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Statistics - Regression and Coefficients

See the attached file.

1. Florida condominiums are popular winter retreats for many North Americans. In recent years the price has steadily increased. A real estate agent wanted to know why prices of similar-size apartments in the same building vary. A possible answer lies in the floor level. It may be that the higher the floor is in the building, the greater the sale price of the apartment. He recorded the price (in $1,000s) of 1,200 square feet condominiums in several buildings in the same location that have sold recently and the floor number of the condominium. Data in File below.

a) Determine the regression line.
b) What do the coefficients tell you about the relationship between the two variables?

2. A newspaper publisher, trying to pinpoint his market's characteristics, wondered whether the way people read a newspaper is related to the reader's educational level. A survey asked adult readers which section of the paper they read first and asked to report their highest educational level. These data were recorded (column 1 = first section read where 1 = front page, 2 = sports, 3 = editorial, and 4 = other) and column 2 = educational level where 1 = did not complete high school, 2 = high school graduate, 3 = university or college graduate, and 4 = postgraduate degree). Is there sufficient evidence to conclude that the four methods differ in their success? Data in File below.

3.To determine how the number of housing starts is affected by mortgage rates, an economist recorded the average mortgage rate and the number of housing starts in a large country for the past 10 years. These data are listed here. Data in file below.
Rate 8.5 7.8 7.6 7.5 8.0 8.4 8.8 8.9 8.5 9.0
Starts 115 111 185 201 206 167 155 117 133 150

(a) Determine the regression line.
(b) What do the coefficients of the regression line tell you about the relationship between mortgage rates and housing starts?

4. (a) Use Fisher's LSD method with ? = .05 to determine which population means differ:
k = 3 n1 = 10 n2 = 10 n3 = 10
MSE = 700 x1 bar = 128 x2 bar = 101.4 x3 bar = 133.7
(b) Repeat part (a), using the Bonferroni adjustment method.
(c) Repeat part (a), using Turkey 's multiple comparison method.

5. Suppose that you have the following data:
x 3 5 2 6 1 4
y 25 110 9 250 3 71
a) Draw the scatter diagram. Does it appear that x and y are related? If so, how?
b) Test to determine whether there is evidence of a linear relationship.

6. Do cell phones cause cancer? This is a multibillion dollar question. There are currently dozens of lawsuits pending that claim cell phones use caused cancer. To help shed light on the issue, several scientific research projects have been undertaken. One such project was conducted by Danish researchers. This 13-year study examined 420,000 Danish cell phone users. The scientists determined the number of Danes who would be expected to contract various forms of cancer. The expected number and the actual number of cell phone users who developed each type of cancer are listed below.
Cancer Expected Number Actual Number
Brain/nervous system 143 - 135
Salivary glands 9 - 7
Leukemia 80 - 77
Pharynx 52 - 32
Esophagus 57 - 42
Eye 12 - 8
Thyroid 13 - 13
a) Can we infer from these data that there is a relationship between cell phone use and cancer?

b) Discuss the results, including whether the data are observational or experimental. provide several interpretations of the statistics. in particular, indicate whether you can infer that cell phone use causes cancer.

Please be specific in your solutions.

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Solution Summary

The solution determines the regression and coefficients of the statistics questions.

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