Employment Discrimination between Men and Women - Research Proposal Example

Name : xxxxxxxxxxx Institution : xxxxxxxxxxx Course : xxxxxxxxxxx Title : Employment Discrimination Between men and women. Tutor : xxxxxxxxxxx @2010 Introduction Gender differences in employment positions have been evident in many occupations. This report aims to compare the income earned by the male and female in the workplace. It brings out the fact of discrimination in workplace regarding to the gender issue. Inequality in salary of women is a controversial issue in the United States. Although the women’s opportunities of getting a job is now more easier after the imposition of the Civil Rights Act making sex discrimination illegal. There are evidences which show women’s salaries are lower than the men salaries in a certain extent even if they are doing the same job (Morris, 2005). This overwhelming issue would be discussed through the comparison of the data collected from a large corporation in the United States. This report will identify differences in relation to job category, amount of salary and sex of employees. Method The data of this report includes samples from US where secondary education takes 12 years and undergraduate college education takes 4 years. It is a random sample collected from a large US corporation and consists of 446 samples. Demographic variables such as sex, age, education level, language background, and previous employment will be analyzed. In addition, employment information on job classification, current salary (grouped and ungrouped), beginning salary, and months since hire will be analyzed to come up with conclusions. The analysis involves a comparison in the change in salary per month between the two genders, comparison of frequency distribution of men and women across job classifications, and comparison of men and women in terms of the summary statistics. Research Question 1. Compare the change in salary per month between men and women in terms of summary statistics for center and spread. Is the difference in means statistically significant? 2. Compare the frequency distribution of men and women across job classifications. Is any difference statistically significant? 3. For each job classification compare men and women in terms of the summary statistics you used in Q.1 After carrying out the analysis the following observations in were made: Compare the change in salary per month between men and women in terms of summary statistics for center and spread. Is the difference in means statistically significant? Question 1 Results here is a relationship between sex of the employees and the change in salary. The relationship has a P value of 0.397 which indicates a significant relationship. This is in accordance with the relationship between one’s sex and the monthly salary. This is indicated by Pearson correlation which is 0.474. This is evident in table 1b in the appendices. In addition, the mean salary indicates that female workers are paid almost half of what their male counter parts get. While the mean current salary for male workers is $42 669.39, that for the female workers is $26 016.26 as indicated in Table 1: The difference in means is thus statistically significant since it shows that women a far much lower salary figure compared to men. Table 1 Summary of the Mean, Std Deviation and Variance of current salary earnings Sex of respondent Mean N Std. Deviation Variance Female $26,016.26 215 $7,572.144 5.734E7 Male $42,669.39 231 $20,245.621 4.099E8 Total $34,641.54 446 $17,573.343 3.088E8 Table 1a Difference between starting and current salary Sex of respondent Mean N Std. Deviation Female $12929.6744 215 $5672.27533 Male $21757.4459 231 $13110.15787 Total $17501.9058 446 $11126.93709 The mean of the difference between current salary of the respondents and the starting salary is higher in males than in females (refer to table 1a). Table 1a) illustrates that the difference between the starting salary and current salary is higher in males than in females. This is a clear show that the males receive more increments as compared to their female counterparts. It can thus be concluded that the more prestigious managerial jobs get more salary increments as opposed to the clerical jobs. This is reflected in the higher means of the difference between starting salary and current salary in men when compared to that of the women. As a result, males are favored in terms of salary increment as opposed to the females. Compare the frequency distribution of men and women across job classifications. Is any difference statistically significant? Question 2 Results According to the analysis done, males