# QNT 275 Week 4 participation Final Exam Review

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QNT 275 Week 4 participation Final Exam Review

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# QNT 275 Week 4 participation Final Exam Review

Week 4 Practice Problem #1

Team

Below is a problem that you may see on the Final Exam or the Quiz:

Which of the following violates the assumptions of regression analysis?

*The error term does not have the normal distribution.*

- The error term has a constant variance.

- The error term is uncorrelated with an explanatory variable.

- The error term has a zero mean.

I chose the 1st option because there are 4 assumptions of Regression Analysis and the 1st option does not align to the 4 assumptions:

- There is a linear relationship between the Independent and the Dependent Variable

- There is a statistical indepedendence of errors

- Homoscedasticity of the errors which means there is a constant variance

- The Error
follow the Normal Distribution*does*

What does the term Homoscedasticity mean?

Week 4 Practice Problem #2

Team

Below is a problem that you may see on the Final Exam or on the Quiz

In the sample regression equation what is ?

- The value of
*y*when*x*= 0

- The
*y*-intercept

*The predicted value of y, given a specific x value*

- The slope of the equation

Why would I have chosen the 3rd option? What is the relationship between X (the Independent Variable) and Y (the Dependent Variable)?

**Week 4 Practice Problem #3**

Team

Below is a problem that you may see on the Final or on the Quiz

What type of relationship is indicated in the scatterplot?

*A positive linear or curvilinear relationship*

- A negative linear relationship

- No relationship

- A negative curvilinear relationship

I picked the 1st option, because a positive relationship is illustrated on a Scatter Plot when the data points move from the bottom left to the upper right. What would a Negative Relationship look like if it was illustrated?

Week 4 Practice Problem #4

Team

Below is a problem that you may see on the Final or on the Quiz:

Serial correlation is typically observed in:

- sparse data

- cross-sectional data

*time series data*

- outliers

Why would I have selected Time Series Data?

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