1. Use descriptive statistics to summarize the data.

2. Develop a 95% confidence interval estimate of the mean annual salary for all sales-persons, regardless of years of experience and type of position.

3. Develop a 95% confidence interval estimate of the mean salary for inside salespersons.

4. Develop a 95% confidence interval estimate of the mean salary for outside sales-persons.

5. Use analysis of variance to test for any significant differences due to position. Use a .05 level of significance, and for now, ignore the effect of years of experience.

6. Use analysis of variance to test for any significant differences due to years of experience. Use a .05 level of significance, and for now, ignore the effect of position.

7. At the .05 level of significance test for any significant differences due to position, years of experience, and interaction.

Suppose that a local chapter of sales professionals in the greater San Francisco area con-ducted a survey of its membership to study the relationship, if any, between the years of experience and salary for individuals employed in inside and outside sales positions. On the survey, respondents were asked to specify one of three levels of years of experience: low (1–10 years), medium (11–20 years), and high (21 or more years). A portion of the data obtained follows. The complete data set, consisting of 120 observations, is contained in the file named SalesSalary.

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