take up most of the managerial positions as compared with women. This is clearly illustrated in table 2 : Table 2 A comparison between placement in different job categories and sex of the employee Sex of respondent * Employment Category Cross tabulation Clerical Manager Total Sex of respondent Female Count 205 10 215 % within Sex of respondent 95.3% 4.7% 100.0% % within Employment Category 56.6% 11.9% 48.2% % of Total 46.0% 2.2% 48.2% Male Count 157 74 231 % within Sex of respondent 68.0% 32.0% 100.0% % within Employment Category 43.4% 88.1% 51.8% % of Total 35.2% 16.6% 51.8% Total Count 362 84 446 % within Sex of respondent 81.2% 18.8% 100.0% % within Employment Category 100.0% 100.0% 100.0% % of Total 81.2% 18.8% 100.0% According to Table 2, the total number of males working in the firm is more than females as they represent 51.8 percent of the total. Most of the female employees are in the clerical job category while most of the people in the managerial positions are males. Despite the fact that there are substantial numbers of both males and females with reference to the clerical position, the females dominate. Clerical position jobs are considered to be of less value as compared to the managerial positions. The results show the prevalence of sex discrimination with the women taking more of the less valued clerical jobs. The graph below (bar chart 2) clearly demonstrates this, Bar Chart 2 As shown by the correlation coefficient in table 2b in the appendices, there is a significant correlation between sex and employment category. The results further indicate that men prefer and take the more prestigious managerial jobs while leaving other jobs such as clerical jobs to the women. Only a few women occupy the managerial positions which do not necessarily imply that they are not qualified to take the positions. For each job classification compare men and women in terms of the summary statistics you used in Q.1 Question 3 Results. The relationship between the sex of the individual and employment category is reasonably significant. As governed by the analysis, there is a very strong relationship between sex and the current salary group. This means that males are paid more even when they are in the same job category with females. The P value is 0.553 indicating a very strong relationship between the two as compared with the relationship between sex and job category whose P value is 0.350 as indicated in table 3b in the appendices. The results indicate that there is a strong relationship between the job position and the difference between starting salary and current salary. The more prestigious job placement and this case the managerial positions have a higher value of the difference between starting salary and current salary in comparison to clerical jobs. Sex discrimination is evidence by the fact that more men occupy the managerial positions as opposed to women. Because men occupy the larger proportion of the managerial positions as opposed to women, then the difference between starting salary and current salary will be higher for the men. Those in clerical positions are paid less as compared to those in managerial positions. Referring to Table 3a in the appendices, most females are in the least paying group ($15 000-$25 000) as accounted for by 87.3 percent. On the other hand, 12.7 percent account for the males. In the highest paying group (above $45 000), 77.8 percent are males while females only account for 22.2 percent. The strongest relation is that between employment category and current salary group when referenced with gender. There is a lot of discrimination against the women in terms job category and salary as well as salary grouping. Conclusion The analysis has revealed different kinds of relationships at varying significant levels. The analysis shows that there is a significant strong relationship between the differences between starting salary and current salary in both men and women. There is also a significant relationship between employment category and sex of the employees. Based on the analysis, women experience a lot of discrimination judging by this sample. Regardless of the education of the women, men continue to dominate and take up most top positions that give them an upper hand when it comes to receiving higher salaries. Men take up managerial positions and even if they are in the same job category as the females, females are placed under a different salary group on a lower scale. In conclusion, the observations show that the male respondent had averagely received higher changes in salary than the female respondents on both clerical and manager level. The pattern shown