The College Board reported the following mean scores for the three parts of the Scholastic Aptitude Test (SAT) (The World Almanac, 2009):  Assume that the population standard deviation on each part of the test is standard deviation= 100. What is the probability a sample of 90 test takers will provide a sample mean test score within 10 points of the population mean of 502 on the Critical Reading part of the test (to 4 decimals)? What is the probability a sample of 90 test takers will provide a sample mean test score within 10 points of the population mean of 515 on the Mathematics part of the test (to 4 decimals)? What is the probability a sample of 100 test takers will provide a sample mean test score within 10 of the population mean of 494 on the writing part of the test (to 4 decimals)?  (next question) The mean tax-return preparation fee H&R Block charged retail customers last year was $183 (The Wall Street Journal, March 7, 2012). Use this price as the population mean and assume the population standard deviation of preparation fees is $50. Round your answers to four decimal places. a. What is the probability that the mean price for a sample of 30 H&R Block retail customers is within $8 of the population mean? b. What is the probability that the mean price for a sample of 50 H&R Block retail customers is within $8 of the population mean? c. What is the probability that the mean price for a sample of 100 H&R Block retail customers is within $8 of the population mean? d. Which, if any, of the sample sizes in parts (a), (b), and (c) would you recommend to have at least a .95 probability that the sample mean is within $8 of the population mean?  Use the data in Problem 4-22 and develop a regression model to predict selling price based on the square footage, number of bedrooms, and age. Use this to predict the selling price of a 10-year-old, 2,000-square-foot house with 3 bedrooms. Also 1) State the linear equation. 2) Explain the overall statistical significance of the model. 3) Explain the statistical significance for each independent variable in the model 4) Interpret the Adjusted R2. 5) Is this a good predictive equation(s)? Which variables should be excluded (if any) and why? Explain. SELLING SQUARE AGE PRICE($) FOOTAGE BEDROOMS (YEARS) 64,000 1,670 2 30 59,000 1,339 2 25 61,500 1,712 3 30 79,000 1,840 3 40 87,500 2,300 3 18 92,500 2,234 3 30 95,000 2,311 3 19 113,000 2,377 3 7 115,000 2,736 4 10 138,000 2,500 3 1 142,500 2,500 4 3 144,000 2,479 3 3 145,000 2,400 3 1 147,500 3,124 4 0 144,000 2,500 3 2 155,500 4,062 4 10 165,000 2,854 3 3 ...

1. The College Board reported the following mean scores for the
three parts of the Scholastic Aptitude Test (SAT) (The World
Almanac, 2009):
Assume that the population standard deviation on each part of
the test is standard deviation= 100.
What is the probability a sample of 90 test takers will provide a
sample mean test score within 10 points of the population mean
of 502 on the Critical Reading part of the test (to 4 decimals)?
What is the probability a sample of 90 test takers will provide a
sample mean test score within 10 points of the population mean
of 515 on the Mathematics part of the test (to 4 decimals)?
What is the probability a sample of 100 test takers will provide
a sample mean test score within 10 of the population mean of
494 on the writing part of the test (to 4 decimals)?
(next question)
The mean tax-return preparation fee H&R Block charged retail
customers last year was $183 (The Wall Street Journal, March
7, 2012). Use this price as the population mean and assume the
population standard deviation of preparation fees is $50.
Round your answers to four decimal places.
a. What is the probability that the mean price for a sample of 30
H&R Block retail customers is within $8 of the population

2. mean?
b. What is the probability that the mean price for a sample of 50
H&R Block retail customers is within $8 of the population
mean?
c. What is the probability that the mean price for a sample of
100 H&R Block retail customers is within $8 of the population
mean?
d. Which, if any, of the sample sizes in parts (a), (b), and (c)
would you recommend to have at least a .95 probability that the
sample mean is within $8 of the population mean?
Use the data in Problem 4-22 and develop a regression model to
predict selling price based on the square footage, number of
bedrooms, and age. Use this to predict the selling price of a 10-
year-old, 2,000-square-foot house with 3 bedrooms. Also
1) State the linear equation.
2) Explain the overall statistical significance of the model.
3) Explain the statistical significance for each independent
variable in the model
4) Interpret the Adjusted R2.
5) Is this a good predictive equation(s)? Which variables should
be excluded (if any) and why? Explain.
SELLING SQUARE AGE
PRICE($) FOOTAGE BEDROOMS (YEARS)
64,000 1,670 2 30

3. 59,000 1,339 2 25
61,500 1,712 3 30
79,000 1,840 3 40
87,500 2,300 3 18
92,500 2,234 3 30
95,000 2,311 3 19
113,000 2,377 3 7
115,000 2,736 4 10
138,000 2,500 3 1
142,500 2,500 4 3
144,000 2,479 3 3
145,000 2,400 3 1
147,500 3,124 4 0
144,000 2,500 3 2
155,500 4,062 4 10
165,000 2,854 3 3