The following table shows different prices of a product at certain weeks. x (Weeks) y (Price($)) 7 19.55 8 17.3 9 19.55 10 18.3 11 17.45 12 19.9 13 18.45 14 18 (a) Based on the data shown above, compute the correlation coefficient accurate to three decimal places. r=r= (b) Find the proportion of the variation in Price that can be explained by the variation in the values of Weeks. Report your answer as a percentage accurate to one decimal place. (Example: If the answer is 0.1234, you would enter 12.3 without the percent symbol.) r2=r2= %
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
| x (Weeks) | y (Price($)) |
|---|---|
| 7 | 19.55 |
| 8 | 17.3 |
| 9 | 19.55 |
| 10 | 18.3 |
| 11 | 17.45 |
| 12 | 19.9 |
| 13 | 18.45 |
| 14 | 18 |
(a) Based on the data shown above, compute the
r=r=
(b) Find the proportion of the variation in Price that can be explained by the variation in the values of Weeks.
Report your answer as a percentage accurate to one decimal place. (Example: If the answer is 0.1234, you would enter 12.3 without the percent symbol.)
r2=r2= %
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