Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold on as the response variable. The least squares regression (LSR) line for the data is ?̂ =−135.99+2.46?y^=−135.99+2.46x. On one of the observed days, the temperature was 82 °F82 °F and 70 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, ?̂ y^, when the temperature is 82 °F.82 °F. Enter your answer as a whole number, rounding if necessary. ?̂ = ? ice bags Using the predicted value you just found, compute the residual at this temperature. residual= ? ice bags
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.
Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold on as the response variable. The least squares regression (LSR) line for the data is ?̂ =−135.99+2.46?y^=−135.99+2.46x.
On one of the observed days, the temperature was 82 °F82 °F and 70 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, ?̂ y^, when the temperature is 82 °F.82 °F. Enter your answer as a whole number, rounding if necessary.
?̂ = ? ice bags
Trending now
This is a popular solution!
Step by step
Solved in 4 steps
