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Created: Apr 21, 2016
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a.serrano project 2
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agustin serrano 

 My report is comparing High School GPA to College GPA based on female and male.I got my Data off StatCrunch. The sample size was 228 students. AS it is shown in my results, the x/independent variable is the HS GPA and the y/dependent is the College GPA. Hence the HS GPA will help us conclude what the College GPA will be.

The regression equation for the project is GPA=1.07277446 + 0.61922928 HS GPS. This is a good perdictor because it helps give me a vivid picture of the relationship between GPA and HS GPS. The points are scattered on a line and widely distributed. It gives the GPA of 1.0727446 and with a postive slope of 0.61922928. The correlation coefficient is 0.71554736 which shows a positve relationship because it is close to 1 but not greater .8 and it is positive going in the upright postion. If R=0.71554736 then R-sq= 0.51200803 and has the estimate of error of standard deviation is 0.37438843

The report compares HS GPA to College GPA for 228 students picked at random sorted by females and males. It was supported by a positive slope of 0.61922928. It has a clear regression of 0.71554736.The higher the HS GPA the better the College GPA.      

Result 1: Simple Linear Regression   [Info]
Simple linear regression results:
Dependent Variable: GPA
Independent Variable: HS GPA
GPA = 1.0727446 + 0.61922928 HS GPA
Sample size: 228
R (correlation coefficient) = 0.71554736
R-sq = 0.51200803
Estimate of error standard deviation: 0.37438843

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept1.07274460.13519836 ≠ 02267.9345978<0.0001
Slope0.619229280.040212884 ≠ 022615.398778<0.0001

Analysis of variance table for regression model:

Result 2: !Simple Linear Regression   [Info]
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Data set 1. Body Image Data Set   [Info]
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