After deciding on the appropriateness of a linear model relating coffee sales and maximum temperature, the managers calculate the equation of the least-squares regression line to be =y−2553.5211.33x . This is the line shown in the scatter plot above. Based on the sample data and the regression line, complete the following. (a)For these data, temperature values that are less than the mean of the temperature values tend to be paired with coffee sales values that are ▼(Choose one) the mean of the coffee sales values. (b)According to the regression equation, for an increase of one degree in temperature, there is a corresponding ▼(Choose one) of 11.33 dollars in coffee sales. (c)What was the observed coffee sales value (in dollars) when the temperature was 39.6 degrees Fahrenheit?
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.
After deciding on the appropriateness of a linear model relating coffee sales and maximum temperature, the managers calculate the equation of the least-squares regression line to be
. This is the line shown in the scatter plot above.
Based on the sample data and the regression line, complete the following.
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