RESEARCH QUESTION 1
Write the first research question. Perform the statistical hypothesis tests to answer your research question. Perform both the parametric test and the corresponding non-parametric test and explain the results. For the parametric test, check all necessary assumptions. Finally, describe which test (parametric or non-parametric) is more suitable for your particular case and why. Also calculate the effect size and explain it. Finally, answer your research question clearly.
mydata <- read.table("./mba_decision_dataset_500.csv",
header=TRUE,
sep=",")
head(mydata)
## Person.ID Age Gender Undergraduate.Major Undergraduate.GPA Years.of.Work.Experience
## 1 1 27 Male Arts 3.18 8
## 2 2 24 Male Arts 3.03 4
## 3 3 33 Female Business 3.66 9
## 4 4 31 Male Engineering 2.46 1
## 5 5 28 Female Business 2.75 9
## 6 6 33 Male Business 3.58 3
## Current.Job.Title Annual.Salary..Before.MBA. Has.Management.Experience GRE.GMAT.Score
## 1 Entrepreneur 90624 No 688
## 2 Analyst 53576 Yes 791
## 3 Engineer 79796 No 430
## 4 Manager 105956 No 356
## 5 Entrepreneur 96132 No 472
## 6 Manager 101925 No 409
## Undergrad.University.Ranking Entrepreneurial.Interest Networking.Importance MBA.Funding.Source
## 1 185 7.9 7.6 Loan
## 2 405 3.8 4.1 Loan
## 3 107 6.7 5.5 Scholarship
## 4 257 1.0 5.3 Loan
## 5 338 9.5 4.9 Loan
## 6 280 3.4 7.1 Scholarship
## Desired.Post.MBA.Role Expected.Post.MBA.Salary Location.Preference..Post.MBA. Reason.for.MBA
## 1 Finance Manager 156165 International Entrepreneurship
## 2 Startup Founder 165612 International Career Growth
## 3 Consultant 122248 Domestic Skill Enhancement
## 4 Consultant 123797 International Entrepreneurship
## 5 Consultant 197509 Domestic Skill Enhancement
## 6 Marketing Director 99591 International Networking
## Online.vs..On.Campus.MBA Decided.to.Pursue.MBA.
## 1 On-Campus Yes
## 2 Online No
## 3 Online No
## 4 On-Campus No
## 5 Online Yes
## 6 On-Campus No
Description: - Person ID – Unique identifier - Age – Age at the time of decision - Gender – Male, Female, Other - Undergraduate Major – Engineering, Business, Arts, Science, etc. - Undergraduate GPA – Scale from 0 to 4 - Years of Work Experience – Years before MBA decision - Current Job Title – Analyst, Manager, Consultant, etc. - Annual Salary (Before MBA) – In USD - Has Management Experience – Yes/No - GRE/GMAT Score – Standardized test score - Undergrad University Ranking – Ranking of Bachelor’s institution - Entrepreneurial Interest – Scale from 1 to 10 - Networking Importance – Scale from 1 to 10 - MBA Funding Source – Self-funded, Loan, Scholarship, Employer Desired Post-MBA Role – Consultant, Executive, Startup Founder, etc. Expected Post-MBA Salary – Expected salary after MBA Location Preference (Post-MBA) – Domestic, International Reason for MBA – Career Growth, Skill Enhancement, Entrepreneurship, etc. Online vs. On-Campus MBA – Preference for learning mode Decided to Pursue MBA? – Yes/No (Target Variable)
Research question: The imported dataset recorded the Expected post MBA Salaries for all students. Can I conclude, that the expected salaries are the same, in other words that the gender of the student does not affect their expected post MBA salaries?