that female is tend to receive lower chance of getting a higher salary in the US corporation in the case as well as being in the manager level compare to the male respondents. This might reveal the hidden problem of sex-discrimination in the corporation and income inequality in the society. At last, gender should not be the guiding criteria when it comes to employment, there are more important factors to be considered like one’s achievements with regard to education and credentials. The society should embrace change and realize that it does not matter if one is a male or a female as long as they have what it takes to take charge of a certain responsibility. Limitations of the Analysis There was some missing data identified after data cleaning. These means that the data did not account for 100 percent of the results collected. For instance, in the variable age in years, there is id 37 was indicated to have 400 years. This is not possible and was thus referred to as a missing value. In addition, id132 is aged 30 years yet the data indicates that the total number of years that this case has been in school is 35 years which is not possible. This has also been defined as a missing value. Though the data has been analyzed scientifically, the sample is too small for generalization. It is not also clear if the data was also entered and coded scientifically! Appendices Table 1b. Correlations between respondent's sex and current salary Sex of respondent Difference between starting and current salary Sex of respondent Pearson Correlation 1 .397** Sig. (2-tailed) .000 N 446 446 Difference between starting and current salary Pearson Correlation .397** 1 Sig. (2-tailed) .000 N 446 446 **. Correlation is significant at the 0.01 level (2-tailed). Table2b. Correlations between the sex of the respondent and employment category Sex of respondent Employment Category Sex of respondent Pearson Correlation 1 .350** Sig. (2-tailed) .000 N 446 446 Employment Category Pearson Correlation .350** 1 Sig. (2-tailed) .000 N 446 446 **. Correlation is significant at the 0.01 level (2-tailed). Table 3a. Comparison between current salary group, sex and employment category Sex of respondent * Employment Category * Current salary group Cross tabulation Current salary group Employment Category Total Clerical Manager $15,000-$25,000 Sex of respondent Female Count 124 124 % within Sex of respondent 100.0% 100.0% % within Employment Category 87.3% 87.3% % of Total 87.3% 87.3% Male Count 18 18 % within Sex of respondent 100.0% 100.0% % within Employment Category 12.7% 12.7% % of Total 12.7% 12.7% Total Count 142 142 % within Sex of respondent 100.0% 100.0% % within Employment Category 100.0% 100.0% % of Total 100.0% 100.0% $25,001-$35,000 Sex of respondent Female Count 69 1 70 % within Sex of respondent 98.6% 1.4% 100.0% % within Employment Category 40.8% 100.0% 41.2% % of Total 40.6% .6% 41.2% Male Count 100 0 100 % within Sex of respondent 100.0% .0% 100.0% % within Employment Category 59.2% .0% 58.8% % of Total 58.8% .0% 58.8% Total Count 169 1 170 % within Sex of respondent 99.4% .6% 100.0% % within Employment Category 100.0% 100.0% 100.0% % of Total 99.4% .6% 100.0% $35,001-$45,000 Sex of respondent Female Count 10 4 14 % within Sex of respondent 71.4% 28.6% 100.0% % within Employment Category 23.8% 44.4% 27.5% % of Total 19.6% 7.8% 27.5% Male Count 32 5 37 % within Sex of respondent 86.5% 13.5% 100.0% % within Employment Category 76.2% 55.6% 72.5% % of Total 62.7% 9.8% 72.5% Total Count 42 9 51 % within Sex of respondent 82.4% 17.6% 100.0% % within Employment Category 100.0% 100.0% 100.0% % of Total 82.4% 17.6% 100.0% Over $45,000 Sex of respondent Female Count 2 5 7 % within Sex of respondent 28.6% 71.4% 100.0% % within Employment Category 22.2% 6.8% 8.4% % of Total 2.4% 6.0% 8.4% Male Count 7 69 76 % within Sex of respondent 9.2% 90.8% 100.0% % within Employment Category 77.8% 93.2% 91.6% % of Total 8.4% 83.1% 91.6% Total Count 9 74 83 % within Sex of respondent 10.8% 89.2% 100.0% % within Employment Category 100.0% 100.0% 100.0% % of Total 10.8% 89.2% 100.0% Table 3b. Correlations : sex, employment category and the difference between current and starting salary Sex of respondent Employment Category Difference between starting and current salary Sex of respondent Pearson Correlation 1 .350** .397** Sig. (2-tailed) .000 .000 N 446 446 446 Employment Category Pearson Correlation .350** 1 .703** Sig. (2-tailed) .000 .000 N 446 446 446 Difference between starting and current salary Pearson Correlation .397** .703** 1 Sig. (2-tailed) .000 .000 N 446 446 446 **. Correlation is significant at the 0.01 level (2-tailed). Read More