Throughout this presentation you will learn about… If men are hired over woman, and if there is a justified reason for this behaviour. What is the effect.
Jan 11, 2016
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Throughout this presentation you will learn about… Throughout this presentation you will learn about…
If men are hired over woman, and if there is a justified If men are hired over woman, and if there is a justified reason for this behaviour. reason for this behaviour.
• What is the effect of women entering the workforce? What is the effect of women entering the workforce?
• Is the divorce rate related to thisIs the divorce rate related to this
• Have the children have been effected from women Have the children have been effected from women entering the workforce? entering the workforce?
• Are men paid more than woman? Are men paid more than woman?
Are these feminists claims correct?Are these feminists claims correct?LETS FIND OUT!!!!!LETS FIND OUT!!!!!
Throughout this presentation you will learn about… Throughout this presentation you will learn about…
If men are hired over woman, and if there is a justified If men are hired over woman, and if there is a justified reason for this behaviour. reason for this behaviour.
• What is the effect of women entering the workforce? What is the effect of women entering the workforce?
• Is the divorce rate related to thisIs the divorce rate related to this
• Have the children have been effected from women Have the children have been effected from women entering the workforce? entering the workforce?
• Are men paid more than woman? Are men paid more than woman?
Are these feminists claims correct?Are these feminists claims correct?LETS FIND OUT!!!!!LETS FIND OUT!!!!!
I predict that a man does have an I predict that a man does have an advantage over women in the advantage over women in the
workplace. I also assume that the workplace. I also assume that the opportunity is not equal; a male is opportunity is not equal; a male is
hired over a female and is paid more hired over a female and is paid more for the same job.for the same job.
I predict that a man does have an I predict that a man does have an advantage over women in the advantage over women in the
workplace. I also assume that the workplace. I also assume that the opportunity is not equal; a male is opportunity is not equal; a male is
hired over a female and is paid more hired over a female and is paid more for the same job.for the same job.
1.1. Decided on an area of study.Decided on an area of study.
2.2. Produced an educated hypothesis.Produced an educated hypothesis.
3.3. Researched from a variety of sources: Researched from a variety of sources: Internet, Magazine and Newspaper Internet, Magazine and Newspaper Articles, and previous reports.Articles, and previous reports.
4.4. Organized data in a logical sequence.Organized data in a logical sequence.
5.5. Inputted all tables and charts into excel.Inputted all tables and charts into excel.
6.6. Performed mathematical functions from Performed mathematical functions from desired chapters to help obtain an desired chapters to help obtain an answer to my hypothesis.answer to my hypothesis.
7.7. Sought out all possible biases in Sought out all possible biases in research.research.
8.8. Review all results to obtain a summary Review all results to obtain a summary and conclusion to my hypothesis.and conclusion to my hypothesis.
1.1. Decided on an area of study.Decided on an area of study.
2.2. Produced an educated hypothesis.Produced an educated hypothesis.
3.3. Researched from a variety of sources: Researched from a variety of sources: Internet, Magazine and Newspaper Internet, Magazine and Newspaper Articles, and previous reports.Articles, and previous reports.
4.4. Organized data in a logical sequence.Organized data in a logical sequence.
5.5. Inputted all tables and charts into excel.Inputted all tables and charts into excel.
6.6. Performed mathematical functions from Performed mathematical functions from desired chapters to help obtain an desired chapters to help obtain an answer to my hypothesis.answer to my hypothesis.
7.7. Sought out all possible biases in Sought out all possible biases in research.research.
8.8. Review all results to obtain a summary Review all results to obtain a summary and conclusion to my hypothesis.and conclusion to my hypothesis.
Convenience Sample:
I selected a small sample group accessible to me; although this survey was limited it produced some
interesting results.
Survey Question:
If you had ultimately had the choice to hire either male or female, what would be your preference, if
any?
Sample 1: Mrs. Richards, Principle of St. Joseph Secondary SchoolSample 1: Mrs. Richards, Principle of St. Joseph Secondary School
““The sex of the potential employee does not affect who I hire, instead I The sex of the potential employee does not affect who I hire, instead I hire based on other credentials such as education, and experience”hire based on other credentials such as education, and experience”
Sample 2: Domenic Maccarone, Sales Manager of Lunbeck CanadaSample 2: Domenic Maccarone, Sales Manager of Lunbeck Canada
““If I ultimately had to choose, with all other credentials being equal, I If I ultimately had to choose, with all other credentials being equal, I would choose the male. The reason for this choice is maternity leave; it would choose the male. The reason for this choice is maternity leave; it does affect the business when the woman leaves for this purpose. does affect the business when the woman leaves for this purpose. However it has not come to these circumstances yet, I’ve always hired However it has not come to these circumstances yet, I’ve always hired people based on other characteristics.”people based on other characteristics.”
