The production of wine is a multibilion-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 of a certain type of wine. A sample of 12 wines is given. Develop a simple linear regression model to predict wine quality, measured on a scale from 0 (very bad) to 10 (excellent), based on alcohol content (%). Complete parts (a) through (d) below. E Click the icon to view the data of wine quality and alcohol content. a. Construct a scatter plot. Choose the correct graph below. OA. OB. Oc. OD. Q Alcohol Content () Aloohol Content (%) b. For these data, b, = 1.8 and b, = 0.5. Interpret the meaning of the slope, b,. in this problem. Choose the correct answer below. O A. The slope, b, implies that for each 0.5 percentage decrease in alcohol content, the wine should have an increase in its rating by 1. O B. The slope, b,, implies that the alcohol content is equal to the value of b,. in percentages. OC. The slope, b, implies that for each increase of 1 wine quality rating, the alcohol content is expected to increase by the value of b,, in percentages. O D. The slope, b,, implies that for each increase of alcohol percentage of 1.0, the wine quality rating is expected to increase by the value of b, c. Predict the mean wine quality for wines with an 11% alcohol content 9, = (Round to two decimal places needed.) d. What conclusion can you reach based on the results of (a)-(c)? O A. Alcohol percentage appears to be affected by the wine quality. Each increase of 1 in quality leads to a mean increase in alcohol of about 1.8. O B. Wine quality appears to be affected by the alcohol percentage. Each increase of 1% in alcohol leads to a mean increase in wine quality of about 1.8. OC. Wine quality appears to be affected by the alcohol percentage. Each increase of 1% in alcohol leads to a mean increase in wine quality of about 0.5 OD. Alcohol percentage appears to be affected by the wine quality. Each increase of 1 in quality leads to a mean increase in alcohol of about 0.5.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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