The following table shows the average annual income in a certain country, adjusted for inflation, for the given year. t = years since 1980 I = annual income 0 $23,009 5 $23,216 10 $25,184 15 $26,694 20 $30,619 25 $30,250 30 $28,838 (a) Find the equation of the regression line. (Round regression line parameters to two decimal places.) I(t) = 22863.21+266.36t (b) Plot the data along with the regression line. (c) Explain in practical terms the meaning of the slope of the regression equation. (Round your answers to two decimal places.) The slope of the regression line is dollars per year. The slope means that, from 1980 on, the average annual income (adjusted for inflation) grew by $ each year. (d) During which year since 1990 was income much lower than would be expected from the regression model? 1995 2000 2005 2010
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 1980 | I = annual income |
---|---|
0 | $23,009 |
5 | $23,216 |
10 | $25,184 |
15 | $26,694 |
20 | $30,619 |
25 | $30,250 |
30 | $28,838 |
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