Sample 3: Brian Davidson, Assistant Manager of Toyota Dealership Sample 3: Brian Davidson, Assistant Manager of Toyota Dealership “Whether or not the employee is male or female does not matter, at least “Whether or not the employee is male or female does not matter, at least in this line of work. This job requires people who are good sales people in this line of work. This job requires people who are good sales people only. People are hired solely based on their test results and interview.”only. People are hired solely based on their test results and interview.”
Sample 4: Peter Withall, Sales Manager of Home Outfitters (Dundas)Sample 4: Peter Withall, Sales Manager of Home Outfitters (Dundas)
““I would hire a woman over the male with all other characteristics equal, I would hire a woman over the male with all other characteristics equal, because our main shoppers are female.”because our main shoppers are female.”
Sample 1: Mrs. Richards, Principle of St. Joseph Secondary SchoolSample 1: Mrs. Richards, Principle of St. Joseph Secondary School
““The sex of the potential employee does not affect who I hire, instead I The sex of the potential employee does not affect who I hire, instead I hire based on other credentials such as education, and experience”hire based on other credentials such as education, and experience”
Sample 2: Domenic Maccarone, Sales Manager of Lunbeck CanadaSample 2: Domenic Maccarone, Sales Manager of Lunbeck Canada
““If I ultimately had to choose, with all other credentials being equal, I If I ultimately had to choose, with all other credentials being equal, I would choose the male. The reason for this choice is maternity leave; it would choose the male. The reason for this choice is maternity leave; it does affect the business when the woman leaves for this purpose. does affect the business when the woman leaves for this purpose. However it has not come to these circumstances yet, I’ve always hired However it has not come to these circumstances yet, I’ve always hired people based on other characteristics.”people based on other characteristics.”
Sample 3: Brian Davidson, Assistant Manager of Toyota Dealership Sample 3: Brian Davidson, Assistant Manager of Toyota Dealership “Whether or not the employee is male or female does not matter, at least “Whether or not the employee is male or female does not matter, at least in this line of work. This job requires people who are good sales people in this line of work. This job requires people who are good sales people only. People are hired solely based on their test results and interview.”only. People are hired solely based on their test results and interview.”
Sample 4: Peter Withall, Sales Manager of Home Outfitters (Dundas)Sample 4: Peter Withall, Sales Manager of Home Outfitters (Dundas)
““I would hire a woman over the male with all other characteristics equal, I would hire a woman over the male with all other characteristics equal, because our main shoppers are female.”because our main shoppers are female.”
***BIAS***BIAS::This survey can contain This survey can contain response bias because the participants response bias because the participants could have given deliberately false could have given deliberately false answers because they may have been answers because they may have been afraid or embarrassed to say they afraid or embarrassed to say they prefer one sex to the other.prefer one sex to the other.
***BIAS***BIAS::This survey can contain This survey can contain response bias because the participants response bias because the participants could have given deliberately false could have given deliberately false answers because they may have been answers because they may have been afraid or embarrassed to say they afraid or embarrassed to say they prefer one sex to the other.prefer one sex to the other.
CANADA'S POPULATIONSource: Statistics Canada
SexBoth
sexesMales Females
1971 21,962,082 11,026,832 10,935,2501972 22,219,560 11,146,601 11,072,9591973 22,493,842 11,274,570 11,219,2721974 22,808,446 11,422,310 11,386,1361975 23,142,275 11,579,741 11,562,5341976 23,449,793 11,723,767 11,726,0261977 23,726,345 11,850,560 11,875,7851978 23,963,967 11,957,863 12,006,1041979 24,202,205 12,065,426 12,136,7791980 24,516,278 12,210,969 12,305,3091981 24,820,382 12,351,600 12,468,7821982 25,117,424 12,493,013 12,624,4111983 25,366,965 12,609,813 12,757,1521984 25,607,555 12,721,762 12,885,7931985 25,842,590 12,830,988 13,011,6021986 26,100,587 12,951,516 13,149,0711987 26,449,888 13,121,628 13,328,2601988 26,798,303 13,291,477 13,506,8261989 27,286,239 13,530,512 13,755,7271990 27,700,856 13,733,446 13,967,4101991 28,030,864 13,894,492 14,136,3721992 28,376,550 14,062,820 14,313,7301993 28,703,142 14,221,551 14,481,5911994 29,035,981 14,383,261 14,652,7201995 29,353,854 14,537,509 14,816,3451996 29,671,892 14,691,777 14,980,1151997 29,987,214 14,850,874 15,136,3401998 30,248,210 14,978,931 15,269,2791999 30,499,219 15,101,937 15,397,2822000 30,769,669 15,234,321 15,535,3482001 31,081,887 15,388,494 15,693,393
Canada’s Population for both males and females follows a linear regression, for male population r^2=0.9962 and for female population r^2=0.9982. As evident both male and female populations follow an almost perfect linear correlation. These values were calculated using excel.
