EBK BUSINESS STATISTICS
7th Edition
ISBN: 8220102743984
Author: STEPHAN
Publisher: PEARSON
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1. Develop a simple linear regression equation for starting salaries using an independent
variable that has the closest relationship with the salaries. Explain how you chose this
variable.
The following equation is the result of performing a multiple regression analysis:
Job performance = 10 + (5*job knowledge) + (0.7* conscientiousness), where job
knowledge is measured on a scale of 0-5 and conscientiousness is measured on a
scale of 0 to 100. Which of the following conclusions is correct?
!!
O If a person scored 5 on job knowledge and 100 on conscientiousness he or she
would have the maximum predictive score possible
If a person scored 0 on both job knowledge and conscientiousness, his or her
predictive score is 0
ONeither job knowledge nor conscientiousness predicts performance
O Conscientiousness is less important than job knowledge.
Question 3!
For a measuring tool to be usefulitmus be
Louis Katz, a cost accountant at Papalote Plastics, Inc. (PPI), is analyzing the manufacturing costs of a molded plastic telephone handset produced by PPI. Louis's independent variable is production lot size (in 1,000's of units), and his dependent variable is the total cost of the lot (in $100's). Regression analysis of the data yielded the following tables.
Coefficients
Standard Error
t Statistic
p-value
Intercept
3.996
1.161268
3.441065
0.004885
x
0.358
0.102397
3.496205
0.004413
Source
df
SS
MS
F
Se = 0.898
Regression
1
9.858769
9.858769
12.22345
r2 = 0.526341
Residual
11
8.872
0.806545
Total
12
18.73077
Using a = 0.05, Louis should ________________.
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- Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300arrow_forwardXYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict the stock price to be in January 2012? January 2013?arrow_forwardbThe average rate of change of the linear function f(x)=3x+5 between any two points is ________.arrow_forward
- For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.arrow_forwardSuppose you are examining a multi-variable linear regression model that was designed to predict the weight of a person, measured in kg, using 3 predictor variables. One of the variables used in this analysis is "height", with the coefficient of this variable being equal to 3.96, with a standard error of the coefficient equal to 1.168. There are 300 datapoints in the dataset. Using this information, what would be the test statistic (t-ratio) for the test to see if the variable "height" is significant? Only round final answer. Round to two decimal places.arrow_forwardSuppose that in a certain neighborhood, the cost of a home is proportional to the size of the home in square feet. If the regression equation quantifying this relationship is found to be (cost) = 94.872*(size) + 612.216, what does the slope indicate? Question 21 options: 1) When cost increases by 1 dollar, size increases by 94.872 square feet. 2) We are not given the dataset, so we cannot make an interpretation. 3) When size increases by 1 square foot, cost increases by 612.216 dollars. 4) When cost increases by 1 dollar, size increases by 612.216 square feet. 5) When size increases by 1 square foot, cost increases by 94.872 dollars.arrow_forward
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