Louis katz, a cost accountant at papalote plastics, inc. (ppi), is

Question 13

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

Louis’s regression model is _____________.

 y = -0.358 + 3.996x

 y = 3.996 – 0.358x

 y = 0.358 + 3.996x

 y = -3.996 + 0.358x

 y = 3.996 + 0.358x

Question 20

According to a study several years ago by the Personal Communications Industry Association, the average wireless phone user earns \$62,600 per year. Suppose a researcher believes that the average annual earnings of a wireless phone user are lower now, and he sets up a study in an attempt to prove his theory. He randomly samples 18 wireless phone users and finds out that the average annual salary for this sample is \$58,974, with a population standard deviation of \$7,810. Use α = .01to test the researcher’s theory. Assume wages in this industry are normally distributed.

The value of the test statistic rounded to 2 decimal places is z =   and we .

The tolerance is +/- 0.05.

A random sample of 51 items is taken, with   and s2 = 25.68. Use these data to test the following hypotheses, assuming you want to take only a 1% risk of committing a Type I error and that x is normally distributed.

StartLayout 1st Row 1st Column Upper H Subscript 0 Baseline colon mu equals 60 EndLayout StartLayout 1st Row 1st Column Upper H Subscript a Baseline colon mu less-than 60 EndLayout

The value of the test statistic is   and we  .

Question 34

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
α = 0.05, Louis should ___________.

 not reject H0: β1 = 0

 reject H0: β1 = 0

 do not reject H0: β0 = 0

 suspend judgment

 increase the sample size
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