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Linear Regression Analysis on Education and Wages

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From the following data set, develop a research question and formulate a hypothesis that can be tested with linear regression analysis.

Education
Years Wage \$
6 11186
12 20852
12 10997
17 14476
8 13787
16 19452
12 16667
12 15234
12 39888
18 13162
18 20793
16 19284
17 13481
11 16789
14 11702
12 11451
16 33351
12 37771
13 25670
14 13312
16 29191
16 41780
8 29977
7 25166
4 30308
12 83443
13 15957
13 21716
9 33461
11 28219
12 31691
12 60626
12 52762
12 22133
12 32094
12 16796
12 35185
12 17690
12 15193
12 75165
12 19227
12 50235
14 44543
12 24509
12 29407
16 34746
12 68573
15 28168
13 18121
17 33498
16 29390
5 26614
12 33411
12 22485
18 83601
16 55777
14 21994
18 32138
14 13318
12 33389
10 50187
12 28440
12 37664
12 15013
10 30133
12 31799
12 29809
13 16817
14 66738
12 9879
12 34484
14 49974
8 31304
9 33959
16 30006
10 19306
8 11780
12 49898
14 17694
15 57623
11 83569
18 23027
12 32786
12 46646
11 20852
14 32235
12 19388
18 26820
16 26795
16 50171
12 31702
12 36178
13 15160
16 12285
15 60152
12 29736
12 45976
12 18752
11 17626
12 19981

https://brainmass.com/statistics/regression-analysis/linear-regression-analysis-236012

Solution Preview

Regression Analysis:
Using Microsoft Excel
Add - Ins  Megastat  Regression Analysis
Regression Analysis

r² 0.005 n 100
r 0.072 k 1
Std. Error 16988.62 Dep. Var. Wage

ANOVA table
Source SS df MS F p-value
Regression 149,104,902.4998 1 149,104,902.49 0.52 .4740
Residual 28,284,101,580.340 98 288,613,281.43
Total 28,433,206,482.840 99

Regression output confidence interval
variables coefficients std. error t (df=98) p-value 95% lower 95% ...

Solution Summary

The solution provides linear regression analysis on education and wages. A hypothesis is formulated.

\$2.19

Regression analysis.

Please see attachment and help me explain the regression analysis and scatter plot.

I ran this regression analysis. My hypothesis is that there is a positive linear relationship between years of education and salary. I used the following data set for this. (see attachment) Table 1: Wages and Wage Earners Data Set

I NEED to be able to explain the analysis in simple words. I believe that it shows a positive linear relationship. Also help me explain the scatter plot below (see attachment).

Regression Analysis

r² 0.167 n 100
r 0.408 k 1
Std. Error 15550.444 Dep. Var. Wage

ANOVA table
Source SS df MS F p-value
Regression 4,735,209,494.9482 1 4,735,209,494.9482 19.58 2.50E-05
Residual 23,697,996,987.8918 98 241,816,295.7948
Total 28,433,206,482.8400 99

Regression output confidence interval
variables coefficients std. error t (df=98) p-value 95% lower 95% upper
Intercept -699.9501 7,293.6714 -0.096 .9237 -15,174.0032 13,774.1031
Ed 2,477.0943 559.7779 4.425 2.50E-05 1,366.2334 3,587.9552

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