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Owner: sbolde13
Created: Apr 23, 2018
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SSmith Project 3
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Sharita Smith 

Project 3

Introduction:  Golden State Warriors selected stats 2016/2017 regular season is the data i used, I pulled this data from statcrunch.  The sample size is 12, the first quantitative variable is (PTS) points score durnig the game and the second quantitative variable is (FT%) Free throws precentages.

Analysis:The regression equation is 65.093695+0.90831867x.The correlation coefficient is 0.70330594. The coefficient of determination is R-sq. = 0.49463924. The linear relationship is strong because it is between .70 to .84 and this is considered to be a strong positive. The coefficient of determination is 0.7033 which means that 70.33% of the change in Y is determined by the regression equation.

Conclusion: Golden State Warriors selected stats 2016/2017 regular season data was used to obtain the sample size of 12.  The dependent X variable was the (PTS) points score, and the independent Y variable was the (FT%) Free throws precentages. A regression should be done because the correlation coefficient is 0.7033 and the points on the scatterplot are  somewhat scattered and cluster about the regression line and about 70% of the change in y is explained by the regression equation. Therefore, a linear regression should have been completed on this data.

Result 1: Golden State Warriors Simple Linear Regression pj33   [Info]
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Result 2: Simple Linear Regression project 3   [Info]
Simple linear regression results:
Dependent Variable: FT%
Independent Variable: PTS
FT% = 65.093695 + 0.90831867 PTS
Sample size: 12
R (correlation coefficient) = 0.70330594
R-sq = 0.49463924
Estimate of error standard deviation: 8.2249666

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept65.0936953.858311 ≠ 01016.871034<0.0001
Slope0.908318670.29033187 ≠ 0103.12855310.0107

Analysis of variance table for regression model:

Data set 1. All MLB Salaries (1985-2015)   [Info]
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HTML link:
<A href="">SSmith Project 3</A>

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