The purpose of this assignment is to create a one-page poster that would help an uninformed reader to become acquainted with linear regression. The assignment can be done individually, or in small...

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The purpose of this assignment is to create a one-page poster that would help an uninformed reader to become acquainted with linear regression. The assignment can be done individually, or in small groups (up to 5-6 students).





Use multi-column format, small fonts, and tight spacing between the lines. For sample posters, check the galleryhttps://www.nvidia.com/gtc/poster-gallery/ai-and-deep-learning/





Include formulas and illustrations. Reference sources for all materials using traceable links. Use academic sources, such as web pages of university statistics departments, published peer-reviewed papers and books.





Submit to this dropbox in machine-readable Word or PDF format by the end of 27 October.





Possible plan for the poster:





1. Motivation (why is the linear regression needed)

2. How is the linear regression calculated

3. Interpretation of the linear regression results

4. Example(s) of use of linear regression

5. Advantages of linear regression

6. Disadvantages of linear regression

7. In what situations is linear regression a suitable method

8. In what situations is linear regression not a suitable method

9. Alternatives to linear regression
Answered 2 days AfterOct 25, 2022

Answer To: The purpose of this assignment is to create a one-page poster that would help an uninformed reader...

Mukesh answered on Oct 27 2022
47 Votes
1. Motivation (why is the linear regression needed)
Answer-
The linear regression analysis estimates the value of one variab
le based on the value of another variable. The variable we want to predict is known as target variable or dependent variable and the variables used to predict our target variable are called explanatory variables.
This type of analysis determines the coefficients of the linear equation by applying one or more explanatory variables that could most accurately predict the value of the target variable. The linear regression method reduces the mismatch between the predicted and observed output values by fitting a line or surface. In linear regression, the "least squares" technique is used to obtain the best-fit line for a collection of data. You then estimate the value of X (the explanatory variables) using Y. (target variable).
Equation of linear Regression given as
where, y = estimated dependent variable,
    β0 is the Intercept,
    β1 is the Slope,
and     x is independent variable.
2. How is the linear regression calculated
Answer-
The regression line's slope is ß1, and its y-intercept is ß0. The intercept (β0) and slope (β1) of the equation are calculated by the formulas below.
3. Interpretation of the linear regression...
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