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Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. -Below is a plot showing residuals versus fitted values for the estimated regression equation relating monthly sales of coffee to price per kilogram. Are all the conditions for linear regression met? Explain. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. -Below is a plot showing residuals versus fitted values for the estimated regression equation relating monthly sales of coffee to price per kilogram. Are all the conditions for linear regression met? Explain. -Below is a plot showing residuals versus fitted values for the estimated regression equation relating monthly sales of coffee to price per kilogram. Are all the conditions for linear regression met? Explain. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. -Below is a plot showing residuals versus fitted values for the estimated regression equation relating monthly sales of coffee to price per kilogram. Are all the conditions for linear regression met? Explain.

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The residual plot indicates th...

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Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot and summary statistics are shown below. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot and summary statistics are shown below. -A pair of variables, x and y, have a correlation coefficient of -0.8851. Which of the following statements is true? A) x explains about 78.34 percent of the variation in y. B) x explains about 88.51 percent of the variation in y. C) y explains about 78.34 percent of the variation in x. D) x cannot explain about 78.34 percent of the variation in y. E) y explains about 88.51 percent of the variation in x. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot and summary statistics are shown below. -A pair of variables, x and y, have a correlation coefficient of -0.8851. Which of the following statements is true? A) x explains about 78.34 percent of the variation in y. B) x explains about 88.51 percent of the variation in y. C) y explains about 78.34 percent of the variation in x. D) x cannot explain about 78.34 percent of the variation in y. E) y explains about 88.51 percent of the variation in x. -A pair of variables, x and y, have a correlation coefficient of -0.8851. Which of the following statements is true?


A) x explains about 78.34 percent of the variation in y.
B) x explains about 88.51 percent of the variation in y.
C) y explains about 78.34 percent of the variation in x.
D) x cannot explain about 78.34 percent of the variation in y.
E) y explains about 88.51 percent of the variation in x.

F) A) and D)
G) C) and E)

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Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -What percent of the variability in cash bonuses can be explained by pay? A) 100% B) 85% C) 73% D) 30% E) 54% Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -What percent of the variability in cash bonuses can be explained by pay? A) 100% B) 85% C) 73% D) 30% E) 54% -What percent of the variability in cash bonuses can be explained by pay?


A) 100%
B) 85%
C) 73%
D) 30%
E) 54%

F) All of the above
G) B) and E)

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Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -The intercept of the estimated regression line that relates the response variable (cash bonus) to the predictor variable (annual pay) is A) 0.409 B) -16945 C) 0.54 D) 3.45 E) none of the above Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -The intercept of the estimated regression line that relates the response variable (cash bonus) to the predictor variable (annual pay) is A) 0.409 B) -16945 C) 0.54 D) 3.45 E) none of the above -The intercept of the estimated regression line that relates the response variable (cash bonus) to the predictor variable (annual pay) is


A) 0.409
B) -16945
C) 0.54
D) 3.45
E) none of the above

F) D) and E)
G) None of the above

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Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -Based on the estimated regression line, the cash bonus for an executive at Johnson Financial earning $82, 613 a year would be A) $11,863 B) $16,844 C) $27,682 D) $4,958 E) $15,819 Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -Based on the estimated regression line, the cash bonus for an executive at Johnson Financial earning $82, 613 a year would be A) $11,863 B) $16,844 C) $27,682 D) $4,958 E) $15,819 -Based on the estimated regression line, the cash bonus for an executive at Johnson Financial earning $82, 613 a year would be


A) $11,863
B) $16,844
C) $27,682
D) $4,958
E) $15,819

F) C) and D)
G) All of the above

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Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. -Use the estimated regression equation to answer the following questions. a. Estimate the monthly sales for a variety of coffee that costs $20.00 per kilogram. b. How confident should you be in this estimate? Explain. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. -Use the estimated regression equation to answer the following questions. a. Estimate the monthly sales for a variety of coffee that costs $20.00 per kilogram. b. How confident should you be in this estimate? Explain. -Use the estimated regression equation to answer the following questions. a. Estimate the monthly sales for a variety of coffee that costs $20.00 per kilogram. b. How confident should you be in this estimate? Explain.

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a. 1.79 kilograms
b. Not very ...

