Statistics Solutions
- Based on the sample data and a significance level equal to 0.05, does there appear to be a difference in the proportion of loan defaults between residential and commercial customers?
- Prepare a short response to the Vintner board of directors. Include in your report a graph of the data that supports your statistical analysis.
- Consider the outcome of the hypothesis test in part a. In the last five audits, 10 residential and 10 commercial customers were selected. In three of the audits, there were more residential than commercial loan defaults. Determine the probability of such an occurrence.
t-Test: Two-Sample Assuming Equal Variances | ||
Residential Loan Status | Commercial Loan Status | |
Mean | 1.155 | 1.180952 |
Variance | 0.131633 | 0.149634 |
Observations | 200 | 105 |
Pooled Variance | 0.137812 | |
Hypothesized Mean Difference | 0 | |
df | 303 | |
t Stat | -0.58009 | |
P(T<=t) one-tail | 0.281143 | |
t Critical one-tail | 1.649898 | |
P(T<=t) two-tail | 0.562286 | |
t Critical two-tail | 1.967824 |
Q2The California State Highway Patrol recently conducted a study on a stretch of interstate highway south of San Francisco to determine what differences, if any, existed in driving speeds of cars licensed in California and cars licensed in Nevada. One of the issues to be examined was whether there was a diffrence in the variability of driving speeds between cars licensed in the two states. The data file Speed-Test contains speeds of 140 randomly selected California cars and 75 randomly selected Nevada cars. Based on these sample results, can you conclude at the 0.05 level of significance there is a difference between the variations in driving speeds for cars licensed in the two states?
t-Test: Two-Sample Assuming Equal Variances | ||
California Cars | Out-of-State Cars | |
Mean | 64.45 | 61.96 |
Variance | 64.29245 | 59.76865 |
Observations | 140 | 75 |
Pooled Variance | 62.7208 | |
Hypothesized Mean Difference | 0 | |
df | 213 | |
t Stat | 2.197197 | |
P(T<=t) one-tail | 0.014542 | |
t Critical one-tail | 1.652039 | |
P(T<=t) two-tail | 0.029084 | |
t Critical two-tail | 1.971164 |
There is a difference between the two cars speed and thus it can be said that there is a significant difference in the two states.
Q3 The Ecco Company makes electronics products for distribution throughout the world. As a member of the quality department, you are interested in the warranty claims that are made by customers who have experienced problems with Ecco products. The file called Ecco contains data for a random sample of warranty claims. Large warranty claims not only cost the company money but also provide adverse publicity. The quality manager has asked you to provide her with a range of values that would represent the percentage of warranty claims filed for more than $300. Provide this information for your quality manager.
Sum of %total | Column Labels | ||||
Row Labels | 1 | 2 | 3 | 4 | Grand Total |
1 | 0.20965 | 0.300377 | 0.146518 | 0.029564 | 0.686109 |
1 | 0.18429 | 0.195902 | 0.090594 | 0.01328 | 0.484067 |
2 | 0.008442 | 0.073476 | 0.044513 | 0.016283 | 0.142714 |
3 | 0.016917 | 0.030999 | 0.011412 | 0.059328 | |
2 | 0.097534 | 0.106477 | 0.039274 | 0.023157 | 0.266442 |
1 | 0.090126 | 0.08719 | 0.006607 | 0.012813 | 0.196737 |
2 | 0.007408 | 0.019287 | 0.023091 | 0.049785 | |
3 | 0.009577 | 0.010344 | 0.019921 | ||
3 | 0.010544 | 0.011278 | 0.025626 | 0.047449 | |
1 | 0.017852 | 0.017852 | |||
2 | 0.010544 | 0.011278 | 0.007775 | 0.029597 | |
Grand Total | 0.317728 | 0.418132 | 0.211418 | 0.052721 | 1 |
Q4 The state transportation department recently conducted a study of motorists in Idaho. Two main factors of interest were whether the vehicle was insured with liability insurance and whether the driver was wearing a seat belt. A random sample of 100 cars was stopped at various locations throughout the state. The data are in the file called Liabins. The investigators were interested in determining whether seat belt status is independent of insurance status. Conduct the appropriate hypothesis test using a 0.05 level of significance and discuss your results.
