Regression Statistics Multiple R 0.874642413 R Square 0.764999351 Adjusted R Square 0.744564512 Standard Error 62.97881926 Observations 51 ANOVA df MS Significance F Regression 4 593934.928 148483.732 37.43603514 6.36772E-14 Residual 46 182451.2571 3966.331676 Total 50 776386.1851 Coefficients Standard Error Upper 95% t Stat P-value Lower 95% Intercept 240.8002285 51.13392961 4.709206398 2.31605E-05 137.8729666 343.7274903 VEHICLE 3.042782981 1.582326221 1.922980824 0.06068593 -0.142274506 6.227840468 DIABETES 11.24212265 1.659066489 6.776173665 1.97533E-08 7.902595017 14.58165028 FLU 12.32304584 2.057012215 5.990749957 2.9897E-07 8. 182495007 16.46359668 HOMICIDE 1.362128456 2.113562817 0.644470297 0.522471501 -2.892252837 5.616509749
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 US government is interested in understanding what predicts death rates. They have a set of data that includes the number of deaths in each state, the number of deaths resulting from vehicle accidents (VEHICLE), the number of people dying from diabetes (DIABETES), the number of deaths related to the flu (FLU) and the number of homicide deaths (HOMICIDE). Your run a regression to predict deaths and get the following output:
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