Using Im function fit the regression model. Write down the regression equation and answer. (Hints: you may need to check the ANOVA table, predicted values of parameters, R-square, residual plot). Y=?0 +?1? + ? = Call: lm(formula = RANGE ~ LAT, data = theData) Coefficients: (Intercept) LAT -6.4793 0.7515 Residual standard error: 5.498 on 43 degrees of freedom Multiple R-squared: 0.3886, Adjusted R-squared: 0.3744 F-statistic: 27.33 on 1 and 43 DF, p-value: 4.786e-06
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.
- Using Im
function fit the regression model. Write down the regression equation and answer. (Hints: you may need to check the ANOVA table, predicted values of parameters, R-square, residual plot).
Y=?0 +?1? + ? = Call:
lm(formula =
Coefficients:
(Intercept) LAT
-6.4793 0.7515
Residual standard error: 5.498 on 43 degrees of freedom
Multiple R-squared: 0.3886, Adjusted R-squared: 0.3744
F-statistic: 27.33 on 1 and 43 DF, p-value: 4.786e-06
We have given
Coefficients:
(Intercept) LAT
-6.4793 0.7515
Residual standard error: 5.498 on 43 degrees of freedom
Multiple R-squared: 0.3886, Adjusted R-squared: 0.3744
F-statistic: 27.33 on 1 and 43 DF, p-value: 4.786e-06
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