Exam 15: Data Analysis II-- Descriptive and Inferential Statistics

Correct Answer:

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When choosing statistics appropriate to a particular set of data, there are several considerations to keep in mind.

First, it is important to consider the type of data being analyzed. For example, if the data is categorical, such as survey responses or demographic information, then measures such as percentages, frequencies, and chi-square tests may be more appropriate. On the other hand, if the data is continuous, such as measurements of height or weight, then measures such as means, standard deviations, and t-tests or ANOVA may be more suitable.

Second, it is important to consider the distribution of the data. If the data is normally distributed, then parametric statistics such as t-tests and ANOVA may be appropriate. However, if the data is not normally distributed, then non-parametric statistics such as Mann-Whitney U tests or Kruskal-Wallis tests may be more suitable.

Third, it is important to consider the research question or hypothesis being tested. Different statistics may be more appropriate depending on the specific research question or hypothesis being investigated. For example, if the research question is about the relationship between two variables, then correlation or regression analysis may be more appropriate.

Finally, it is important to consider the level of measurement of the variables. For example, if the variables are measured on a nominal scale, then different statistics may be appropriate compared to variables measured on an interval or ratio scale.

In summary, when choosing statistics appropriate to a particular set of data, it is important to consider the type of data, the distribution of the data, the research question or hypothesis, and the level of measurement of the variables. By carefully considering these factors, researchers can choose the most appropriate statistics to analyze their data and draw valid conclusions.