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Is regression can be calculated with different scale of measurement of two variables?
Wiki User
∙ 13y ago
Yes.
Wiki User
∙ 13y ago
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What is Full Regression?
Regression :The average Linear or Non linear relationship between Variables.
What is the difference between the logistic regression and regular regression?
in general regression model the dependent variable is continuous and independent variable is discrete type. in genral regression model the variables are linearly related. in logistic regression model the response varaible must be categorical type. the relation ship between the response and explonatory variables is non-linear.
What is Meaning of Regression in Statistics?
It measures associations between variables.
What characteristic makes regression line of best fit?
The equation of the regression line is calculated so as to minimise the sum of the squares of the vertical distances between the observations and the line. The regression line represents the relationship between the variables if (and only if) that relationship is linear. The equation of this line ensures that the overall discrepancy between the actual observations and the predictions from the regression are minimised and, in that respect, the line is the best that can be fitted to the data set. Other criteria for measuring the overall discrepancy will result in different lines of best fit.
Can dummy variables be used in multiple linear regression analysis?
Yes they can.
What does one have to do before a regression analysis?
Before undertaking regression analysis, one must decide on which variables will be analysed. Regression analysis is predicting a variable from a number of other variables.
Simple regression and multiple regression?
Simple regression is used when there is one independent variable. With more independent variables, multiple regression is required.
What is Full Regression?
Regression :The average Linear or Non linear relationship between Variables.
What are explanatory variables in regression?
Explanatory (or independent) variables are variables such that changes in their value are thought to cause changes in the "dependent" variables.
What is the difference between the logistic regression and regular regression?
in general regression model the dependent variable is continuous and independent variable is discrete type. in genral regression model the variables are linearly related. in logistic regression model the response varaible must be categorical type. the relation ship between the response and explonatory variables is non-linear.
What is Meaning of Regression in Statistics?
It measures associations between variables.
Why are there two regression lines?
There are two regression lines if there are two variables - one line for the regression of the first variable on the second and another line for the regression of the second variable on the first. If there are n variables you can have n*(n-1) regression lines. With the least squares method, the first of two line focuses on the vertical distance between the points and the regression line whereas the second focuses on the horizontal distances.
What characteristic makes regression line of best fit?
The equation of the regression line is calculated so as to minimise the sum of the squares of the vertical distances between the observations and the line. The regression line represents the relationship between the variables if (and only if) that relationship is linear. The equation of this line ensures that the overall discrepancy between the actual observations and the predictions from the regression are minimised and, in that respect, the line is the best that can be fitted to the data set. Other criteria for measuring the overall discrepancy will result in different lines of best fit.
What is regression analysis?
In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables.
Difference between regression coefficient and correlation coefficient?
Regression coefficient measures the change in the dependent variable for a one-unit change in the independent variable, while correlation coefficient measures the strength and direction of the linear relationship between two variables. Regression coefficient is specific to the relationship between two variables in a regression model, while correlation coefficient is a general measure of association between two variables.
What is a regression analysis?
Regression analysis is a statistical technique to measure the degree of linear agreement in variations between two or more variables.
Can dummy variables be used in multiple linear regression analysis?
Yes they can.
