The formula for a regression line is y=a+bx For the regression equation shown below (assume values in US$) average monthly sales=126+172 advertising cost Which among the following statements is/are true? (a) for every increase of $1.00 in advertising cost, the expected average monthly sales are predicted to increase by $172.00 (b) for every increase of $1.00 in advertising cost, the expected average monthly sales are predicted to increase by $126.00 (c) this linear regression has positive relationship on business (d) this linear regression has negative relationship on business (e) this linear regression has no relationship on business O statements (b) and (c) are true O only statement (a) is true O statements (a) and (c) are true O only statement (b) is true O only statement (e) is true
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.
Step by step
Solved in 2 steps