For the next four problems just do the following:
(Answer any three of the four questions. If you answer a fourth question and identify that as an extra-credit question, it will be graded for four extra credit points)
A. Identify the independent variable(s) – if any (and define them precisely and indicate they are qualitative or quantitative)
B. Identify the dependent variable – if any (and define them precisely and indicate they are qualitative or quantitative)
C. Identify the type of analysis that is appropriate (Chi-Square test of independence, ANOVA, Regression, or Correlation)
D. Justify why the analysis you identified in part C is correct.
(3 + 3 + 3 + 3 points)
A.
B.
C.
D.
A.
B.
C.
D.
A.
B.
C.
D.
A.
B.
C.
D.
Problems — Full
For the next two problems just do the following:
A. Set up the appropriate hypotheses (in plain English)
B. Draw appropriate statistical conclusions (based on the printout provided). In your conclusions, make sure to indicate what values you specifically used from the printout (i.e., highlight/mark/circle the relevant values you need from the printout and then use them in your discussion/conclusions).
C. Present proper conclusions for the business problem.
Please refer to Printout #1 for this problem
A. H0:
H1:
B.
C.
MODEL 1988 Price
(in thousands) Number sold
(in thousands)
Hyundai
Oldsmobile Cierra
Nissan Sentra
Ford Tempo
Chev. Corsica
Pontiac Grand Am
Toyota Camry
Chev. Caprice 5.4
11.4
6.4
9.1
10.0
10.3
11.2
12.5 264
245
236
219
214
211
187
177
At = .05, is there evidence of relationship between the two variables?
(3 + 8 + 6 points)
Please refer to Printout #2 for this problem
A H0:
H1:
B.
C.
Essay Questions
Printout #1
One-way ANOVA: Mistakes versus NoiseLevel
Method
Null hypothesis All means are equal
Alternative hypothesis Not all means are equal
Significance level α = 0.05
Equal variances were assumed for the analysis.
Factor Information
Factor Levels Values
NoiseLevel 3 1, 2, 3
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
NoiseLevel 2 546.9 273.433 42.19 0.000
Error 27 175.0 6.481
Total 29 721.9
Model Summary
S R-sq R-sq(adj) R-sq(pred)
2.54588 75.76% 73.96% 70.07%
Means
NoiseLevel N Mean StDev 95% CI
1 10 13.900 2.923 (12.248, 15.552)
2 10 6.500 2.550 (4.848, 8.152)
3 10 3.800 2.098 (2.148, 5.452)
Pooled StDev = 2.54588
Printout #2
Regression Analysis: Number versus Price
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 3311 3310.9 7.77 0.032
Price 1 3311 3310.9 7.77 0.032
Error 6 2556 426.0
Total 7 5867
Model Summary
S R-sq R-sq(adj) R-sq(pred)
20.6396 56.43% 49.17% 23.44%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 302.9 30.9 9.80 0.000
Price -8.78 3.15 -2.79 0.032 1.00
Regression Equation
Number = 302.9 – 8.78 Price
Fits and Diagnostics for Unusual Observations
Obs Number Fit Resid Std
Resid
2 245.0 202.8 42.2 2.30 R
R Large residual