A pumpkin farmer wants to create a linear regression model to predict the circumference of a pumpkin (Y-variable) from its weight (X-variable). He samples 40 pumpkins from his pumpkin patch and the mean weight is 14 lbs with a standard deviation of 1 lb. The mean circumference is 50 inches with a standard deviation of 10 inches. The correlation between pumpkin weight and circumference is r = 0.50. What is the slope of the linear regression model predicting circumference from weight? 7 1 5 3
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.
A pumpkin farmer wants to create a linear regression model to predict the circumference of a pumpkin (Y-variable) from its weight (X-variable). He samples 40 pumpkins from his pumpkin patch and the mean weight is 14 lbs with a standard deviation of 1 lb. The mean circumference is 50 inches with a standard deviation of 10 inches. The
What is the slope of the linear regression model predicting circumference from weight?
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