Year 1980 1985 1990 1995 Individual, x 288 397 540 676 Business, y 72 77 110 174 Year 2000 2005 2010 2015 Individual, x 1137 1108 1164 1760 Business, y 236 307 278 390
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 table shows the gross income tax collections (in billions of dollars) by the Internal Revenue Service for individuals x and businesses y for selected years. (a) Use the regression capabilities of a graphing utility to find the least squares regression line for the data. (b) Use the model to estimate the business income taxes collected when the individual income taxes collected is $1300 billion. (c) In 1975, the individual income taxes collected was $156 billion and the business income taxes collected was $46 billion. Describe how including this information would affect the model.
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