Canada's Population
R2 = 0.9962
R2 = 0.9982
10,000,000
11,000,000
12,000,000
13,000,000
14,000,000
15,000,000
16,000,000
Year
Male
Female
Linear (Male)
Linear (Female)
LABOUR FORCE CHARACTERISTICSSource: Statistics Canada
Labour force characteristics
(Persons)Sex Males Females1976 6,145.50 3,630.701977 6,198.40 3,716.301978 6,320.50 3,891.701979 6,526.40 4,131.301980 6,630.90 4,339.301981 6,749.90 4,546.901982 6,436.20 4,510.901983 6,420.50 4,606.601984 6,553.40 4,746.701985 6,689.90 4,927.401986 6,860.10 5,118.901987 7,021.30 5,299.301988 7,178.20 5,532.101989 7,287.30 5,699.101990 7,277.80 5,806.201991 7,060.00 5,790.601992 6,970.40 5,789.601993 7,029.90 5,827.501994 7,177.50 5,934.201995 7,298.50 6,058.401996 7,346.00 6,116.601997 7,508.30 6,266.201998 7,661.40 6,479.001999 7,865.80 6,665.302000 8,049.30 6,860.402001 8,109.70 6,967.10
Employment
The gap between male employees and female employees is
decreasing with each passing year. This is proven through linear
regression: the female employment has a stronger linear regression of
r^2=0.9801, where as the male linear regression is r^2=0.8939. There may be a possibility in the
near future that the amount of female employees will equal or
surpass the amount of male employees.
This data may contain bias simply because there is more males
employed in the workplace than females. This bias will try to be taken
into account wherever possible.
Employement
R2 = 0.894
R2 = 0.981
3,000.00
4,000.00
5,000.00
6,000.00
7,000.00
8,000.00
9,000.00
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Year
Male
Female
Linear (Male)
Linear (Female)
Employment vs. Population
R2 = 0.981
3,000.00
3,500.00
4,000.00
4,500.00
5,000.00
5,500.00
6,000.00
6,500.00
7,000.00
7,500.00
Population
Em
plo
yme
nt
Employment
Linear (Employment)
Using excel, the correlation coefficient can be found by taking the square root of the linear regression (r^2), the numbers are simply too large to calculate manually.
R^2= 0.981 R= 0.9904 Thus, there is a strong relationship between the female population and employment.
DIVORCE POPULATIONSource: Statistics Canada
Sex Males Females1971 78,222 104,4861972 88,420 120,1141973 99,183 136,5011974 110,547 153,9331975 122,461 172,1481976 134,698 190,8961977 149,842 211,6381978 165,338 232,9561979 181,468 255,1071980 198,803 278,9731981 216,947 303,8211982 232,574 327,9781983 248,102 352,3001984 264,026 377,3331985 280,589 403,3231986 298,172 430,7771987 350,297 487,0401988 405,333 545,9731989 464,923 609,9751990 526,111 675,2501991 589,109 741,4481992 577,760 736,2061993 565,904 730,7051994 553,169 724,8501995 539,236 718,1671996 524,016 710,4991997 547,914 742,6711998 569,206 771,7531999 592,656 803,1182000 616,816 835,0112001 641,734 868,037
Divorced Population
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
1,000,000
Year
Male
Female
CRITICAL ANALYSIS:
Canada's current divorce law came into effect on 1 June 1986
ACTIVITY IN THE LABOUR FORCESource: Statistics Canada
Hirings and separations (Number)
Sex 1998 1999 2000 2001
Males 2,951.70 2,937.10 2,680.10 2,503.80 Females 2,586.30 2,475.00 2,432.20 2,254.80 Males 1,413.80 1,422.50 1,474.50 1,451.90 Females 1,343.50 1,372.50 1,439.00 1,378.80 Males 1,352.60 1,320.10 1,183.60 1,204.00 Females 969.2 946 835.8 857.6
Total number of hirings
Total number of quits
Total number of layoffs
Activity in the Labour Force
500.00
1,000.00
1,500.00
2,000.00
2,500.00
3,000.00
1998 1999 2000 2001
Year
Total Hirings Male
Total Hirings Female
Total Quits Male
Total Quits Female
Total Layoffs Male
Total Layoffs Female
More males are hired than females, however more males quit their jobs and are laid off,
balancing it out.