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Consider the following to answer the question(s) below: To determine whether the tip left at the end of a meal is related to the size of the total bill at their restaurant, Chez Michelle, data were gathered for 10 customers. The data and summary statistics are shown below. Consider the following to answer the question(s) below: To determine whether the tip left at the end of a meal is related to the size of the total bill at their restaurant, Chez Michelle, data were gathered for 10 customers. The data and summary statistics are shown below. -The residual for the estimated tip for a total bill of $120 would be A) $5.13 B) $19.00 C) 0 D) -$11.45 E) $9.38 -The residual for the estimated tip for a total bill of $120 would be


A) $5.13
B) $19.00
C) 0
D) -$11.45
E) $9.38

F) None of the above
G) A) and B)

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Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -Comment on whether each of the following conditions for correlation / linear regression is met. a. Quantitative variable condition. b. Linearity condition. c. Outlier condition. Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -Comment on whether each of the following conditions for correlation / linear regression is met. a. Quantitative variable condition. b. Linearity condition. c. Outlier condition. -Comment on whether each of the following conditions for correlation / linear regression is met. a. Quantitative variable condition. b. Linearity condition. c. Outlier condition.

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a. Yes, both variables are qua...

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Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. -Comment on whether each of the following conditions for correlation / linear regression is met. a. Quantitative variable condition. b. Linearity condition. c. Outlier condition. Consider the following to answer the question(s) below: A small independent organic food store offers a variety of specialty coffees. To determine whether price has an impact on sales, the managers kept track of how many kilograms of each variety of coffee were sold last month. The data, scatterplot, and summary statistics are shown below. -Comment on whether each of the following conditions for correlation / linear regression is met. a. Quantitative variable condition. b. Linearity condition. c. Outlier condition. -Comment on whether each of the following conditions for correlation / linear regression is met. a. Quantitative variable condition. b. Linearity condition. c. Outlier condition.

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a. Yes, both variables are qua...

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Consider the following to answer the question(s) below: To determine whether the tip left at the end of a meal is related to the size of the total bill at their restaurant, Chez Michelle, data were gathered for 10 customers. The data and summary statistics are shown below. Consider the following to answer the question(s) below: To determine whether the tip left at the end of a meal is related to the size of the total bill at their restaurant, Chez Michelle, data were gathered for 10 customers. The data and summary statistics are shown below. -If a residual plot exhibits a curved pattern in the residuals, this means that A) The relationship between x and y is also curved. B) The residuals are not normally distributed. C) x and y are positively correlated. D) The residuals have a constant variance. E) The relationship between x and y is linear. -If a residual plot exhibits a curved pattern in the residuals, this means that


A) The relationship between x and y is also curved.
B) The residuals are not normally distributed.
C) x and y are positively correlated.
D) The residuals have a constant variance.
E) The relationship between x and y is linear.

F) A) and E)
G) D) and E)

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Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -Below is a plot showing residuals versus fitted values for the estimated regression equation relating cash bonus to pay for the account executives at Johnson Financial. Are all the conditions for linear regression met? Explain. Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -Below is a plot showing residuals versus fitted values for the estimated regression equation relating cash bonus to pay for the account executives at Johnson Financial. Are all the conditions for linear regression met? Explain. -Below is a plot showing residuals versus fitted values for the estimated regression equation relating cash bonus to pay for the account executives at Johnson Financial. Are all the conditions for linear regression met? Explain. Consider the following to answer the question(s) below: To determine whether the cash bonuses paid by Johnson Financial Group are related to annual pay, data were gathered for 10 account executives who received such bonuses in 2007. The data, scatterplot and summary statistics are shown below. -Below is a plot showing residuals versus fitted values for the estimated regression equation relating cash bonus to pay for the account executives at Johnson Financial. Are all the conditions for linear regression met? Explain.

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The residual plot shows that t...

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Consider the following to answer the question(s) below: To determine whether the tip left at the end of a meal is related to the size of the total bill at their restaurant, Chez Michelle, data were gathered for 10 customers. The data and summary statistics are shown below. Consider the following to answer the question(s) below: To determine whether the tip left at the end of a meal is related to the size of the total bill at their restaurant, Chez Michelle, data were gathered for 10 customers. The data and summary statistics are shown below. -A manufacturing company is interested in predicting the number of defects (y) that will be produced each hour on the assembly line (x) . Using sample data they estimate the equation as defects = 5.67 + 0.048 (hours) . Which of the following statements is true? A) The correlation between x and y is positive. B) 4.8% of the variability in y is explained by x. C) 23.08% of the variability in y is explained by x. D) An increase in x of one-unit will result in an average increase of 5.67 in y. E) The relationship between x and y could be either positive or negative. -A manufacturing company is interested in predicting the number of defects (y) that will be produced each hour on the assembly line (x) . Using sample data they estimate the equation as defects = 5.67 + 0.048 (hours) . Which of the following statements is true?


A) The correlation between x and y is positive.
B) 4.8% of the variability in y is explained by x.
C) 23.08% of the variability in y is explained by x.
D) An increase in x of one-unit will result in an average increase of 5.67 in y.
E) The relationship between x and y could be either positive or negative.

F) A) and B)
G) A) and C)

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