a person should exercise per week (Y), given their age (x1) and the number of calories they eat per day (x2). After collecting data, the clinic is able to perform linear regression and discovers that the correct coefficient for the "age" variable is 13, the correct coefficient for the "calories per day" variable is 23, and the "constant" is-16. Given this information, what would the prediction equation look like to allow the clinic to predict the number of hours of exercise given age and calories? OY= -16x1 + 23x2 + 13 OY = 23 - 16x1 + 13x2 OY= -16 + 13x1+ 23x2 Y = -16 +23x1 + 13x2
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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