Develop a multiple linear regression equation that

Reference no: EM13474104

Simple Regression Analysis.

Use the data in the chart to answer the questions below. The data indicates the number of "sick days" appliance installers take during a three month period, and the number of complaints filed by customers during the same interval. Use the Analysis Toolpak in Excel to perform this simple regression and answer the questions.

a. Is the correlation between number of sick days and number of customer complaints statistically significant?

b. What is the best prediction for the number of complaints that will be registered for an installer who takes five sick days during the period?

Use Excel to help you answer the questions in the forum but do not attach your Excel document to the discussion post.

Multiple Regression Analysis.

Develop a multiple linear regression equation that describes the relationship between tenure and the other variables in the chart above. Use the Analysis Toolpak located in Excel to perform this multiple regression.

Do these two variables explain a reasonable amount of the variation in the dependent variable?

Estimate the tenure of someone that could have $5.8($k) and 15 years of job satisfaction. Make sure to state your multiple regression equation in your example. What are some of things that you can estimate from the model? How effective is evaluating the R-squared of the model? What is the relationship between the independent and dependent variables?

Use Excel to help you answer the questions in the forum but do not attach your Excel document to the discussion post.

Guided Response: Review several of your classmates' postings. Respond to at least two classmates by commenting on how this information might be used to make business decisions.

Reference no: EM13474104

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