EDUCATION VS UNEMPLOYMENT AND EMPLOYMENT RATES

SERENE WONG

PERIOD 2

ELLIOTJUNE0809

OVERVIEW• THESIS• HYPOTHESIS

– ONE VARIABLE PREDICTION & TWO VARIABLE PREDICTION

• BACKGROUND INFORMATION• DATA STAGE / COLLECTION• ONE VARIABLE ANALYSIS

– INDEPENDENT & DEPENDENT VARIABLE

• TWO VARIABLE ANALYSIS– LIMITATIONS & CAUSE/EFFECT

• CONCLUSION• FURTHER RESEARCH QUESTIONS• REFERENCES

THESIS

What is the relationship between the level of education achieved by individuals, versus

their employment status whether it be unemployed or employed?

HYPOTHESIS: GENERAL

• The level of education a person achieves will most likely affect their employment status. The higher the level of education achieved, the higher the chance that the individual is employed.

HYPOTHESIS: ONE VARIABLE PREDICTION

• MEAN: represent the average Canadian• MODE: a good representation of the educational

level completed by the average person• MEDIAN: a good representation of the

educational level completed by the average person

• SEMI-INTERQUARTILE TO INTERQUARTILE RANGE: display results to support the fact that the average citizen has the educational level equivalent to the one found through the mean, median and mode.

HYPOTHESIS: TWO VARIABLE PREDICTION

• LINEAR REGRESSION: best representation – The relationship between unemployment rate

and level of education should be a strong one and negative.

– The relationship between education level and level of employment should be a strong positive correlation.

BACKGROUND INFORMATION

• The study emphasizes the importance of education – to finish high school and attend post-secondary education

• Benefits students to determine the likelihood of employment based on education

• I wanted to know if gettinga higher education is worth the effort

DATA STAGE

• Employment rates, Unemployment rates and Highest Certification of Education data need to be collected

• Organized into a chart• Statistics Canada conducted a nationwide

census– Geography: Canada, including both females and

males, and the labour force– Census gave accurate picture of the employment

situation in Canada

DATA COLLECTIONEDUCATION LEVEL UNEMPLOYMENT RATE EMPLOYMENT RATE

1 No certificate, diploma or degree 11.1 % 38.1 %

2 High school certificate or equivalent 7.3 % 63.8 %

3 Apprenticeship or trades certificate or diploma

6.2 % 68.1 %

4 College, CEGEP or other non-university certificate or diploma

5.0 % 74.2 %

5 University certificate or diploma below bachelor level

5.2 % 67.1 %

6 Bachelor’s degree 4.7 % 77.2 %

7 University certificate or diploma above bachelor level

4.2 % 73.6 %

8 Degree in medicine, dentistry, veterinary medicine or optometry

2.6 % 78.9 %

9 Master’s degree 4.5 % 76.2 %

10 Earned doctorate 3.6 % 75.3 %

DATA COLLECTION

• Levels of degrees were given a certain weighting. – A weighting of 10: the highest and hardest degree

that one could achieve, and less common. – A weighting of 1 would indicate that the level of

education completed was low, such as no certificate, diploma or degree.

• The rate of Unemployment and Employment is calculated as a percentage.

ONE VARIABLE ANALYSIS INDEPENDENT VARIABLE

LEVEL OF EDUCATION ACHIEVEDMEAN 5.5 %

MEDIAN 5.5 %

MODE N/A

RANGE 9 %

MINIMUM 1 %

MAXIMUM 10 %

STANDARD DEVIATION 2.872

VARIANCE 8.25

Z – SCORES 0.54

Q1 3 %

Q3 8 %

IQR 5 %

SIQR 2.5 %

OUTLIER CALCULATIONS

Q1 – 1.5(IQR) = -4.5Outliers < -4.5

Q3 + 1.5 (IQR) = 15.5Outliers > 15.5

There are no Outliers

DATA: a ranking from 1-10 based on level of education

ONE VARIABLE ANALYSIS INDEPENDENT VARIABLELEVEL OF EDUCATION ACHIEVED

• MEAN & MEDIAN = 5.5– This indicates that the average level of education

achieved and the normal person in a population would achieve an education level of 5.5, which is between a University Certificate or Diploma below Bachelor’s Degree, and a Bachelor’s Degree.

• Since data values for education is simply a ranking, outliers and measures of central tendencies are irrelevant

ONE VARIABLE ANALYSIS DEPENDENT VARIABLE : UNEMPLOYMENT

MEAN 5.44 %

MEDIAN 5.1 %

MODE N/A

RANGE 8.5 %

MINIMUM 2.6 %

MAXIMUM 11.1 %

STANDARD DEVIATION 2.25

VARIANCE 5074

Z – SCORES 0.898

Q1 4.2 %

Q3 6.2 %

IQR 2 %

SIQR 1%

OUTLIER CALCULATIONS

Q1 – 1.5(IQR) = 2.7 %Outliers < 2.7

Q3 + 1.5 (IQR) = 7.7 %Outliers > 7.7 %

2.6 % and 11.1 % areoutliers

MEAN = 5.44%. This means that the average unemployment in Canada is 5.44%. However, the average unemployment rate in Canada is 6.0% in 2007. But in 2008, the unemployment rate rose to 8.0%, possibly due to the oncoming recession at that time. Therefore, the mean rate that is calculated from the set of data is actually lower than the statistical unemployment rate and is not actually that high.

