Using the “JMSB Student Life” data set posted on Moodle, test the following three hypotheses

by performing statistical analyses of the data using JASP.

1. There is a gender difference in the amount of time spent studying.

2. A student’s major is related to his or her academic performance (GPA).

3. Another bivariate hypothesis of your choice that uses the t-test or ANOVA.


Descriptive Statistics

Descriptive Statistics
Valid 163 162 163 159 162 162 
Missing 0 1 0 4 1 1 
Mean 1.503 14.068 2.975 3.004 22.944 1.395 
Std. Deviation 0.502 9.818 1.614 0.439 2.751 0.644 
Minimum 1.000 0.000 1.000 0.840 20.000 1.000 
Maximum 2.000 50.000 6.000 4.000 45.000 3.000 

Frequency Tables

Frequencies for GENDER
GENDERFrequencyPercentValid PercentCumulative Percent
Male 81 49.693 49.693 49.693 
Female 82 50.307 50.307 100.000 
Missing 0 0.000     
Total 163 100.000     
Frequencies for MAJOR
MAJORFrequencyPercentValid PercentCumulative Percent
Accounting 34 20.859 20.859 20.859 
Finance 36 22.086 22.086 42.945 
Management/HRM 47 28.834 28.834 71.779 
International Business 13 7.975 7.975 79.755 
Marketing 12 7.362 7.362 87.117 
Other 21 12.883 12.883 100.000 
Missing 0 0.000     
Total 163 100.000     
Frequencies for SKP_CLS
SKP_CLSFrequencyPercentValid PercentCumulative Percent
Never 112 68.712 69.136 69.136 
Rarely 36 22.086 22.222 91.358 
Occasionally 14 8.589 8.642 100.000 
Missing 1 0.613     
Total 163 100.000     
  • For 1st hypothesis: There is a gender difference in the amount of time spent studying. (t-test on jasp)

Nominal Variable (with two levels) = Gender

Interval/Ratio = amount of time spent studying

Independent Samples T-Test

Independent Samples T-Test
STDY_HRS -1.404 160 0.162 
Note.  Student’s t-test.


Group Descriptives
STDY_HRS Male 80 12.975 9.400 1.051 
  Female 82 15.134 10.153 1.121 
  • For 2nd hypothesis: A student’s major is related to his or her academic performance (GPA). (ANOVA test on jasp)

Nominal Variable (with 6 levels) = student major

Internal/Ratio = GPA


CasesSum of SquaresdfMean SquareFp
MAJOR 2.098 5 0.420 2.265 0.051 
Residuals 28.340 153 0.185     
Note.  Type III Sum of Squares


Descriptives – GPA
Accounting 3.060 0.372 34 
Finance 3.099 0.440 35 
International Business 2.705 0.293 13 
Management/HRM 3.009 0.502 47 
Marketing 3.121 0.241 10 
Other 2.867 0.461 20 
  • For 3rd hypothesis: A student’s age is related to how often he or she skip class. (ANOVA test on JASP)

Nominal variable (with 3 levels) = how often he or she skip class

Interval/Ratio = Age


CasesSum of SquaresdfMean SquareFp
SKP_CLS 6.727 2 3.364 0.439 0.646 
Residuals 1211.770 158 7.669     
Note.  Type III Sum of Squares


Descriptives – AGE
Never 23.000 2.926 111 
Occasionally 23.357 2.437 14 
Rarely 22.611 2.346 36 
  1. Provides brief theoretical explanations of why each hypothesis might be predicted. Please use your experience and creativity to come up with your best possible explanations.
  1. There is a gender difference in the amount of time spent studying.

Female students tend to spend more time on studying than male students. As to the mass of the day, the degree of dispersion of the distribution of male intelligence is greater than that of females, that is, there are more clever and stupid males than females, and there are more females with moderate intelligence than males. And people with either extraordinary intelligence or mental retardation won’t spend much time in library. Besides, due to gender differences, girls are quieter and better-behaved than boys. In this case, girls can learn relatively more “quietly” according to the requirements of study guidelines, which is the same as our traditional external performance of “diligence”.

  • A student’s major is related to his or her academic performance (GPA).

Students who major in International business seem to have obviously lower GPA than students in Marketing, Accounting, Management or Finance. In JMSB, International business is often regarded as a less popular major compared with Accounting or Finance. And similar phenomena can easily be found in a lot of business schools. The reason can be traced back to the recruitment demand of the whole society. We all agree that there are less job vacancies in the area of international trade than accounting or finance. In this way, more outstanding high school graduates have higher interests in majors other than international business.

  • Another bivariate hypothesis of your choice that uses the t-test or ANOVA.skip classes

The number of students around 23 years old who never skip classes is more than twice large of who rarely or occasionally skip classes. First of all, university tuition is expensive. Secondly, students around the age of 23 have learned to arrange their time wisely, so that they seldom face time conflicts due to lectures. In addition, attendance checks can happen through many methods, in-class paper, for example, is often applied to take students’ attendance. Further, the knowledge points in class will be tested in exams. No one would take the risk of missing key points which might appear in exams to win only extra 2 hours.

b. Describes your findings in proper form, presenting the statistical support for your conclusions.

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