Comparing incomes: People with college degrees and people without college degrees - Research Paper Example

Incomes for people with college degrees are collected from Management occupations, Business and financial operations occupations, Computer and mathematical occupation, Architecture and engineering occupations, Life, physical, and social science occupations, and legal occupations. Data are selected randomly, and numbers of data from each population consist of 30 values. Table 1 displays the sample data for both populations. The code column states the job code according to the Bureau of Labor classification.

Figure 1 and Figure 2 display histograms of data respectively for income without a college degree and with a college degree. The graphical representations of data of both categories do not display Skewness. Income without college education Income with college education Code Income Code Income Code Income Code Income 31-1015 25,700 45-2041 20,870 11-2022 119,980 17-2041 84,140 31-1014 26,620 45-2090 21,080 11-3121 109,590 17-2061 103,980 35-2011 18,780 45-3011 36,900 13-1051 63,080 17-2071 91,810 35-3011 21,630 45-4011 28,600 13-1111 88,070 17-2072 95,250 35-3031 20,710 45-4020 35,140 13-2041 69,500 17-2081 85,140 35-3041 22,010 47-2011 55,830 13-2082 41,700 17-2121 96,140 35-9021 18,930 47-2021 50,370 15-1111 103,670 17-2141 84,770 35-9099 23,390 47-2031 44,520 15-1121 83,800 17-2161 107,140 37-2010 24,130 47-2042 38,450 15-1131 78,260 19-1022 73,250 37-2011 24,850 47-2061 34,490 15-1133 93,280 19-1041 71,400 37-2012 21,820 47-2071 40,170 15-1152 62,960 19-2011 102,550 37-3010 26,460 47-2141 38,590 15-2041 79,570 19-2012 114,150 37-3012 32,000 47-2142 36,630 17-1012 68,030 19-3011 99,480 37-3013 33,850 53-3021 38,470 17-2011 104,810 19-3041 80,820 37-3019 30,620 53-6021 21,540 17-2021 77,370 23-1011 130,880 Table 1.

Raw data collected from Bureau of Labor Statistics Figure1. Histogram of sampling data of income without a college degree Figure 2. Histogram of sampling data with a college degree The sample data are also presented graphically in Figure 3 along with the values of average incomes. Figure 3. Graphical display of incomes of people with and without degree Figure 4 and Figure 5 display frequency histograms of sampling data. The nature resembles normal distribution for both populations. Figure 4. Frequency histogram of income without college degree Figure 5.

Frequency histogram of income of people with college degree Data type This study is a non-experimental research, and sample data characterizes continuous interval level (“Variable Types”). Data are obtained for two populations: income of people without a college degree and with a college degree. Both samples are independent, and sample sizes are large enough to conduct statistical interpretation. Table 2 displays descriptive statistics values of both data groups. Figure 6 represent a scatter plot of sampling data.

The scattered plot is computed with sorted data in ascending order. Index Income without degree Income with degree Min 18780 41700 Max 55830 130880 Mean 30438 88819 Median 27610 86605 Standard Deviation 9620 19167 Standard Error 1756 3499 Table 2. Descriptive statistics values Figure 6. Scattered plot of incomes with and without college degrees Regression analysis Let X, be the income of people without a college degree, and Y be the income with a college degree. A linear regression analysis computed between X and Y, and it is represented through the equation, Y = 79663 + 0.3 X. However, the value of R = 0.

15098 implies a very weak