Simple Linear Regression Analysis ( A Complete Course )
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Simple Linear Regression Analysis ( A Complete Course )

Course covers everything that Statistics students want to gain from regression analysis
4.0 (6 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
818 students enrolled
Created by Alia Mubashir
Last updated 4/2017
English
Current price: $10 Original price: $200 Discount: 95% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 1.5 hours on-demand video
  • 5 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Regression Analysis
  • Examples of Regression
  • Examples with Interpretation
  • Graphic Explanation
  • Properties of Regression analysis
  • Standard Error of Estimate
  • Coefficient of determination
  • Interpretation of coefficient of determination
  • Prediction in regression analysis
  • Interpolation vs Extrapolation
  • Properties of coefficient of correlation
  • Relationship between Coefficient of Correlation , Determination and S.E
  • Test the significance of coefficient of correlation
  • Testing of hypothesis about regression coefficient
  • Examples of testing of hypothesis about regreession coefficient
  • F.test for slope
  • Confidence interval and prediction interval
  • Examples of confiddence interval and prediction interval
  • Learn the theoratically and numerically concepts of Regression
  • How to calculate numericals of Regression
  • Explained Variations , The Format for ANOVA table
  • Correlation and Causation
  • Co-variance
  • Total Variation, Explained Variation and Unexplained Variation
  • Also include downloadable material in the form of PDF files . Each section consists of PDF Files
View Curriculum
Requirements
  • An Open Mind and Commitment
  • Interest in Statistics
  • Basic knowledge of statistics
Description

Welcome to the course on "Simple Linear Regression Analysis ( A Complete Course )" This course covers running and evaluating linear regression models (simple linear regression) including assessing the overall quality of models and interpreting individual predictors for significance with PDF files and complete exercises that consists of examples and concepts . We also explore R-Square in depth, including how to interpret R-Square for significance. Together with in-depth coverage of simple regression, we'll also explore correlation, which is closely related to regression analysis. By the end of this course you will be skilled in running and interpreting your own linear regression analyses, as well as critically evaluating the work of others. Lectures provided in HD video .While you can be confident that you are getting accurate information with Quantitative Specialists,

You will Learn

  • Standard Error of Estimate
  • Coefficient of determination
  • Interpretation of coefficient of determination
  • Relationship between Coefficient of Correlation , Determination and S.E
  • Test the significance of coefficient of correlation
  • Testing of hypothesis about regression coefficient
  • Examples of testing of hypothesis about regreession coefficient
  • F-test for slope and many more concepts.
  • Also downloadable material .

we also make it our highest priority in creating crystal-clear, easy-to-follow videos. Be confused by regression no longer -- Enroll Today!


Who is the target audience?
  • Statistics Students can take this course
  • Who want to learn Regression Analysis
  • Students taking a Statistics course that need some extra help.
  • Accounting Students
  • Finance Students
  • This course is ideal for those who have interest in learning
Compare to Other Regression Analysis Courses
Curriculum For This Course
29 Lectures
01:19:03
+
Introduction to course
1 Lecture 01:47
+
Basic Concepts of Simple Linear Regression Model with terminologies and Examples
4 Lectures 13:06

The least squares principle is a criterion for fitting a specified model to observed data such that the sum of squares of the residuals (difference between observed and estimate value) is minimized? in detail.

The estimated model can be written?
Regression Analysis
03:01

Quiz
1 question

  • Determine the regression equation.
  • Determine the value of....... when X is....?
Examples of Regression Analysis
06:03

Examples with Interpretation
03:38

Quiz
1 question

Here you can Download PDF Files that consists of Examples and Exercise

Get PDF File ( For More Practice )
00:24
+
Properties of Regression analysis , Prediction , Graphic Explanation , Etc
4 Lectures 09:46
Graphic Explanation
03:35

Properties of Regression analysis
01:41

Quiz
1 question

Total Variation, Explained Variation and Unexplained Variation


A measure of the variation of the actual values of the dependent variable from the estimated values of that variable?

