2022 Introduction to Statistics in Research Mitchell 2nd ed

I N T R O T O R E S E A R C H : D A T A V I S U A L I Z A T I O N & C O M M O N S T A T T E S T S

SAMPLE DATA DESCRIPTION:

Sample study: Your company has timber yards in all four regions of the U.S. and you’ve received complaints about your COVID- 19 policies, but you don’t know if the complaints are mostly in one region or not. You randomly choose five stores in each region to collect the number of complaints (mainly guests who do not want to wear a mask) from their store in the last month. You want to see if there is a difference between regions before you make any changes to the COVID-19 policies.

Normal Distribution Before we get too far, we need to test the normal distribution assumption. There are three ways suggested: the Q-Q plot, the histogram, and the Shapiro-Wilk test. #1 – Test Normal Distribution graphically – Q-Q plot Use the following steps in SPSS to produce a Q-Q plot: Analyze > Descriptive Statistics > Q-Q Plots

Table 126: One Way Anova Sample dataset

Table 127: Q-Q plot to test normal distribution graphically

The scatter should li e as close to the line as possible. You don’t want to see a pattern coming away from the line. Patterns that come away from the line can indicate skewed data. This one looks pretty close the line, so I’m assuming it is a normal distribution, but let’s k eep checking.

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