Minitab Solution Interpretation for the Water/Temperature example.
* The printout gives you more information than what is listed below. We will interpret more of the data later in the rest of the tutorial.*
Regression Analysis
The regression equation is
Water Consumption = - 96.8 + 1.45 Temperature
Predictor
Coef StDev
T P
Constant
-96.85
16.09 -6.02 0.002
Temperat
1.4512
0.1821 7.97
0.001
S = 3.777 R-Sq = 92.7% R-Sq(adj) = 91.2%
Interpretation of the printout above:
Constant - This is referring to the y-intercept.
-96.85 is the value of water consumption when the temperature is zero. This means that a person would be expected to drink about -97 ounces of water when the temperature is zero. Therefore our model is not applicable around x=0. Our data was taken in the summer time when the temperatures ranged from 75 to 99 degrees Fahrenheit so our model only predicts for temperatures approximately in that range.
Temperat - This is referring to the slope.
The slope is equal to 1.4512 or approximately 1.5. The slope is equal to (ounces of water)/(degrees F). For our model, the interpretation of the slope is for each one degree F increases, you can predict an increase of 1.5 ounces in water consumption.
R-Sq = 92.7%
In our model, the r-sq interpretation is that almost 93% of the variability in the amount of water consumed is explained by the temperature outside.
For this model, the slope and y-intercept can be easily identified by the regression equation Water Consumption = -96.8 + 1.45 Temperature.
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