BA 215 Week 8 Project Assignment Final Project

W8 Final Project

Grantham University


In this analysis our work was smart. We tried to compare two study majors and see which of the two majors are better in terms of giving higher Return on Investment at the lowest cost.

The data contains the values for several variables and for the past 7 weeks we analyzed it to find out the valid and appropriate conclusions which are of our interest.

Collection of Data:

The data is collected for 21 schools for two major types “Business Major” and “Engineering Major” and 4 variables. The details of each of the variable is given below.

School Type: The school type, i.e. whether it is a Public school or private school.

Cost: The cost to complete the course in total (in $).

30 Year ROI: The 30-year ROI of the course for that school (in $).

Annual ROI: The annual percentage ROI of the course for that school (in %).

From the above description it can be seen that only the variable “School Type” is qualitative and nominal scaled and the rest of the variables are quantitative or numerical and ratio scaled. Thus our analysis was performed based on the best or most appropriate techniques.

Learned Information:

There are several points we noted and are important to draw any valid conclusions. Each of the points are given below separately with supporting results to make a valid interpretation.

  Cost Business Major Cost Engineering Major
Mean 188632 164680
Standard Error 11292.91004 14844.16453
Median 215200 214350
Mode #N/A #N/A
Standard Deviation 50503.42902 66385.12191
Sample Variance 2550596343 4406984411
Kurtosis 0.021694158 -1.919935884
Skewness -1.255321602 -0.324449097
Range 142870 165170
Minimum 87030 64930
Maximum 229900 230100
Sum 3772640 3293600
Count 20 20
  30 Year ROI Business Major 30 Year ROI Engineering Major
Mean 1477800 1838000
Variance 17673957895 32327578947
Observations 20 20
Hypothesized Mean Difference 0  
df 35  
t Stat -7.2039  
P(T<=t) one-tail 0.0000  
t Critical one-tail 1.3062  
P(T<=t) two-tail 0.0000  
t Critical two-tail 1.6896  
  Annual ROI Business Major Annual ROI Engineering Major
Mean 0.0782 0.09145
Variance 0.000120905 0.000213208
Observations 20 20
Pooled Variance 0.000167057  
Hypothesized Mean Difference 0  
df 38  
t Stat -3.2418  
P(T<=t) one-tail 0.0012  
t Critical one-tail 1.6860  
P(T<=t) two-tail 0.0025  
t Critical two-tail 2.0244  

Review and Conclusion:

  • School Type for each major:
  • The 1st thing we need to talk about is the school Type for each major. The obtained results concluded that the Business Major has comparatively more Private Schools than Engineering Major. The results included that, in the sample 16 out of 20 business schools i.e. 80% of the business schools are Private. On the other hand, 11 out of 20 i.e. only 55% engineering schools are Private.
  • The Cost for each major:
  • The next point we need to look at is the cost for each major. The obtained descriptive statistics would help us in this case.
  • The above table indicated that the average cost for Business Major is $188,632, whereas for Engineering Major it is $164,680. However, the hypothesis test indicated no significant difference between the average costs for the two majors. From the above results we can also see that the medians and the variations between the costs for the majors are not significantly different.
  • The 30 Year ROI for each major:
  • In week 6 we tested for the ROI between the majors. The results (given below) indicated that the 30 Year ROI for Business Major is significantly less than that of Engineering Major at 10% significance level.
  • The Annual % ROI for each major:
  • We have not particularly tested a two sample test for Annual % ROI between the majors. But if we do we have the following output,
  • The above output clearly indicates that the Business Major has significantly lower Annual % ROI than Engineering Major at 10% significance level.

From the above discussions we clearly have some good idea about the two majors. We compared almost all of the aspects of each of the variables which gave us plenty of information from which we can draw valid and important conclusions.

For example, we already know, on an average how much does which major costs or what is the average 30-year ROI for each major or how does the Annual % ROI for each major looks like. Both of the majors showed some promising results. But if we look at the data we can see that the Business Major is comparatively expensive. It requires more cost on an average and gives lower ROI. Both the 30-year ROI and the Annual % ROI is lower for Business major thus Engineering Major gives a better ROI. The hypothesis tests also showed that the 30-year ROI and the Annual % ROI both are significantly smaller for Business major.

But I expected little different results. As Business major is a very well-known major and promises higher compensations so I expected that the Business major would have a better ROI which is not getting prove by the data we have. Based on the above results thus I believe that Engineering Major would have a better ROI and the reason is the cost of education. The cost for Engineering Major is smaller than that of Business major making it a relatively cheaper option with higher ROI value.

However, the above result is solely based on the obtained sample and as the sample always varies so some other sample might give a result which is totally opposite. Even the population results might be opposite due to the same variation factor. This means that we may find that the Business major is actually giving a better ROI in general as compare to Engineering Major however the possibility of that is very small (but not impossible).

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