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1. Text link: Linear regression - Wikipedia Domain: en.wikipedia.org Link: https://en.wikipedia.org/wiki/Linear_regression Description: The following are the major assumptions made by standard linear regression models with standard estimation techniques (e.g. ordinary least squares ): Weak exogeneity. This essentially means that the predictor variables x can be treated as fixed... Linearity. This means that the mean of the ... |
2. Text link: What is Linear Regression? - Statistics Solutions Domain: statisticssolutions.com Link: https://www.statisticssolutions.com/what-is-linear-regression/ Description: Linear regression is a basic and commonly used type of predictive analysis. The overall idea of regression is to examine two things: (1) does a set of predictor variables do a good job in predicting an outcome (dependent) variable? (2) Which variables in particular are … |
3. Text link: Simple linear regression - Wikipedia Domain: en.wikipedia.org Link: https://en.wikipedia.org/wiki/Simple_linear_regression Description: Simple linear regression. In statistics, simple linear regression is a linear regression model with a single explanatory variable. That is, it concerns two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system)... |
4. Text link: Introduction to Linear Regression - Free Statistics Book Domain: onlinestatbook.com Link: http://onlinestatbook.com/2/regression/intro.html Description: In simple linear regression, we predict scores on one variable from the scores on a second variable. The variable we are predicting is called the criterion variable and is referred to as Y. The variable we are basing our predictions on is called... |
5. Text link: Linear Regression - Yale University Domain: stat.yale.edu Link: http://www.stat.yale.edu/Courses/1997-98/101/linreg.htm Description: Linear Regression Example. The dataset "Televisions, Physicians, and Life Expectancy" contains, among other variables,... Outliers and Influential Observations. After a regression line has been computed for a group... Residuals. Once a regression model has been fit to a group of data,... Lurking ... |
6. Text link: Linear Regression - ibm.com Domain: ibm.com Link: https://www.ibm.com/support/knowledgecenter/en/SSLVMB_25.0.0/statistics_mainhelp_ddita/spss/base/idh_regs.html Description: Linear Regression estimates the coefficients of the linear equation, involving one or more independent variables, that best predict the value of the dependent variable. For example, you can try to predict a salesperson's total yearly sales (the dependent variable) from independent variables such as age, education, and years of experience. Example. |
7. Text link: Linear Regression — Detailed View – Towards Data Science Domain: towardsdatascience.com Link: https://towardsdatascience.com/linear-regression-detailed-view-ea73175f6e86 Description: Feb 26, 2018 · Linear regression is used for finding linear relationship between target and one or more predictors. There are two types of linear regression- Simple and Multiple. Simple linear regression is useful for finding relationship between two continuous variables. One is predictor or independent variable and other is response or dependent variable. |
8. Text link: Lesson 1: Simple Linear Regression | STAT 501 Domain: newonlinecourses.science.psu.edu Link: https://newonlinecourses.science.psu.edu/stat501/node/250/ Description: Simple linear regression is a statistical method that allows us to summarize and study relationships between two continuous (quantitative) variables. This lesson introduces the concept and basic procedures of simple linear regression. We will also learn two measures that describe the strength of the linear association that we find in data. |