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Owner: 7jshelton
Created: Jul 24, 2019
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Janice Shelton- Project 3 Revision
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Janice Shelton Project 3 

The data collected is on the average gas prices in Illinois versus the average US prices.  In this data Illinois is the dependent variable and the U.S. is the independent variable.  The size of this data is 30. I retrieved this data from stat crunch data website.

The Regression equation is y= -0.3882 + 1.1613x. correlation coefficient is 0.9394. Coefficient of determination is 0.8825. 88.25% of the variation in Y  is explained by the regression equation. The R is very strong The regression equation for this data is y= -0.3882+ 1.1613x. The line goes up on the scattered plot. The correlation coefficient is 0.9394. The direction denoted by r is up, which is positive. The strength of r is very strong. The coefficient of determination is 0.8825 which brings the percent of variation to 88.25% explained by the regression equation.

The sample size of this data is 30, the dependent variable is Illionois, and the independent variable is the USA  A regression should be done on the data because the r is very strong. The coefficient of determination 0.8825, which is 88.25% of the variation Y  that is explained by the regression equation.

Result 1: Simple Linear Regression project 3   [Info]

Simple linear regression results:

Dependent Variable: Illinois Average
Independent Variable: USA Average
Illinois Average = -0.38820935 + 1.1613071 USA Average
Sample size: 30
R (correlation coefficient) = 0.9394201
R-sq = 0.88251013
Estimate of error standard deviation: 0.029669267

Parameter estimates:

ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept-0.388209350.21980636 ≠ 028-1.76614250.0883
Slope1.16130710.080077113 ≠ 02814.502359<0.0001

Analysis of variance table for regression model:


Result 2: Project 3 Revision   [Info]
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Data set 1. Gas Prices - U.S. v IL   [Info]
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