Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. We used linear regression to explore the relationship between the number of calories and amount of carbohydrates (in grams) Starbucks food menu items contain. The estimated regression equation with carbohydrates as the response variable and the calories as the explanatory variable is ŷ = 8.94 + 0.11x, and summary statistics of the two variables is provided below. variable min Q1 median Q3 max mean sd n missing calories 80 300 350 420 500 338.8 105.4 77 carbohydrates 16 31 45 59 80 44.9 16.6 77
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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