Labour force characteristics
(Persons)Educational Attainment Sex 1990 1991 1992 1993 1994 1995 1996 2000
Males 1,517.30 1,484.20 1,508.80 1,523.30 1,473.20 1,492.10 1,520.70 1,655.40
Females 1,461.70 1,459.10 1,460.20 1,457.70 1,376.20 1,363.40 1,396.20 1,496.50
Males 1,845.40 1,809.40 1,813.50 1,869.30 2,033.70 2,152.50 2,200.50 2,563.60
Females 1,591.00 1,624.20 1,651.40 1,716.80 1,834.60 1,930.10 1,998.10 2,276.20
Males 1,107.10 1,131.10 1,170.40 1,268.20 1,305.70 1,328.20 1,341.90 1,556.30
Females 778 799.4 875.2 943.3 1,022.40 1,065.20 1,085.60 1,380.80
Males 1,420.90 1,376.00 1,381.80 1,389.70 1,348.40 1,370.30 1,384.40 1,523.60
Females 1,122.70 1,082.80 1,083.10 1,056.70 1,005.30 994.8 1,010.00 1,121.20
Males 1,760.20 1,707.50 1,696.70 1,745.30 1,904.30 2,015.70 2,055.50 2,414.00
Females 1,214.80 1,228.30 1,235.70 1,272.70 1,362.80 1,436.60 1,479.90 1,728.50
Males 1,049.90 1,069.10 1,101.70 1,184.80 1,219.40 1,243.20 1,244.30 1,455.60
Females 637 646.1 701 758.7 815.1 849.9 858.1 1,102.00
Males 96.4 108.2 127 133.6 124.8 121.8 136.4 131.8
Females 339.1 376.4 377.1 401 370.8 368.7 386.2 375.2
Males 85.2 101.9 116.7 124 129.5 136.8 145 149.6
Females 376.2 395.9 415.7 444.1 471.8 493.5 518.1 547.7
Males 57.2 62.1 68.7 83.5 86.3 85 97.6 100.8
Females 140.9 153.3 174.2 184.6 207.3 215.3 227.5 278.7
Employment
High school graduate
Postsecondary certificate or
diploma
University degree
Full-time employment
High school graduate
Postsecondary certificate or
diploma
University degree
Part-time employment
High school graduate
Postsecondary certificate or
diploma
University degree
Source: Statistics Canada
Actual hours worked (Persons
x1000) Sex 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991
Males 184.4 199 206.7 215.3 230.5 245.7 260 286.9 290.1 285.4 290.7 287.9 289.4 286.6 301.6 330.5 Females 343.6 365.5 376.2 410 444.5 467 488.7 517.3 508.9 527.7 522.6 525.1 551.4 526.7 542.5 582.9
Males 394.6 391.6 361.5 361.2 401.2 450.9 469.1 443.7 456.6 457.1 485.4 498 487.4 480.9 505.6 543.6 Females 632.1 647.3 645.2 673.2 756.7 845.4 861.6 835.3 855.2 917.5 950.7 1,023.30 1,022.20 1,008.90 1,029.90 1,082.60
Males 669.1 623.3 458.4 384.8 565.1 785.5 636.7 576.5 534.9 557.9 558.5 754.8 583.4 357.7 403 569.3 Females 475.3 457.7 393.6 376.9 478 613.2 543.2 513.9 512 544.9 566.3 698.3 610.6 498.8 535.6 636.4
Males 641.5 678.4 708.5 709.1 727.6 727.9 762.6 763.8 742.8 731.8 736 711.1 719.7 737.9 740.3 740.9 Females 759.3 811.5 901.2 931.4 929.9 913.9 958.6 972.3 1,001.70 985 1,013.80 973.4 1,049.60 1,180.50 1,147.80 1,101.00
Males 2,121.80 2,197.90 2,376.10 2,471.60 2,363.80 2,212.00 2,171.20 2,136.00 2,182.40 2,217.00 2,272.00 2,197.90 2,357.20 2,576.00 2,502.90 2,310.80 Females 825 829.3 930.1 1,015.00 988.6 936.5 914.4 953.8 988.2 1,025.70 1,096.30 1,059.00 1,190.50 1,298.70 1,309.50 1,204.80
Males 745.4 739.2 765.1 805.4 787.5 780 691.5 718.5 766.7 798 820.5 819 885.2 938.6 888.9 781.4 Females 180.3 176.9 195.1 222 224.3 221.7 214.5 238.7 253.5 275.6 293.8 297.4 338.8 382.2 367.1 330.5
Males 963.9 959.3 1,012.80 1,099.20 1,076.00 1,056.40 987.6 1,038.50 1,098.40 1,175.70 1,204.70 1,254.60 1,374.50 1,430.70 1,395.30 1,283.90 Females 139.7 145 163.6 178.3 178.8 182.8 193.5 211.7 230.1 248.7 261.5 280.9 319.5 343.9 360 338
40 hours
41 to 49 hours
50 hours or more
1 to 14 hours
15 to 29 hours
30 to 34 hours
35 to 39 hours
From the above table it is evident males work longer than females.
