The production of wine is a​ multi-billion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine​ experts, data was collected from red wine variants from a particular type of foreign wine. A multiple linear regression model was developed from a sample of 55 wines. The model was used to predict wine​ quality, measured on a scale from 0​ (very bad) to 10​ (excellent) based on the alcohol content​ (%) and the amount of chlorides.  a. Construct a​ 95% confidence interval estimate of the population slope between wine quality and the percentage of alcohol. ​(Round to four decimal places as​ needed.)

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The production of wine is a​ multi-billion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine​ experts, data was collected from red wine variants from a particular type of foreign wine. A multiple linear regression model was developed from a sample of 55 wines. The model was used to predict wine​ quality, measured on a scale from 0​ (very bad) to 10​ (excellent) based on the alcohol content​ (%) and the amount of chlorides. 

a. Construct a​ 95% confidence interval estimate of the population slope between wine quality and the percentage of alcohol.

​(Round to four decimal places as​ needed.)

Standard
Variable
Coefficient
Error
t Statistic
p-value
0.1928
1.04548
Intercept
Alcohol, X,
Chlorides, X2
1.19502
0.87
0.35685
0.10228
3.49
0.0010
- 9.77305
3.50609
-2.79
0.0074
Transcribed Image Text:Standard Variable Coefficient Error t Statistic p-value 0.1928 1.04548 Intercept Alcohol, X, Chlorides, X2 1.19502 0.87 0.35685 0.10228 3.49 0.0010 - 9.77305 3.50609 -2.79 0.0074
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