For this exercise, round all regression parameters to three decimal places. The following table shows the number† P of design patents awarded by the U.S. Patent and Trademark Office from 1950 through 2010. t = years since 1950 P = patents 0 4718 10 2543 20 3214 30 3949 40 8024 50 17,413 60 22,799 c) In what years were there more patents awarded than might be expected from the model? (Enter your answers as a comma-separated list.)
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.
| t = years since 1950 | P = patents |
|---|---|
| 0 | 4718 |
| 10 | 2543 |
| 20 | 3214 |
| 30 | 3949 |
| 40 | 8024 |
| 50 | 17,413 |
| 60 | 22,799 |
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