The following table shows retail sales in drug stores in billions of dollars in the U.S. for years since 1995. Year Retail Sales 0 85.851 3 108.426 6 141.781 9 169.256 12 202.297 15 222.266 Let S(t) be the retails sales in billions of dollars in t years since 1995. A linear model for the data is F(t)=9.44t+84.182F(t)=9.44t+84.182. Estimate the retails sales in the U. S. in 2016. In billions of dollars. Use the model to predict the year in which retails sales will be $243 billion.
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.
The following table shows retail sales in drug stores in billions of dollars in the U.S. for years since 1995.
| Year | Retail Sales |
|---|---|
| 0 | 85.851 |
| 3 | 108.426 |
| 6 | 141.781 |
| 9 | 169.256 |
| 12 | 202.297 |
| 15 | 222.266 |
Let S(t) be the retails sales in billions of dollars in t years since 1995. A linear model for the data is F(t)=9.44t+84.182F(t)=9.44t+84.182.
Estimate the retails sales in the U. S. in 2016. In billions of dollars.
Use the model to predict the year in which retails sales will be $243 billion.
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