Online clothes An online clothing retailer keeps trackof its customers’ purchases. For those customers who signed up for the company’s credit card, the com-pany also has information on the customer’s Age and Income. A random sample of 500 of these customers shows the following scatterplot of Total Yearly Pur-chases by Age:The correlation between Total Yearly Purchases and Age isr = 0.037. Summary statistics for the two variables are: a) What is the linear regression equation for predictingTotal Yearly Purchase from Age?b) Do the assumptions and conditions for regressionappear to be met?c) What is the predicted average Total Yearly Purchasefor an 18-year-old? For a 50-year-old? d) What percent of the variability in Total Yearly Pur-chases is accounted for by this model? e) Do you think the regression might be a useful one forthe company? Explain.
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.
of its customers’ purchases. For those customers who
pany also has information on the customer’s Age and
chases by Age:The
r = 0.037. Summary statistics for the two variables are:
Total Yearly Purchase from Age?
b) Do the assumptions and conditions for regression
appear to be met?
c) What is the predicted average Total Yearly Purchase
for an 18-year-old? For a 50-year-old?
chases is accounted for by this model?
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