A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression equation of the least squares line is ŷ = 3 + 1x. EX= 24 EX = 124 EY= 42 EY = 338 EXY = 196 MSE = 4 Using the sums of the squares given above, determine the 90 percent confidence interval for the mean value of monthly tire sales when the advertising expenditure is $5.000. distance value = .20238 a. (6.08, 9.92) b. (3.235, 6.765) c. (2.465, 6.853) d. (5.325, 7.675)
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.
A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression equation of the least squares line is ŷ = 3 + 1x.
EX= 24
EX = 124
EY= 42
EY = 338
EXY = 196
MSE = 4
Using the sums of the squares given above, determine the 90 percent confidence interval for the mean value of monthly tire sales when the advertising expenditure is $5.000.
distance value = .20238
a. (6.08, 9.92)
b. (3.235, 6.765)
c. (2.465, 6.853)
d. (5.325, 7.675)
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