Level of Education vs Unemployment Rate

11.1

7.3

6.2

5 5.24.7

4.2

2.6

4.5

3.6

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Level of Education Achieved (Ranking)

Un

em

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t R

ate

(%

)

ONE VARIABLE ANALYSIS DEPENDENT VARIABLE : UNEMPLOYMENT

• as the Level of Education Achieved increases, the levels of unemployment decrease. – Logical, as people

with certain skill sets, specializations and level of training or education are more likely to be hired.

ONE VARIABLE ANALYSIS DEPENDENT VARIABLE : EMPLOYMENT

MEAN 69.25 %

MEDIAN 74.75 %

MODE N/A

RANGE 40.8 %

MINIMUM 38.1 %

MAXIMUM 78.9 %

STANDARD DEVIATION 11.36 %

VARIANCE 129.05 %

Z – SCORES -0.459

Q1 4.2 %

Q3 6.2 %

IQR 2 %

SIQR 1%

OUTLIER CALCULATIONS Q1 – 1.5(IQR) = 53.45 %Outliers < 53.45 %

Q3 + 1.5 (IQR) = 89.95 %Outliers > 89.95 %38.1 % is an outlier

Canada’s statistical employment rate is 63.6% as of 2008. The calculated mean in this case study is 69.25%, which indicates that the theoretical employment rate is higher than it actually is.

TWO VARIABLE ANALYSIS UNEMPLOYMENT

Unemployment Rate Versus Level Of Education

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Level of Education

Rate

of U

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REGRESSION TYPE r2 Equation

Linear 0.6965 y = - 0.6545x + 9.04

Quadratic 0.8879 y = 0.1356x2 - 2.1462x + 12.023

Cubic 0.9204 y = - 0.0231x3 + 0.517x2 - 3.9053x + 14.007

Exponential 0.7364 y = 9.3596e-0.1121x

• The correlation for the Rate of Unemployment was 0.8346 which is strong and negatively sloped as the r value was near 1 and the linear regression sloped downwards.

Unemployment Rate Versus Level Of Education

R2 = 0.6965r = 0.8346

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TWO VARIABLE ANALYSIS EMPLOYMENT

REGRESSION TYPE r2 Equation

Linear 0.5498 y = 2.9327x + 53.12

Quadratic 0.8018 y = - 0.7848x2 + 11.566x + 35.853

Cubic 0.8763 y = 0.1764x3 - 3.6957x2 + 24.991x + 20.717

Exponential 0.4938 y = 51.706e0.0499x

Employment Rate Versus Level of Education

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Employment Rate Versus Level of Education

R2 = 0.5498r = 0.7415

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• The correlation for the Rate of Employment was 0.7415 which was strong and positive because the value was close to 1 and the linear regression sloped upwards.

LIMITATIONS / CAUSE & EFFECTS

• CAUSE AND EFFECT RELATIONSHIP: as the Level of Education increases, the Employment Rate increases, and the Unemployment Rate decreases.

• Obvious: higher education, more likely to be hired because you have more skills and knowledge

• Discrepancy at ‘level 8’ (Degree in Medicine, Dentistry, Veterinary Medicine or Optometry), Unemployment Rate is 2.6% andEmployment peaks at 78.9%

73.678.9

76.2 75.3

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1 2 3 4 5 6 7 8 9 10

4.2

2.6

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Level of Education Achieved (Ranking)

unemployment

employment

LIMITATIONS / CAUSE & EFFECTS

• Employment and Unemployment rates do not add up to 100%– Due to hidden unemployment, lies about employment status,

non-registered businesses, out of work due to injury & compensation (e.g. WSIB), frictional unemployment etc.

– Also, people: in between jobs,• just immigrated to Canada and are looking

for jobs• who want to have a job but have given up

looking for one

LIMITATIONS / CAUSE & EFFECTS

• Interpolating and extrapolating does not make sense– No level of education that is ‘in between’

another. For example, a Bachelor and half a degree does not exist.

EXTRANEOUS VARIABLES

• Census– Includes the more unfortunate communities– Can hugely influence and skewer statistics – Immigrants– Native Americans on Reserve have different

education and employment– Respondents may not be completely honest,

or unavailable (e.g., away for travel at time of census)

CONCLUSION

• As the level of education achieved increases, the rate of unemployment decreases.

• As the level of education increases, the rate of employment increases as well.

• Backed by evidence of linear regression of a cubic relation.

• Results are similar to hypothesis. However, in the hypothesis, it was predicted that the relationship would be linear, but instead, is a cubic function.

CONCLUSION

• Relationship between Unemployment rate and Employment rate:– Regression are opposite of each other. As one tends

to increase, the other tends to decrease.Unemployment Rate Versus Level Of Education

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Employment Rate Versus Level of Education

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FUTURE RESEARCH QUESTIONS

• Does the age of individuals affect the levels of employment and unemployment?

• Will the total percentage of employment and unemployment every equal 1, where there is none unaccounted for?

• What can be done to maximize employment and minimize unemployment?

• Also, what can be done to encourage education, especially the completion of a High School Diploma?

REFERENCES• DATA COLLECTION SOURCE: Statistics Canada. 2008. Labour

Force Activity (8), Highest Certificate, Diploma or Degree (13), Attendance at School (3), Age Groups (12A) and Sex (3) for the Population 15 Years and Over of Canada, Provinces, Territories, Census Divisions and Census Subdivisions, 2006 Census - 20% Sample Data (table). Topic-based tabulation. 2006 Census of Population.Statistics Canada catalogue no. 97-559-XCB2006028. Ottawa. Released October 28, 2008.<http://www12.statcan.gc.ca/english/census06/data/topics/Print.cfm?PID=97691&GID=771240&D1=0&D2=0&D3=0&D4=0&D5=0&D6=0 (accessed December 14, 2008).>