Describe multiple regression?
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.
Describe multiple regression?
Regression analysis enables the inference or prediction of a variable from one or more other variables.
The value is predicted using the multiple linear regression equation when there is just one dependent variable and several independent variables. Let Y be the dependent variable and X1 and X2 be the two independent variables. The equation for multiple regression is stated as:
where is y-intercept and are the slope coefficients for each independent variable. The independent variable can be continuous or categorical.
Y is the response variable and all x's variables are called predictors or explanatory variables.
Example:
It has been noted that sales of cold beverages peak in the summer and progressively decline throughout the other monsoon seasons. For six months, a researcher chooses to examine how cold drinks compare to other soft drinks. He then noticed that during the hot summer months of June and July, all brands of cold drinks quickly sold out. Several independent factors, such as "weather, addiction, and age groups," serve as the parameters for the dependent variable's rise in sales. He draws 80 participants from a random sample of all ages to see whether age groups have an impact on the sales of cold drinks. Use the ANOVA test to determine if the age group is statistically significant or not.
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