Regression Statistics Multiple R R Square Adjusted R Square 0.186361 0.03473 -0.08593 Standard Error 4.867994 Observations 10 ANOVA df SS MS Regression 1 6.821053 6.821053 0.28784 Residual 8. 189.5789 23.69737 Total 196.4 Standard Coefficients Error t Stat P-value Intercept 147.3263 9.310343 15.82394 2.54E-07 X Variable 1 -0.18947 0.353161 -0.53651 0.606201
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.
Given the following information which compares the number of games a
the baseball team won and the number of runs for that team, answer the following questions.
Using the information to write the line of best fit, predict how many runs the
team might make if it plays 28 games.
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