Wine Regression

In: Other Topics

Submitted By rerzen
Words 1758
Pages 8
Applied Regression Analysis
41100-81

Christian Hansen
Winter 2015

“I pledge my honor that I have not violated the Honor Code during this assignment.”

Kataras, Peter
Foltyn, Tom
Erzen, Robert
Scholl, Katie

In order to begin we first had to gain a high level understanding of the 6000 observations that we were given. We ran descriptive statistics on all of the original variables after transforming the variable Color into a dummy variable called White (White Wine=1, Red wine=0). Descriptive Statistics | | N | Minimum | Maximum | Mean | Std. Deviation | quality | 6000 | 2.5000 | 9.5000 | 5.825317 | .9206965 | fixed_acidity | 6000 | 3.8000 | 15.9000 | 7.221233 | 1.3094165 | volatile_acidity | 6000 | .0800 | 1.5800 | .340727 | .1653986 | citric_acid | 6000 | .0000 | 1.6600 | .318008 | .1455540 | residual_sugar | 6000 | .6000 | 65.8000 | 5.425650 | 4.7411670 | chlorides | 6000 | .0100 | .6100 | .056483 | .0344872 | free_sulfur_dioxide | 6000 | 1.0 | 289.0 | 30.482 | 17.7550 | total_sulfur_dioxide | 6000 | 6.0 | 440.0 | 115.576 | 56.5940 | density | 6000 | .99 | 1.04 | .9949 | .00504 | pH | 6000 | 2.74 | 4.01 | 3.2195 | .16022 | sulphates | 6000 | .2200 | 2.0000 | .532073 | .1487300 | alcohol | 6000 | 8.0000 | 14.9000 | 10.491008 | 1.1901957 | White | 6000 | 0 | 1 | .75 | .433 |

Some of our variables in the dataset have very tight ranges, for example density has a min of .99 and a max of 1.04. On the other hand, total sulfur dioxide has a range of 6 to 440 and a standard deviation of 56.6, with the max value being over 5 standard deviations from the mean.
In order to get a sense of the overall dataset, we ran a regression of all of the original variables with the dependent variable of quantity. Below are the outputs of the regression (Potential Model 1):

Potential Model 1 Summary | R Square | Adjusted R Square |…...

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