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Riley, Machovec, and Kovatch - Phase 2 Optimism of Future Spring of 2019
Generated Mar 14, 2019 by rmachovec673

Phase Two-  Flagler College Students and Optimism about the Future

Riley, Machovec, and Kovatch

Introduction: In phase one of our project we presented data from the spring of 2019 survey over optimism of our future. This survey was taken by 150 statistics students in Dr. Carrie Grant’s classes. These students represent Flagler College as a whole. In phase two we will be comparing self-employed with the non self-employed. Remember this is IF the student wants to be self employed when they grow up. The two groups will be compared with age students wish to retire, whether or not they approve of trump, and gender.

Result 1:



Students were asked if they dreamed of becoming self-employed one day. These are the two categories wwe will be using to compare. The first comparison will be the age students wish to retire vs self and non-self employed. The second comparison will consist of whether the student approves of President Trump vs self and non-self employed. The third comparison will tell us if the gender of the students has nothing to do with whether or not that want to be self-employed.

Comparison #1: Age to Retire

The presented stacked boxplot and it’s summary statistics show the comparison of the age of retirement and self-employment. There were no outliers or extreme statistics that needed to be removed.

The data does not seem to be too uneven. They are close numbers and do not stray away from each other. The students who desired to be self employed seem to want to retire a little bit earlier than the not self-employed. The median is ~60  for the want to be self employed while the median is ~ 65 for the students who do not desire to be self- employed. The IQR for the self- employed students (10) does stretch out further than the non self-employed students (8). The minimums do turn out to be equal exactly at 45 years for both employments. The both max out at 80 which seems reasonable due to no one really finally decides to retire at age 80. This concludes there is no big difference in students age of retirement compared to self and not self- employed.

Result 2: Boxplot- of Age to Retire Between Self- EMployed and Not Self- Employed


Result 3: Summary Statistics- Age to Retire Between Self- EMployed and Not Self- Employed


Comparison #2: Approval of Trump

This data compares the approval of Trump to whether a students wants to be self- employed or not self-employed. The statistics comes out to be very close with percents being nearly equal. Of the students who do not wish to be self employed 64.5% do not approve of Trump and 35.5 % do approve of him. Of the students that do wish to be self-employed 65.9% do not approve of Trump while only 34.1% do approve of him. This data proves that there is no correlation with the approval of Trump compared to self- employment.

Result 4: Bar-Plot Not Self- employed and Self- employed vs Approval of Trump


Comparison #3: Gender

The third and final comparison deal is shown with a contingency table. This table shows whether or not gender has anything to do with whether or not a student wants to be self- employed. ~75% of the students who did not want to be self employed were female; however, ~63% of people who did want to be self-employed were females as well.

Result 5: Contingency Table Gender vs Self and Not Self- Employed


Conclusion: In conclusion with all three comparisons there seemed to be no correlation. Retirement age vs self employment seemed to not be a big difference. Students who wanted to be self- employed seemed to want to retire a little earlier than people who did not want to be self- employed. The approval of trump and self employment comparison was almost equal. The data turned out that most students of either non self-employment and self- employment both agreed on the disapproval of Trump. The contingency table provided data that mostly females wanted to be self-employed however mostly females also wanted to not be self employed. This happened due to the fact there were more females participating in the survey. When calculating percentages males would even out to about the same percentage even though having less if you did the calculation P(a) +P(b)- P(ab) / total.

Result 1: 1st one on phase two   [Info]
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Result 2: Boxplot of Age to Retire Between Self-Employed and Not-Self EMployed   [Info]
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Result 3: Summary Stats for Boxplot age to reitre between self employed and not self employed   [Info]

Summary statistics for Sample(Age to Retire):

Group by: Sample(Self-Employed)

Result 4: Bar Plot With Data Not self employed and self employed vs approval of trump   [Info]
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Result 5: Contingency table (with data) rachel   [Info]

Contingency table results:

Rows: Sample(Self-Employed)
Columns: Sample(Gender)

Chi-Square test: