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Post-Secondary Education and Earnings

Post-Secondary Education and Earnings. Over the past 25 years, technological advancement has increased the need for highly educated workers. Women saw their employment rates increase as more of them moved into the labour market.

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Post-Secondary Education and Earnings

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  1. Post-Secondary Education and Earnings

  2. Over the past 25 years, technological advancement has increased the need for highly educated workers. Women saw their employment rates increase as more of them moved into the labour market. However, for men, rates have decreased. This decline is visible due to their lower levels of education. Education in the Past

  3. From the years 1996-2005, has the enrolments in to undergraduate and graduate programs been a steady increase? Who is enrolling at a greater pace, males or females? I predict that there will be a steady increase in enrolments for under- and graduate degrees. I also predict that females are enrolling at a greater pace than males. Question? Hypothesis

  4. MEAN Undergrad: Male: 286,529 Female: 395,275 Graduate: Male: 61,583 Female: 62,026 MEDIAN Undergrad: Male: 276,461 Female: 379,634 Graduate: Male: 58,250 Female: 59,297 MODE Undergrad: Male: none Female: none Graduate: Male: none Female: none One can see that the mean number of females entering undergraduate programs is substantially higher than the mean number of males enrolling in undergraduate programs. Central Tendency

  5. Females: • y = 1943.8x2 - 8E+06x + 8E+09 • r2 = 0.9827 Males: • y = 1478.1x2 - 6E+06x + 6E+09 • r2 = 0.9794

  6. MINIMUM Male: 268,734 Female: 362,874 MAXIMUM Male: 325,374 Female: 460,284 RANGE Male: 56,640 Female: 97,410 As shown above, one can see that the minimum and maximum number of undergraduate enrolments of males are substantially lower than that of females. Undergrad Enrolments

  7. Q1: Male: 277525 Female: 375008.5 Q2: Male: 276,461 Female: 379,634 Q3: Male: 300917 Female: 419959 Inter-quartile Range: Male: 23392 Female: 44950.5 Box and Whisker Plot Undergrad Enrolments: Measures of Spread

  8. Male= L1 Female= L2 Z-score: Male Z-score: Female Minimum: -0.871 Minimum: -0.882 Maximum: 1.902 Maximum: 1.771 Undergrad Enrolments: Measures of Spread

  9. Males: • y = -3.8346x5 + 38339x4 - 2E+08x3 + 3E+11x2 - 3E+14x + 1E+17 • r2 = 0.9972 Females: • y = 293.33x2 - 1E+06x + 1E+09 • r2 = 0.9946

  10. Male=L3 Female=L4 RANGE Male: 15,861 Female: 22,035 - As illustrated above, one can see that overall, more females are enrolled in graduate programs. It can also be seen that the minimum number of male enrolments is higher than the number for females. By contrast, the maximum number of graduate enrolments for males is much lower than the number for females. This difference proves that on average, more females are enrolled in graduate programs. Graduate Enrolments

  11. Q1: Male: 58275.75 Female: 56759.25 Q2: Male: 58,250 Female: 59,297 Q3: Male: 65354.5 Female: 67,777 Inter-quartile Range Male: 7078.75 Female: 11017.75 Box and Whisker Plot Graduate Enrolments: Measures of Spread

  12. Standard Deviation Male: 5983.846 Female: 7785.44 Variance Male: 35,806,414 Female: 60,613,079.6 Z-score: Male Minimum: -0.833 Maximum: 1.818 Z-score: Female Minimum: -1.002 Maximum: 1.828 Graduate Enrolments: Measures of Spread

  13. My hypothesis was PARTIALLY correct. The graphs proved that there is an increase in the number of enrolments to university, but the increase has not been steady. Between 1997 and 2000 the numbers of female and male enrolments dipped, but steadily increased after 2001. My hypothesis was correct in predicting that females are enrolling in university programs at a greater rate than males. The mean for females is higher for both undergraduate and graduate enrolments. Was my hypothesis correct? Conclusion

  14. As more students are enrolled in university programs, have college and trade enrolments declined? Who has a higher enrolment rate into these programs, males or females? Question? Hypothesis I predict that the number of students enrolled in college and trade programs throughout the years has not been declining, but remaining steady. Also, I predict that males have a higher enrolment rate than females.

  15. Central Tendency MEAN College: Male: 1,187 Female: 1,235 Trade:Male: 23.5 Female: 121 MEDIAN College: Male: 1,175 Female: 1,226 Trade:Male: 22.5Female: 127.5 MODE College: Male: none Female: none Trade:Male: noneFemale: none Based on the central tendencies provided above, one can see that the mean and median for female enrolments are higher than the mean and median for male enrolments, proving that more females are enrolled in college and trade programs.

  16. Males: • y = -0.434x6 + 5208x5 - 3E+07x4 + 7E+10x3 - 1E+14x2 + 8E+16x - 3E+19 • r2 = 0.7823 Females: • y = -0.5321x6 + 6385.8x5 - 3E+07x4 + 9E+10x3 - 1E+14x2 + 1E+17x - 3E+19 • r2 = 0.9641

  17. MINIMUM Male: 945 Female: 1,005 MAXIMUM Male: 1,536 Female: 1,644 RANGE Male: 591 Female: 639 One can see that the minimum and maximum for the number of college enrolments is higher for females than for males. This proves that more females are enrolled in college programs. College Enrolments

  18. Q1: Male: 1151.3 Female: 1253.25 Q2: Male: 1175 Female: 1226 Q3: Male: 1059.8 Female: 1322.25 Inter-quartile Range Male: -91.5 Female: 69 Box and Whisker Plot College Enrolments: Measures of Spread

