Problem solving

Problem solving
You may use Microsoft Excel or any other technology to complete the question as long as the explanation is clear and a screen shot is included.

Please complete the following problems:

1. Open the Chapter 3 Webfile GDPyears.xlsx. This Excel file is located in the Chapter 3 Webfiles. You can find this in the Module 2 folder “Answers to even exercises and webfiles.” Please answer the following:

a. How could you improve the readability of this table?

b. The file GDPyears contains sample data from the United Nations Statistics Division on 30 countries and their GDP values from 2005 to 2010 in U.S. dollars ($). Create a table that provides all these data for a user. Format the table to make it as easy to read as possible. (Hint: It is generally not important for the user to know GDP to an exact dollar. It is more typical to present in millions or billions of dollars).

2. Open the Chapter 3 Webfile GasPrices.xlsx. The table contains time series data for regular gasoline prices in the U.S. for 36 consecutive months.

a. Create a line chart for these time series data. What interpretations can you make about the average price per gallon of conventional regular gasoline over these 36 months?

b. Fit a linear trendline to the data. What does the trendline indicate about the price of gasoline over these 36 months?

3. Open the Chapter 4 Webfile Absent.xlsx. A sociologist was hired by a large city hospital to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance in miles they live from work. A sample of 10 employees were chosen and the data is given in the Webfile.

a. Develop a scatter chart for these data. Does a linear relationship appear reasonable? Explain.

b. Use the data to develop an estimated regression equation that could be used to predict the number of days absent given the distance to work. What is the model?

c. What is the 99 percent confidence interval for the regression parameter beta subscript 1 ? Based on this interval, what conclusion can you make about the hypotheses that the regression parameter beta subscript 1 is equal to 0?

d. How much of the variation in the sample values of number of days absent does the model you estimated in part b explain?