# 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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