Chapter 9
Construct a scatterplot, find the value of the linear correlation coefficient r and use a significance level of α= 0.05 to determine whether there is a significant linear correlation between the two variables:
Pg 443, 11.) Fourteen different secondyear medical students took blood pressure measurements of the same patient and results are listed below. Is there a correlation between systolic and diastolic blood pressure values? Apart from correlation, is there some other method that might be used to address an important issue suggested by the data?
Systolic 
125 
107 
126 
110 
110 
107 
113 
126 
Diastolic 
78 
54 
81 
68 
66 
83 
71 
72 
Pg 461, 5.) Use the given data to find the equation of the regression line.
X 
0 
1 
2 
3 
4 
Y 
4 
1 
0 
1 
4 
_______________________________________________________________________________________________________
Pg470, 5.) Refer to information from Minitab listed below that was obtained by using the paird data consisting of neck size (in inches) and weight (in pounds) for the sample of bears. Along with the paired sample data, Minitab was also given a neck size of 25.0in. to be used for predicting the weight. Test slope.
Using the information provided in the display determine the value of the linear correlation coefficient. Given that there are 54 pairs of data, is there a significant linear correlation between bear neck sizes and bear weights?
Minitab
The regression equation is WEIGHT= 232 + 20.2 NECK
Predictor 
Coef 
SE Coef 
T 
P 
Constant 
231.70 
22.78 
10.17 
0.000 
NECK 
20.169 
1.069 
18.86 
0.000 
S= 43.9131 RSq= 87.2% RSq(adj)= 87.0%
Predicted Values for NEW observations
New Obs 
Fit 
SE Fit 
95% CI 
95% PI 
1 
272.53 
7.64 
257.21, 287.85 
183.09, 361.97 
Pg 480, 1.) Refer to the SPSS display that follows & answer the question. The SPSS display is based on sample of 54 bears.
Identify the multiple regression equation that expresses weight in terms of head length, length, and chest size.
Test Model
Test Individual variable
SPSS
Model Summary
Model 
R 
R square 
Adjusted R square 
Std Error of the estimate 
1 
0.963^{a} 
0.928 
0.924 
33.656 
a. Predictors: (Constant), Distance around the chest, Length of Head, Length of body
ANOVA^{b}
Model 
Sum of Squares 
Df 
Mean Square 
F 
Sig 
1 Regression 
729645.5 
3 
243215.153 
214.711 
0.000^{a} 
Residual 
56637.875 
50 
1132.758 


Total 
786283.3 
53 



Coefficients
^{ }
Model 
Unstandardized Coefficients B Std.Error 
Standard Coefficients Beta 
t (t ratio) 
Sig (p) 
1. (constant) 
271.711 31.617 

8.594 
0.000 
Length of head 
.870 5.676 
0.015 
0.153 
0.879 
Length of body 
.554 1.259 
0.049 
0.440 
0.662 
Distance around chest 
12.153 1.116 
0.933 
10.891 
0.000 
Chapter 10
Pg 500, 11.) Based on genotypes of parents, offspring are expected to have genotypes distributed in such a way that 25% have genotypes denoted by AA, 50% have genotypes denoted by Aa, and 25% have genotypes denoted by aa. When 145 offspring are obtained, it is found that 20 of them have AA genotypes, 90 have Aa genotypes, and 25 have aa genotypes. Test the claim that the observed genotype offspring frequencies fit the expected distribution of 25% for AA, 50% for Aa, and 25% for aa. Use significance level of 0.05.
P 515, 7.) The accompanying table summarizes successes and failures when subjects used different methods in trying to stop smoking. The determination of smoking or not smoking was made five months after the treatment was begun, and the data are based on results from the CDC. Use a 0.05 significance level to test the claim that success is independent of the method used. If someone wants to stop smoking, does the choice of the method make a difference?

Nicotine Gum 
Nicotine Patch 
Smoking 
191 
263 
Not Smoking 
59 
57 
Repeat exercise after adding:

Nicotine Gum 
Nicotine Patch 
Nicotine Inhaler 
Smoking 
191 
263 
95 
Not Smoking 
59 
57 
27 
Chapter 11
Pg 546, 3.) A random sample of males who finished the New York Marathon is partitioned into three categories with ages 2129, 3029, & 40 or over. The times (in seconds) are obtained from a random sample of those who finished. The analysis of variance results obtained from Excel are shown below.
a.) what is the null hypothesis?
b.) What is the alternative hypothesis
c.) Identify the value of the test statistic
d.) Find the critical value for a 0.05 significance level
e.) Indentify the Pvalue
f.) Is there sufficient evidence to support the claim that men in the different age categories have different mean times?
Excel
Source of variation 
SS 
df 
MS 
F 
Pvalue 
F crit 
Between groups 
3532063.284 
2 
1766031.642 
0.188679406 
0.828324293 
3.080387501 
Within Groups 
1010875649 
108 
9359959.71 



Total 
1014407712 
110 




Pg 558 8. & 9.) USE THESE TABLES:
Times in seconds for New York Marathon Runners
Age
2129 3039 40 & over
13, 615 14,677 14,528
18,784 16,090 17,034
14,256 14,086 14,935
Male 10,905 16,461 14,996
12,077 20,808 22,146
Female 16,401 15,357 17,260
14,216 16,771 25,399
15,402 15,036 18,647
15,326 16,297 15,077
12,047 17,636 25,898
Dependent Variable: TIME
Source 
Type III Sum of Squares 
Df 
Mean square 
F 
Sig 
Model 
8292665892^{a} 
6 
1367110967 
151.422 
0.000 
GENDER 
15225412.8 
1 
15225412.80 
1.686 
0.206 
AGE 
92086979.4 
2 
46043489.70 
5.100 
0.014 
GENDER*AGE 
21042068.6 
2 
10521034.30 
1.165 
0.329 
Error 
216683456 
24 
9028477.350 


Total 
8419349258 
30 



^{a. }R squared=0.974 (Adjusted R squared= 0.968)
8.) Interaction Effect. These the null hypothesis that the times are not affected by an interaction between gender and age category. What do you conclude?
9.) Assume that the marathon running times are not affected by an interaction between gender and age category. Is there sufficient evidence to support the claim that gender has an effect on running times?
Pg 558. Refer to the display which is from 24 subject that were given hearing tests using four different lists of words. The 24 subjects had normal hearing and the tests were conducted with no background noise. The main objective was to determine whether the four lists are equally difficult to understand. In the original table of hearing test scores, each cell has one entry.
Analysis of Variance for Hearing
Source 
DF 
SS 
MS 
F 
P 
Subject 
23 
3231.6 
140.5 
3.87 
0.000 
List 
3 
920.5 
306.8 
8.45 
0.000 
Error 
69 
2506.5 
36.3 


Total 
95 
6658.6 



11.) Assuming that there is no effect on hearing test scores from an interaction between subject and list, is there sufficient evidence to support the claim that the choice of subject has an effect on the hearing test score? Interpret the results by explaining why it makes practical sense.
Subject  Mathematics 
Due By (Pacific Time)  11/05/2013 05:00 pm 
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