correlation What are properties of a regression line? What is error in regression? How do you calculate standard error?
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.
- What are properties of a regression line?
- What is error in regression?
- How do you calculate standard error?
Regression Analysis: It is a method for the estimation of relationships between a response variable (y) and one or more explanatory variables (x). This method enables us to determine which variables matter most and which can be ignored, and also determines how these factors influence each other.
Regression line: It is a line that describes how a response variable y behaves due to a change in explanatory variable x.Generally, we use the regression line to predict the value of y for a given value of x. In other words, we can say that the regression line is the line that best fits the data. And it is defined as follows:
y=a+bx
where, y= response variable
x= explanatory variables
a= intercept term
b= slope parameter
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