Driving Citations | Vehicle Year | Driver Sex | Driver Age | Seat Belt Status | Law Knowledge | Employment Status | Year In State | Registered Vehicles | Years Education | Insurance Certificate Status | Insurance Status | |
Driving Citations | 1 | |||||||||||
Vehicle Year | 0.030072 | 1 | ||||||||||
Driver Sex | -0.25747 | 0.258334 | 1 | |||||||||
Driver Age | -0.29097 | 0.116277 | 0.041819 | 1 | ||||||||
Seat Belt Status | 0.009689 | -0.22479 | -0.11649 | -0.1071 | 1 | |||||||
Law Knowledge | -0.02023 | -0.06389 | -0.04404 | 0.164283 | 0.177074 | 1 | ||||||
Employment Status | -0.1347 | 0.098752 | 0.192186 | 0.306856 | -0.06546 | 0.186704 | 1 | |||||
Year In State | -0.17428 | 0.12232 | -0.08811 | 0.610012 | 0.018003 | 0.022402 | 0.03915 | 1 | ||||
Registered Vehicles | -0.17653 | -0.04777 | -0.13674 | 0.330033 | -0.09816 | 0.046213 | 0.011787 | 0.285945 | 1 | |||
Years Education | -0.00536 | 0.247238 | 0.137123 | 0.048782 | -0.28447 | -0.22471 | 0.059279 | 0.055306 | 0.1084 | 1 | ||
Insurance Certificate Status | 0.067598 | -0.07084 | -0.02452 | -0.0343 | -0.05786 | 0.080405 | 0.138235 | -0.10396 | -0.1895 | 0.102671 | 1 | |
Insurance Status | -0.00283 | 0.060221 | -0.12737 | 0.046721 | 0.088611 | -0.07135 | 0.042459 | 0.166711 | 0.149672 | -0.01691 | -0.14086 | 1 |
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.088611 | |||||||
R Square | 0.007852 | |||||||
Adjusted R Square | -0.00227 | |||||||
Standard Error | 0.525144 | |||||||
Observations | 100 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 1 | 0.213886 | 0.213886 | 0.775578 | 0.380652 | |||
Residual | 98 | 27.02611 | 0.275777 | |||||
Total | 99 | 27.24 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | 1.571429 | 0.198486 | 7.917078 | 3.81E-12 | 1.17754 | 1.965317 | 1.17754 | 1.965317 |
Insurance Status | 0.18126 | 0.20582 | 0.880669 | 0.380652 | -0.22718 | 0.589703 | -0.22718 | 0.589703 |
Seat belt status is independent of insurance status
Q5 An economist for the state government of Mississippi recently collected the data contained in the file called Mississippi on the percentage of people unemployed in the state at randomly selected points in time over the past 25 years and the interest rate of Treasury bills offered by the federal government at that point in time.
- Develop a plot showing the relationship between the two variables.
- Describe the relationship as being either linear or curvilinear.
- Develop a simple linear regression model with unemployment rate as the dependent variable.
- Write a short report describing the model and indicating the important measures.
SUMMARY OUTPUT | ||||||||
Regression Statistics | ||||||||
Multiple R | 0.973125 | |||||||
R Square | 0.946972 | |||||||
Adjusted R Square | 0.943658 | |||||||
Standard Error | 0.788972 | |||||||
Observations | 18 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 1 | 177.8604 | 177.8604 | 285.7299 | 1.26E-11 | |||
Residual | 16 | 9.959637 | 0.622477 | |||||
Total | 17 | 187.82 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | -19.3726 | 1.586889 | -12.2079 | 1.6E-09 | -22.7366 | -16.0085 | -22.7366 | -16.0085 |
Interest Rates (x) | 2.902579 | 0.171714 | 16.90355 | 1.26E-11 | 2.538561 | 3.266597 | 2.538561 | 3.266597 |
Linear
Quadratic
The equation is a quadratic one.