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Owner: igibs19
Created: Apr 24, 2018
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IGibson Project 3 (revised)
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Iesha Gibson/ Trishaun Coleman



Nutritional Data/Trans Fat vs Calories-I Gibson Project 3


Introduction: The data used for this project was obtained from the stat crunch website. It is the nutritional data for various fast food restaurants in 2017. The sample size is 127. There are 12 columns of information to choose from. For the project, we choose the trans-fat vs the calories. the independent variable (predictor) will be trans-fat (g) and the dependent variable will be calories.

Analysis: The regression equation for the data is = 348.24+204.00x. The correlation coefficient is .8015 and the coefficient of determination is .6423. Therefore, 64.23% of the change in y is explained by the regression equation and the change in x. The relationship between x (trans fat) and y (calories) has a strong and positive linear relationship because the correlation coefficient is .8015 (closer to 1). The direction of the line is going up because “r” is positive. The points on the scatter diagram are scattered about the regression line as well. So, a regression line should be done.

Conclusion: As stated before, the data was retrieved from the stat crunch website. The data used was nutritional information from various fast food restaurants. The independent variable is trans-fat. The dependent variable is calories. A regression line should be done on this data because the correlation coefficient is .8015. It is closer to 1, therefore, the linear relationship between x (trans fat) and y (calories) is positive and strong. Also, the points on the scatter diagram are scattered about the regression line. It was also determined that the line will be going up because “r” is positive.


Result 1: Simple Linear Regression I. Gibson   [Info]
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Result 2: Simple Linear Regression I. Gibson   [Info]
Simple linear regression results:
Dependent Variable: Calories
Independent Variable: Trans Fat (g)
Calories = 348.23866 + 204.00419 Trans Fat (g)
Sample size: 114
R (correlation coefficient) = 0.80146424
R-sq = 0.64234492
Estimate of error standard deviation: 147.21567

Parameter estimates:
ParameterEstimateStd. Err.AlternativeDFT-StatP-value
Intercept348.2386618.154472 ≠ 011219.181977<0.0001
Slope204.0041914.383949 ≠ 011214.182767<0.0001

Analysis of variance table for regression model:

Data set 1. Nutritional Data for Fast Food 2017 (I. Gibson)   [Info]
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<A href="">IGibson Project 3 (revised)</A>

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