ABSENCE RATES FOR FULL TIME PAID WORKERS
Source: Statistics Canada
SexPresence of
children1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
With children 0.9 0.9 1 1.1 1.1 1 1.1 1 1.2 1.1 1.1 1.2 1.3 1.3Without children 0.7 0.9 0.9 0.8 0.7 0.7 0.7 0.8 0.7 0.7 0.8 0.9 0.9 0.9
With children 7.8 8.7 9.4 9.3 10.5 10.9 12.1 11.9 12 11.6 2.1 1.9 2.1 2.1Without children 1.7 1.8 2 2.3 1.8 2 2 2 2.2 2.3 1.1 1.2 1.1 1.1
Males
Females
Females miss a lot more work overall than males. This could be another reason why a man may be preferred over a
woman. Females with children miss the most amount of work.
Days Missed at Work for Full Time Paid Workers
0
2
4
6
8
10
12
14
1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Male (Children)
Female (Children)
Female (No Children)
Male (No Children)
WORKING OVERTIMESource: Statistics Canada
Overtime Sex 1997 1998 1999 2000 2001
Males5,609.90 5,691.20 5,880.30 6,090.70 6,152.20
Females 4,934.20 5,095.60 5,283.70 5,487.80 5,614.10
Males1,190.60 1,197.00 1,256.80 1,403.20 1,450.70
Females 752.9 766.6 801.1 897.9 966.6
Males547.4 555.5 559.8 613.1 649.4
Females 467.4 471.1 495.4 553.5 612.2
Males614.2 616.9 668.8 750.1 752.4
Females 266.4 278 286.8 315.4 321.6
Total employees at work (Persons)
Employees working overtime (Persons)
Working unpaid overtime (Persons)
Working paid overtime (Persons)
Overall men work longer hours than females.Overall men work longer hours than females.Overall men work longer hours than females.Overall men work longer hours than females.
MULTIPLE JOB HOLDERS (PERSONS x1000)Source: Statistics Canada
Sex 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Males 294.2 323.3 336 342.1 325 322.3 341.1 327.9 326.5 338.3 346.5 343 349.1 336.1 329.5
Females209.9 247.9 259.3 288 287 296.5 309 319.7 329.3 351.6 365.8 364.1 375 381.4 378.4
Find the Z-Score for 1987 and 2001…
Average Male: 332.06
Average Female: 317.547
Standard Deviation Male: 13.5081
Standard Deviation Female: 52.7895
Males: Females:
1987:
Z= 294.2 – 332.06 Z= 209.9 – 317.
