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Company W is testing a sales software. Its sales force of 500 people is divided into four regions: Northeast, Southeast, Central, and West. Each sales person is expected to sell the same amount of products. During the last 3 months, only half of the sales representatives in each region were given the software program to help them manage their contacts. The Northeast using the software sold 165 and the group with no software sold 100, The Southeast with software sold 200 and the group with no software sold 125. The Central groups with software sold 175 and the group with no software sold 125. The West group with software sold 180 and the group with no software sold 130. Using this data calculate the Chi Square statistic.
The VP of Sales at WidgeCorp, who is comfortable with statistics, wants to know the possible null and alternative hypotheses for a nonparametric test on this data using the chi-square distribution. A nonparametric test is used on data that are qualitative or categorical, such as gender, age group, region, and color. It is used when it does not make sense to look at the mean of such variables. (You can refer to the article for this phase for further information.)