A researcher took a random sample of beef hotdogs and measured the amount of sodium (in mg) and calories contained in them. The results of a correlation and regression analysis are shown in the tables below: Correlation: Calories, Sodium Content Matrix Plot of Calories, Sodium Pearson Correlation 600 500 400 300 r = 0.946 p = 0.001 150 160 170 180 190 Calories Pairwise Pearson Correlations Sample 1 Sample 2 N Correlation 95% CI for p P-Value Sodium Calories 7 0.946 (0.670, 0.992) 0.001 Regression Analysis Durbin-Watson Statistic Durbin-Watson Statistic = 2.18902 Sodium
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.
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