13.5081 52.7895
=-2.803 =-2.039
2000:
Z= 329.5 – 332.06 Z= 329.5 – 317.547
13.5081 52.7895
=-0.1895 =2.0646
Multiple Job Holders (Persons x1000)
200
220
240
260
280
300
320
340
360
380
400
1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Year
Males
Females
AVERAGE EARNINGS BY SEXSource: Statistics Canada
Statistics (Dollars)
Average earnings,
female
Average earnings,
male
Female to male earnings ratio (Percent)
1980 17,699 34,176 51.81981 17,893 33,409 53.61982 17,500 31,809 551983 17,642 31,962 55.21984 18,064 31,425 57.51985 18,095 32,183 56.21986 18,727 32,618 57.41987 19,002 32,913 57.71988 19,378 33,727 57.51989 19,965 33,826 591990 19,969 33,413 59.81991 19,971 32,486 61.51992 20,654 32,363 63.81993 20,413 31,761 64.31994 20,623 33,168 62.21995 21,080 32,421 651996 20,879 32,336 64.61997 21,013 33,120 63.41998 21,999 34,171 64.4
Mean Average Earnings Male: $ 32 805
Mean Average Earnings Female: $19 503
Median Average Earnings Male: $19 956
Median Average Earnings Female: $32 618
Average Female to Male Ratio: 59.5%
Standard Deviation Female Data: 1398.236
Standard Deviation Male Data: 829.9842
*Calculations done by excel
Average Earnings by Sex
15,000
17,000
19,000
21,000
23,000
25,000
27,000
29,000
31,000
33,000
35,000
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998
Year
Aver
age
Earn
ings
Male
Female
RETIREMENTSource: Statistics Canada
Class of worker
Sex Males Females Males (x-mean) Females (x-mean)1976 65.3 63.9 1.6 1.51977 65.6 63.8 1.9 1.41978 65.6 63.6 1.9 1.21979 65 63.4 1.3 11980 65.1 63.5 1.4 1.11981 65.1 63.5 1.4 1.11982 65 63.8 1.3 1.41983 64.7 62.8 1 1.41984 64.9 63.4 1.2 0.41985 64.6 63 0.9 11986 64.1 62.8 0.4 0.41987 63.8 62.9 0.1 0.51988 63.5 62.9 -0.2 0.51989 63.5 62.6 -0.2 0.21990 63.1 62.6 -0.6 0.21991 63.1 62 -0.6 0.41992 62.5 63.6 -1.2 1.21993 62.4 61.7 -1.3 -0.71994 62.2 61.7 -1.5 -0.71995 62.2 61.4 -1.5 -11996 62.3 61 -1.4 -1.41997 62.1 60 -1.6 -2.41998 61.6 59.8 -2.1 -2.61999 61.7 60.1 -2 -2.32000 62.3 60.6 -1.4 -1.8
Total -1.2 2Average of Males 63.652 ^2 1.44 4
Average of Females 62.416 1.44/N 4/NN=24 1.44/24.00 4 / 24.00
0.06 0.16666Take Sqrt 0.245 0.408
Total, all retirees
Standard Deviation Calculations for Male and Female
Median: Male
=63.5 Female =62.8
Mode: Male
=65.6 Female =63.8
Average Retirement Age in the Labour Force
59
60
61
62
63
64
65
66
1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Male
Female
Labour force survey estimates (LFS), wages of employees by type of work, Standard Occupational Classification, 1991 (SOC), annual (data in thousands)
Source: Statistics Canada
Standard Occupational Classification, 1991 (SOC) Sex 1997 1998 1999 2000 2001
Males5,983.80 6,099.20 6,265.30 6,480.70 6,583.70
Females 5,437.00 5,616.00 5,803.00 6,007.60 6,183.80
Males 586 566.6 581.8 593.2 538.2
Females 379.6 392.3 353.6 358.9 325
Males604.9 640.3 634.4 650.3 674.4
Females 1,647.70 1,661.70 1,724.20 1,753.40 1,828.40
Males539.5 586.2 627.5 674.1 693.2
Females 130.6 139 164.7 178.2 187.4
Males 92.1 91.6 98.6 90.6 98
Females 545 542.5 559 582.9 604.1
Males 323.3 318.1 339.1 334.6 333.8
Females 511.7 534.1 562.8 589.8 612.9
Males 102 108.3 115.8 111.4 119.5
Females 125.7 133 149.8 156 162.5
Males 1,218.10 1,257.40 1,285.70 1,369.80 1,445.80
Females 1,655.90 1,727.60 1,801.80 1,885.50 1,969.00
Males 1,577.20 1,557.60 1,578.30 1,621.30 1,640.10
Females 97 110.6 96.9 102.9 106.7
Males 207.3 209.9 207 213.6 218.8
Females 40.7 50.1 46 48 45.3
Males733.4 763.2 797.2 821.8 821.8
Total employees, all occupations
Management occupations
Business, finance and administrative occupations
Natural and applied sciences and related occupations
Trades, transport and equipment operators and related occupations
Occupations unique to primary industry
Occupations unique to processing, manufacturing and utilities
Health occupations
Occupations in social science, education, government service and religion
Occupations in art, culture, recreation and sport