Symbolically,

Sum of squares of residual.......... ?

Total Variation, Explained Variation and Unexplained Variation
01:49

Prediction in Regression Analysis

Here we will discuss how we may use a regression line to summarize the pattern but we will put less confidence in prediction based on the line.

Prediction in regression analysis
02:41
+
Intermediate concepts of Simple Linear Regression Model
5 Lectures 22:13
Standard Error of Estimate
06:44

Coefficient of determination
05:16

Quiz
1 question

  • Estimate the regression line of sales on price and interpret the results?
  • What is the part of the variation in sales which is not explained by the regression line?
  • Calculate coefficient of determination and standard error of estimate.?


Interpretation of coefficient of determination
05:22

Get PDF File ( For Additional Help )
00:24

Correlation Analysis

Pearson’s Product Moment Correlation Coefficient:

Pearson’s product moment correlation coefficient, usually denoted by r, is one example of a correlation coefficient. It is a measure of the linear association ....................?

Preview 04:27

Quiz
1 question
+
Properties of coefficient of correlation , Relationship between Coefficient Etc
5 Lectures 09:56
Properties of coefficient of correlation
02:12

Correlation and Causation
01:02

The Relationship among the Coefficient of Correlation, the Coefficient of Determination and the S.E of Estimate:

Sum of square of regression =S.S.R =Regression=Explained variation........?

.............?

Preview 04:21

Quiz
2 questions

Get PDF File ( For More Practice )
00:24

Interpolation Verses Extrapolation:

We will learn how Interpolation is the process of finding the value of the response variable Y for a given value of the explanatory variable X which lies within its given range of values. Whereas extrapolation is the......................................?

Interpolation vs Extrapolation
01:57
+
Testing of Hypothesis about Regression Coefficient , ANOVA Table and F.Test Etc
5 Lectures 14:39
Test the significance of coefficient of correlation
05:27

Inferences about the Slope Coefficient:

The inferences about the regression coefficient can be made by t−test for the slope and F−test for the slope.

Testing Hypotheses about Regression Coefficient

Testing of hypothesis about regression coefficient
02:21


Quiz
1 question

  • Complete the ANOVA table.
  • How large was the sample.
  • Determine the standard error of estimate.
  • Determine the coefficient determination.
The format for ANOVA table
02:04

F−test for Slope:

The ANOVA F−test can be used to test the null hypothesis H0: β =0 that Y is not linearly related of X in a regression equation......?

The variation can be measured by sum of squared deviations .

F.test for slope
02:08
+
Confidence interval and prediction interval , Examples of confiddence in......??
5 Lectures 07:36
Get PDF File ( For More Practice )
00:24

Able to learn what is the predicted value for any selected X value.?

X is any selected value of X.

X̅ is the mean of the Xs found by ∑ X/n

n is the number of observations?

sy. x is the standard error of estimate.?

t is the value of t with n−2 degrees of freedom.? and many more

Confidence interval and prediction interval
01:52

Examples of confiddence interval and prediction interval
02:46

Quiz
1 question

Co-variance
02:10

Complete Exercise ( Download PDF file )
00:24
About the Instructor
Alia Mubashir
2.4 Average rating
103 Reviews
7,974 Students
72 Courses
Instructor at Udemy

I have Specialization in Statistics , Finance and also teach Economics , Statistics and Mathematics to students in an academy and now I have started to teach online . I also hold

  1. Studied in Statistics and Finance from Punjab University
  2. I also hold Diplomas in Office Productivity and many Softwares
  3. Post Graduate Diploma in Business Administration and Finance.
  4. Bachelors in Science from Post Graduate College .
  5. Also hold diplomas in fashion , make up , beauty and cosmatics

Now I want to teach online and I'm very passionate about it.

I teach Economics, Mathematics, Statistics, Finance and English. Now i'm creating courses online in all these subjects.

Enroll today, create change, and be amazing!