# Stat Project Essay

1721 Words May 27th, 2013 7 Pages
Stat 113 Beiyi(Summer) Liu
Professor Ihsan Shahwan
Final Project Part C
In order to figure out how variables relates to each other and the connections among the variables, or one can predict the other. I will choose three quantitative variables or two quantitative variables and one categorical variable on each pairs. I will also use graphs of scatter plots; regression and correlation to understand that how one variable affect other two variables. There are six groups below:
Group one: High School Percentile (HSP), Cumulative GPA (GPA), and ACT Composition Score (COMP) a) HSP vs GPA

b) HSP vs COMP

c) COMP vs GPA

From graph a, we can find out that there is moderate
From graph b, there is weak negative liner relationship between ENGLISH scores and COMP scores; the correlation is-0.038; the equation of regression is COMP=-0.0584814*AGE+24.6029; the slope is -0.0584814 which is negative; when the predictor variable CREDITS increase, the response variable GPA also weakly increase; for example, when AGE increase by 1, the COMP scores will decrease 0.0584814.
From graph c, there is a strong positive liner association between ENGLISH scores and COMP scores; the correlation is 0.843; the equation of regression is COMP=0.65656*ENGLISH+8.43327; the slope is 0.65656 which is positive; when the predictor variable ENGLISH scores increase, the response variable COMP scores also strongly increase; for instance, when ENGLISH scores increase by 1, the COMP scores will increase 0.65656. According to the graphs and data above, we can find out a student who is older with a litter lower English and Comp scores; the student with higher English score has very high Comp score.
Group Five: Quantitative variables High School Percentile (HSP), Age (AGE) and a categorical variable Sex (SEX) a) HSP vs GPA (both sex)

b) HSP vs GPA (males)

c) HSP vs GPA (females)

From graph a, we can see that there is a moderate positive liner relationship between HSP and GPA; the correlation is 0.552; the equation of regression is GPA=0.0163928*HSP+1.8408; the slope is 0.0163928 which is positive; when the predictor

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