Sales and service occupations
Total Employee's Wages (per thousand)
0.00
1,000.00
2,000.00
3,000.00
4,000.00
5,000.00
6,000.00
7,000.00
1997 1998 1999 2000 2001
Year
Male
Female
REASON FOR PART-TIME WORK BY SEXSource: Statistics Canada
Reason for part-time work Sex 1997 1998 1999 2000 2001
Males791.7 810.3 813.6 829.7 844
Females 1,843.10 1,863.50 1,868.30 1,871.80 1,887.60 Males 4 4.3 5.3 5.9 6.3 Females 288.3 279.8 291.6 284.1 292.4
Males11.7 9.6 12.2 13.9 13.3
Females 106.2 104.1 95.7 113.9 118 Males 312.7 326.7 349.1 364.3 373 Females 372.2 392 415.5 448.8 460.5
Males82 72.4 66.1 53.5 46.9
Females 130.1 121.3 103.4 84.1 77.4
Could not find full-time work, looked for full-time work in last month
Part-time employment, all reasons
Caring for children
Other personal or family responsibilities
Going to school
Part-time Employment
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1997 1998 1999 2000 2001
Year
Male
Female
Reason for Part-time Work B/C Child Care
1
2
LABOUR FORCE SURVEY
Source: Statistics Canada
Job PermanenceUnion
coverageSex Age group 1997 1998 1999 2000 2001
15 to 24 years 108 111 125.2 135.4 142.7
25 to 54 years 1,637.70 1,620.70 1,588.70 1,625.80 1,610.5055 years and over 195.4 199.2 193.7 200.8 207.6
15 to 24 years 81.7 79.6 85.9 93.9 103.6
25 to 54 years 1,362.00 1,355.30 1,390.80 1,417.50 1,439.2055 years and over 124.3 135 137.3 155.7 170.5
15 to 24 years 624.9 619.6 639.1 654 652.5
25 to 54 years 2,485.60 2,586.10 2,702.70 2,786.20 2,845.5055 years and over 273.2 283.8 288.2 311.1 335.3
15 to 24 years 597.7 603.6 627.1 649 643.8
25 to 54 years 2,405.60 2,500.70 2,568.50 2,616.50 2,691.2055 years and over 228.2 233.6 262.7 278.7 288.3
15 to 24 years 30.8 30.1 32 39.3 47.9
25 to 54 years 119.7 115.4 124.9 128.2 139.855 years and over 12.5 12.1 13.9 16.9 18.9
15 to 24 years 25.2 30.5 33.7 39.2 42.4
25 to 54 years 139.3 150.7 145 159.2 168.455 years and over 7.1 8.1 11.2 12.9 17.6
15 to 24 years 224.5 247 270 287.6 288.9
25 to 54 years 237.7 240.4 248.5 247.5 245.555 years and over 33.7 33.9 38.6 48.1 48.6
15 to 24 years 198.3 233 251 274.3 299.7
25 to 54 years 244.2 257.7 260.9 277.1 284.355 years and over 23.3 28.1 28.9 33.6 34.9
Temporary employees
Union coverage
Males
Females
No union coverage
Males
Females
Permanent employees
Union coverage
Males
Females
No union coverage
Males
Females
Union Coverage (Males vs. Females)
0
500
1000
1500
2000
2500
3000
3500
4000
1997 1998 1999 2000 2001
Year
Permant Employee, Union, Male
Permanent Employee, Union, Female
Permanent Employee, Non-Union, Male
Permanent Employee, Non-Union, Female
Temporary Employee, Union, Male
Temporary Employee, Union, Female
Temporary Emplyee, Non-Union, Male
Temporary Employee, Non-Union, Female
Permanent Employees (Union)
1400
1500
1600
1700
1800
1900
2000
1997 1998 1999 2000 2001
Year
Male
Female
Permanent Employees (Non-Union)
3100
3200
3300
3400
3500
3600
3700
3800
3900
1997 1998 1999 2000 2001
Year
Males
Females
Temporary Employees (Union)
140
150
160
170
180
190
200
210
220
230
240
1997 1998 1999 2000 2001
Year
Males
Females
Temporary Employees (Non-Union)
400
450
500
550
600
650
1997 1998 1999 2000 2001
Year
Male
Female
DELAYING MOTHERHOOD IS GOOD FOR THE PAYCHEQUE
Source: Statistics Canada
Early On Time Delayed Early On Time Delayed Early On Time Delayed
Average $14.42 $15.96 $16.89 $14.79 $15.71 $16.34 $15.47 $16.74 $17.74
Hourly Wage rate42 42 42 55 55 55 44 44 44
Number of years of schooling
13 14 14 12 13 13 13 14 14
Years of potential work experience
23 22 22 37 37 36 24 24 24
Actual years of full-time, full-year work experience
15 15 17 23 21 25 17 18 19
Had Children:
Mothers Born Before 1948
Mothers Born Between 1948 and 1960 Mothers Born After 1960
Lone-parent families 1996 Male lone-parent families 2.5
Female lone-parent families12.1
Lone-Parent Families
1
2
There are more female lone parent families than male. Female lone parent families made up 12% of all family types in 1996.
