Chapter 5 Residual Analysis
Summary
1. Various formulas for standard deviations and confidence/prediction intervals:
Population model
Y = 0 + 1 X 1+ 2 X 2 + K X K +
Prediction equation (least square equation)
Y^ =b 0 +b1 X 1 +b2 X 2 + b K X K
Residuals
e=
Question 1:
Explain the difference between the information given by the tests of statistical significance t and Chi Square,
and measures of association Cramers V, Gamma and Pearsons correlation coefficient, r.
Can a test of significance show a statistical
Question 1:
Men
10.17
11.71
137.12
118
Mean hours per week
Standard Deviation
Variance
Sample Size
Women
9.08
12.26
150.31
157
a) Testing the Research Hypothesis
1. Assumptions:
It is assumed that the sample is random and independent. It is also assumed t
Question 1:
a) A bivariate table of frequencies for race and victimization:
Race
Victimization
Non-White
Yes
8
No
5
Total
13
White
8
9
17
Total
16
14
30
Race is the independent variable.
b) A bivariate table of percentages for race and victimization:
Race
Question 1:
Urban residents self-evaluation of the likelihood:
Likelihood of Victimization
Very Likely
Somewhat Likely
Not Likely
Total
Urban
90
70
80
240
Cumulative Frequency
90
160
240
a) Mode = Observation that occurred maximum number of times
Mode = V
Question 1:
Sample Size = 1,000
Average local crime stories = 3.01
Standard Deviation = 2.65
Assuming that the distribution of crime stories in newspapers is normal.
a) Calculation of Z score associated with a newspaper with 8 local crime stories:
Z score
Question 1:
a) Relationship between Incarceration Rate and Median State IncomeResearch Hypothesis: There is a significant linear correlation between Incarceration rate and Median
State Income.
Null Hypothesis: There is no significant linear correlation be