Minitab Solution Interpretation for the Water/Temperature/Time
Mowing example.
The printout gives you more information than what is listed below. We will interpret more of the data later in the Multiple Regression Inferences Tutorial.
Regression Analysis
The regression equation is
Water Consumption = - 122 + 12.5 Time mowing + 1.51
Temperature
Predictor Coef StDev
T P
Constant -121.655
6.540 -18.60 0.000
Time mow 12.532
1.933 6.48 0.003
Temperat 1.51236
0.06077 24.89 0.000
Interpretation of the printout above:
Constant - This is referring to the y-intercept.
-121.655 is the value of water consumption when the temperature is zero. This means that a person would be expected to drink about -121.655 ounces of water when the temperature is zero and no time is spent mowing. 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.
Temperature - This is referring to the slope.
The slope is equal to 1.51 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 increase, you can predict an increase of 1.5 ounces in water consumption when the Time mowing is held constant.
Time mowing - This is also referring to the slope.
This slope is equal to 12.53. The slope is equal to (ounces of water)/(hours spent mowing). For our model, the interpretation of the slope is for each one hour spent mowing increase, you can predict an increase of 12.53 ounces in water consumption when the temperature is held constant.
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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