CONTRIBUTION OF WIVES EARNINGS TO OVERALL FAMILY INCOME (1994)
10% < 10-19% 20-29% 30-39% 40-49%50% or more
13.1 14.6 17.3 18.8 18.3 17.9
Source: The Vanier Institute of the Family
17.9 percent of families have a female as household
head.
Contribution of Wives Earnings to Overall Family Income (1994)
0
2
4
6
8
10
12
14
16
18
20
10% < 10-19% 20-29% 30-39% 40-49% 50% or more
Percentage
On average woman provide from 30-40% of family income.
Total statistics studied (n):
1. Males dominate the labour force –Males +1
2. Males are hired more than females –Males +1
3. Males are laid off more often –Female +1
4. Men work more hours –Males +1
5. Females retire earlier –Males +1
6. Females miss more work –Males +1
What is the probability a man will be hired?
P(A)=n(A) number of outcomes where a man has an advantage
n(S) total possible outcomes
P(male is hired)= 5
6
=0.83
Therefore the probability of a male being hired over a female is 83%, however this is biased because not all these factors are considered during the hiring process.
What are the odds of a female being hired?
Odds in favour of A = P(A) = 0.17 =0.2 or 17:83 P(A’) 0.83
P(A’)= 0.83
P(A) = 1 – 0.83 = 0.17
COMBINATIONS:
a) Seven qualified women and eight qualified men send in their resumes to a company and are called back for interviews. After the interview the company decides to hire five of these people. In how many ways could they be selected with no restrictions?
(15 C 5) = 3003
b) In order to avoid being accused of hiring only men, 2 females must be hired along with the remaining given to 3 of the men. In how many ways could they be selected?
(7 C 2) * (8 C 3) = 1176
I compared Canada to Brazil, a poorer country, I compared Canada to Brazil, a poorer country, and surprisingly the results were very similar. and surprisingly the results were very similar. They also have a male dominated workforce; They also have a male dominated workforce;
more males are present in the labour force than more males are present in the labour force than females. Again the women dominated part-time females. Again the women dominated part-time and service jobs, where as the males dominated and service jobs, where as the males dominated
agricultural jobs, manufacturing, and agricultural jobs, manufacturing, and construction. The only difference is the type of construction. The only difference is the type of
work, Brazil has agriculture, construction, work, Brazil has agriculture, construction, mining, etc., whereas Canada has more indoor mining, etc., whereas Canada has more indoor
occupations such as financing, retail, health care, occupations such as financing, retail, health care, etc. Women are also paid less than malesetc. Women are also paid less than males
I compared Canada to Brazil, a poorer country, I compared Canada to Brazil, a poorer country, and surprisingly the results were very similar. and surprisingly the results were very similar. They also have a male dominated workforce; They also have a male dominated workforce;
more males are present in the labour force than more males are present in the labour force than females. Again the women dominated part-time females. Again the women dominated part-time and service jobs, where as the males dominated and service jobs, where as the males dominated
agricultural jobs, manufacturing, and agricultural jobs, manufacturing, and construction. The only difference is the type of construction. The only difference is the type of
work, Brazil has agriculture, construction, work, Brazil has agriculture, construction, mining, etc., whereas Canada has more indoor mining, etc., whereas Canada has more indoor
occupations such as financing, retail, health care, occupations such as financing, retail, health care, etc. Women are also paid less than malesetc. Women are also paid less than males
In conclusion my hypothesis was half correct and half incorrect. Women do have an equal opportunity in achieving the job depending on their employer. However, women have a greater chance over men to sustain the job. Unfortunately men are still paid a greater amount than women, even for the same tasks. The trends show that this will
eventually diminish and equality can exist in Canada’s workforce, this may occur in the next 100 years. The same trends are true internationally.
Next time I would like to obtain a larger sample size, such as the USA vs. Canada vs. Australia vs. Hong Kong. With the larger sample size I could answer the
question “where is the best place to live as a working women?” Due to the limited size of my studies my conclusion could contain biased results.
Overall I was very satisfied with the results of this project. I found it very challenging to mathematically manipulate the tables and graphs to better my data. The tables were very complex, and I often found it difficult to create a graph with the data.
Once again I found this project very time consuming but worthwhile.
Related Documents