  19. Male=L1 Female=L2 Z-score: Male Z-score: Female Minimum: -1.543 Minimum: 2.229 Maximum: -1.201 Maximum: 2.139 College Enrolments: Measures of Spread

  20. Females: y = 5.25x5 - 52571x4 + 2E+08x3 – 4E+11x2 + 4E+14x - 2E+17 r2 = 1 Males: y = 2.05x5 - 20527x4 + 8E+07x3 - 2E+11x2 + 2E+14x - 7E+16 r2 = 1

  21. MINIMUM Male: 9 Female: 78 MAXIMUM Male: 42 Female: 159 RANGE Male: 33 Female: 81 Based on the data above, it can be seen that more women are entering the trades because the minimum and maximum values are higher. Trade/Vocational and Preparatory Training

  22. Q1: Male: 24.75 Female: 122.25 Q2: Male: 22.5 Female: 127.5 Q3: Male: 20.25 Female: 107.25 Inter-quartile Range Male: -4.5 Female: -15 Box and Whisker Plot Trade Enrolments: Measures of Spread

  23. Male=L1 Female=L2 Z-score (2005) Males: -0.501 Females: -1.0317 Trade Enrolments: Measures of Spread

  24. My hypothesis was NOT correct. I predicted that more males would be enrolled in college and trade programs and that the enrolment rate of males and females would be steady. The graphs prove that females are enrolled in college and trade programs in greater numbers than males. The data also proved that the enrolment rates fluctuated greatly each year from 1996 to 2005. There were also many outliers in the data, which also proved that my prediction was incorrect. Conclusion: Was my hypothesis correct?

  25. If females are enrolled in university, college and trade programs in higher numbers than males, which sex earned the greatest amount of money between 1996 and 2005? Question? Hypothesis I predict that males made more money between 1996 and 2005 because it will take more time to see the economic effects of more women enrolling in post-secondary school or trade programs because each program takes a specific number of years to complete.

  26. Central Tendency MEAN Males: 53,590 Females: 37,620 MEDIAN Males: 53,850 Females: 38,000 MODE Males: none Females: 38000 Based on the central tendencies listed above, it can be seen that on average, males earn more money than females.

  27. Males: Females: y = -6.5268x4 + 52247x3 – y = -0.2768x4 + 2220.7x3 - 2E+08x2 + 2E+11x - 1E+14 7E+06x2 + 9E+09x - 4E+12 r2 = 0.9616 r2 = 0.8073

  28. Male=L1 Female=L2 RANGE Males: 6,900 Females: 3,900 The minimum and maximum values are higher for males than for females. This data proves that between the year 1996 and 2005, males have made more money. Earnings

  29. Earnings: Measures of Spread Q1: Male: 51625 Female: 36700 Q2: Male: 53850 Female: 38000 Q3: Male: 54775 Female: 38650 Inter-quartile Range Male: 3150 Female: 1950 Standard Deviation Male: 1980.152 Female: 1228.82 Variance Male: 3,921,000 Female: 1,510,000 Z-score: MaleZ-score: Female Minimum: -2.12 Minimum: -1.98 Maximum:1 Maximum: 1.19

  30. My hypothesis WAS correct. I predicted that since females have enrolled in post-secondary and trade programs more than males between 1996 and 2005, it will take a few more years before the data will show a rise in female wages. Currently on average, males earn more money than females. Conclusion: Was my hypothesis correct?

  31. Which graduate will make the most money in the future? A college, university or only high school graduate? Question? Hypothesis I predict that those who have graduated from high school will earn the most money because most often these graduates work in the skilled trade careers, which are generally well paid.

  32. Correlation Coefficients University Degree y = 0.0069x6 - 83.108x5 + 415659x4 - 1E+09x3 + 2E+12x2 - 1E+15x + 4E+17 r2 = 0.872 r = 0.934 College Certificate or Diploma y = -0.0004x6 + 4.4216x5 - 22132x4 + 6E+07x3 - 9E+10x2 + 7E+13x - 2E+16 r2 = 0.3828 r = 0.619 Graduated High School y = 0.0003x6 - 4.0881x5 + 20465x4 - 5E+07x3 + 8E+10x2 - 7E+13x + 2E+16 r2 = 0.5561 r = 0.746

  33. My hypothesis WAS correct. I predicted that those who graduated from trade preparatory programs would earn the most money. The correlation coefficients indicate that a university degree and earnings have a strong polynomial correlation, however, there is a large outlier in the data. On average, the earnings for trade employees are higher than the earnings for university and college graduates. Conclusion: Was my Hypothesis Correct?

  34. Post-secondary Education and Earnings By: Amanda Bettencourt

  35. Works Cited CANSIM Table 477-0013. “University Enrolments, by registration status, program level, Classification of Instructional Programs, Primary Grouping, and sex, annual.” StatisticsCanada: E-STAT. July 2007. http://estat.statcan.ca/cgi-win/CNSMCGI.EXE?regtkt=&C2Sub=&ARRAYID=4770013&C2DB=EST&VEC=&HILITE=ENROLMENTS&LANG=E&SrchVer=&ChunkSize=50&SDDSLOC=%2F%2Fwww.statcan.ca%2Fenglish%2Fsdds%2F*.htm&ROOTDIR=ESTAT/&RESULTTEMPLATE=ESTAT/CII_PICK&ARRAY_PICK=1&SDDSID=&SDDSDESC= CANSIM Table 202-0104. “Female-to-male earnings ratios, by selected characteristics, annual.” StatisticsCanada: E-STAT. July 2007. http://estat.statcan.ca/cgi-win/CNSMCGI.EXE

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