Chapter 5 Exercise 6 (page 170)
(a) No, the relationship is directional. In fact, the decrease in the number of different illnesses patients have might diminish the length of hospital stays, although it depends on many other factors. However, the reduction in length of hospital stays could not reduce the number of different illnesses patients have as it does not make sense.
(b) The length of hospital stays is an important factor of cost of the hospital visits, therefore the reduction in the length of hospital stays could reduce the cost of the hospital visits although other factors are present.
Chapter 5 Exercise 9 (page 176-177)
(a) The data do not support the concern, since there is no substantial negative correlation between the score for each employee and the length of time between when the evaluation …show more content…
(b) A particular company has a value of 15 on the measure of future growth its P E ratio is 4.5 what would you conclude about this company’s PE? Briefly explain
The PE ratio:
PE = 3 + (0.9 * 15) = 16.5
But the actual PE ratio of the company is 4.5.
The model adequacy of the regression model is measured using the R squared value. The R squared = 18%. Therefore, only 18% of the variability in the PE ratio can be explained by the regression model. Also, the SE of estimate is 5 which, it is relatively high and so, the accuracy of prediction will be low. In conclusion, the PE ratio for the company is 4.5 and the regression model is not significant in foreseeing the PE ratio.
(c) Since 13.2 is greater than 9 can you conclude the PE ratio has a stronger relationship to dividends than future growth? If not, what would you need to know to conclude which variable has a stronger relationship to the P E ratio? Briefly explain.
The correlation coefficient between X and Y: r = β x (SD of X divided by SD of Y) β is the regression coefficient, SD X (independent variable) and SD Y (dependent
(a) No, the relationship is directional. In fact, the decrease in the number of different illnesses patients have might diminish the length of hospital stays, although it depends on many other factors. However, the reduction in length of hospital stays could not reduce the number of different illnesses patients have as it does not make sense.
(b) The length of hospital stays is an important factor of cost of the hospital visits, therefore the reduction in the length of hospital stays could reduce the cost of the hospital visits although other factors are present.
Chapter 5 Exercise 9 (page 176-177)
(a) The data do not support the concern, since there is no substantial negative correlation between the score for each employee and the length of time between when the evaluation …show more content…
(b) A particular company has a value of 15 on the measure of future growth its P E ratio is 4.5 what would you conclude about this company’s PE? Briefly explain
The PE ratio:
PE = 3 + (0.9 * 15) = 16.5
But the actual PE ratio of the company is 4.5.
The model adequacy of the regression model is measured using the R squared value. The R squared = 18%. Therefore, only 18% of the variability in the PE ratio can be explained by the regression model. Also, the SE of estimate is 5 which, it is relatively high and so, the accuracy of prediction will be low. In conclusion, the PE ratio for the company is 4.5 and the regression model is not significant in foreseeing the PE ratio.
(c) Since 13.2 is greater than 9 can you conclude the PE ratio has a stronger relationship to dividends than future growth? If not, what would you need to know to conclude which variable has a stronger relationship to the P E ratio? Briefly explain.
The correlation coefficient between X and Y: r = β x (SD of X divided by SD of Y) β is the regression coefficient, SD X (independent variable) and SD Y (dependent