Simple Linear Regression (Statistics)

Simple Linear Regression is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
This lecture discusses simple linear regression models that use a single numerical independent variable, X, to predict the numerical dependent variable, Y. In this lecture, you will learn regression analysis techniques that help uncover relationships between variables. regression analysis leads to selection of a model that expresses how one or more independent variables can be used to predict the value of another variable, called the dependent variable. regression models identify the type of mathematical relationship that exists between a dependent variable and an independent variable, thereby enabling you to quantify the effect that a change in the independent variable has on the dependent variable. Models also help you identify unusual values that may be outliers

Learning objectives:

• How to use regression analysis to predict the value of a dependent variable based on a value of an independent variable
• The meaning of the regression coefficients b0 and b1
• How to evaluate the assumptions of regression analysis and know what to do if the assumptions are violated
• To make inferences about the slope and correlation coefficient
• To estimate mean values and predict individual values

In this File you will find:

Simple Linear Regression Lecture Power Point Presentation
Test Bank for Simple Linear Regression with 213 Questions with all answers to them
86 Exercises for Simple Linear Regression seminar or lecture
Plus reading resource on Simple Linear Regression in order to enhance you overall knowledge about the topic.

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