Needs to Done on Time!!!
ylang
Week6Project2.docx
Project Week 6
Using the ROI data set:
1. For each of the 2 majors test the hypothesis at the 5% significance level:
. The mean ‘Cost’ for a college is $160,000. Be sure to interpret your results.
Business major:
Since P(T<=t) two-tail = 0.020173879 < 0.05, so we should reject the null hypothesis, that is to say, the mean ‘Cost’ for Business major is not $160,000.
Engineering major:
Since P(T<=t) two-tail = 0.75598907>0.05, so we should cannot reject the null hypothesis, that is to say, the mean ‘Cost’ for Engineering major is $160,000.
· For Business versus Engineering majors conduct a two sample test of the hypothesis at the 10% significance level (assume the variances are not equal):
. The average ’30-Year ROI’ for Business majors is less than for Engineering Majors. Be sure to interpret your results.
|
t-Test: Two-Sample Assuming Unequal Variances |
|
|
|
|
|
|
|
|
30 Year ROI Business |
30 Year ROI Engineering |
|
Mean |
1477800 |
1838000 |
|
Variance |
17673957895 |
32327578947 |
|
Observations |
20 |
20 |
|
Hypothesized Mean Difference |
0 |
|
|
df |
35 |
|
|
t Stat |
-7.203889288 |
|
|
P(T<=t) one-tail |
1.04423E-08 |
|
|
t Critical one-tail |
1.306211802 |
|
|
P(T<=t) two-tail |
2.08847E-08 |
|
|
t Critical two-tail |
1.689572458 |
|
Since P(T<=t) one-tail = 1.04423E-08<0.1, so we cannot reject the null hypothesis, that is to say, the average ’30-Year ROI’ for Business majors is less than for Engineering Majors.
Costtest
Mean188632160000
Variance25505963430
Observations2020
Hypothesized Mean Difference0
df19
t Stat2.535396094
P(T<=t) one-tail0.01008694
t Critical one-tail1.729132812
P(T<=t) two-tail0.020173879
t Critical two-tail2.093024054
Costtest
Mean164680160000
Variance44069844110
Observations2020
Hypothesized Mean Difference0
df19
t Stat0.31527541
P(T<=t) one-tail0.37799454
t Critical one-tail1.72913281
P(T<=t) two-tail0.75598907
t Critical two-tail2.09302405
