the order and the exact differences between values. Ration scales give many possibilities when it comes to statistical analysis. The level of measurement can influence data analysis, and once I have indentified the level of measurement, I begin to use some of the quantitative data analysis procedures. I think that ordinal and nominal data analysis would be a good method of analyzing survey results, as numerical and survey data can be easily analyzed and handled using statistical equations.

References:

Ary, D., Jacobs, L. C., & Sorensen, C. (2010). Introduction to Research in education. 8th edition, California: Thomson Wadsworth.

Curtis, E. & Drennan, J. (2013). Quantitative Health Research: Issues and Methods.McGraw-Hill Education

Newman, M. (2011).Research Methods in Psychology. San Diego, CA: Bridgepoint Education, Inc. Retrieved from https://content.ashford.edu/print

The terms offer and acceptance. (2016, May 17). Retrieved from

[Accessed: March 29, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016.

[Accessed: March 29, 2024]

freeessays.club (2016) The terms offer and acceptance [Online].
Available at:

[Accessed: March 29, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016

[Accessed: March 29, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016

[Accessed: March 29, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016

[Accessed: March 29, 2024]

"The terms offer and acceptance." freeessays.club, 17 May 2016

[Accessed: March 29, 2024]
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