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Instructions from my professor ** VERY IMPORTANT** Python Script: To complete t

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Instructions from my professor ** VERY IMPORTANT**
Python Script: To complete the tasks listed below,
open the Project Three Jupyter Notebook link in the Assignment
Information module. This notebook contains your data set and the Python
scripts for your project. In the notebook, you will find step-by-step
instructions and code blocks that will help you complete the following
tasks:
Simple Linear Regression
Create scatterplots
Compute the correlation coefficient
Conduct a linear regression
Multiple Regression
Create scatterplots
Compute the correlation matrix
Conduct a multiple regression analysis
Summary Report: Once you have completed all the
steps in your Python script, you will create a summary report to present
your findings. Use the provided template to create your report. You
must complete each of the following sections:
Introduction: Set the context for your scenario and the analyses you will be performing.
Scatterplots and Correlation: Discuss relationships between variables using scatterplots and correlation coefficients.
Simple Linear Regression: Create a simple linear regression model to predict the response variable.
Multiple Regression: Create a multiple regression model to predict the response variable.
Conclusion: Summarize your findings and explain their practical implications.
Section 2
Python Script: Hypothesis Testing. Highest level is proficient here and this means that there are no errors in your script.
Summary Report: Simple Linear Regression Correlation. This covers part 3 of the template.
Naturally answer all of the bullets in the templates 🙂
Major Things to Look Out For:
INCLUDE THE SCATTERPLOT and address the following by looking at the graph:
Describe the strength of
the association seen in the graph eye-balling closeness to
straight-line (strong, moderate, weak) as an indication of how strong
the relationship is
Describe the direction of the association seen in the graph as positive (as x increase y tends to increase) or negative (as x increases, y tends to decrease)
Is the trend (strength and direction discussed above) what you expected to see?
Include the output from Python showing the r value. Discuss:
Strength (strong, moderate, weak) based on closeness to +1 or -1 using the cut-offs shown in your text Table 5.3.1
Direction (positive or negative) based on the sign of the r value
For
the correlation test, be sure to include all elements including Ho/Ha
for testing as I showed in the General Questions>Module 5
Questions>For Discussion: The Scatterplot & Correlation Coefficient thread (scroll to end of post where I reference the project). Also review Zybooks 5.3 and scroll down to t-test for the population correlation coefficient
Summary Report: Simple Linear Regression Model. This covers part 4 of the template.
Of course answer ALL bulleted questions
NOTE: If you start a study using a
specific significance level (say the 0.01 given in part 3 of the
template), when you go to run the hypothesis test, you stick with the
original alpha. That is, don’t change to 0.05 in part 4 which is a
continuation of part 3.
If you do not know how to use
equation editor in word to write your Ho/Ha appropriately, please search
YouTube for Equation Editor and whatever system you’re using. Here’s
one for windows or if you want to get fancy here.
Include the hat notation when writing
your line as you did in discussion 5 and related posted examples in
General Questions>Module Five Questions examples.
Include all elements of the hypothesis test for
as we did in week 5 discussion BUT you must do the F-test instead of the t-test that we did.
Show ALL working when you’re doing
your prediction. That is, show the actual plugging in of the X values
into plugging into regression line you generated being sure to note the
rounding rules stated in the template.
Summary Report: Multiple Regression Correlation. This covers part 5 of the template.
Same tips as for #2 above
Summary Report: Multiple Regression Model. This covers parts 6 & 7 of the template.
Similar comments to #3 above except
now we’re moving into what we covered in Module 6 & 7 so be sure to
check those General Questions threads for examples, as well as reviewing
your discussion posts
For your coefficient of determination (
) interpretation, don’t forget that we first encountered this in Section 5.3 of Module 5
Of course, check include all steps for the Overall F-test as shown in our module 7 examples and Zybooks 7.2 section (scroll down to Overall F-Test)
For EACH slope’s individual t-test, be sure that you include all elements to test each
as shown in Zybooks 7.2 section (scroll down to Overall F-Test)
Be sure to include
Ho/Ha
Test Statistic
P-value
Conclusion: Example: There is/isn’t sufficient evidence at the 0.01 level that the Average Points slope is statistically significant.
Summary Report: Intro & Conclusions. This covers parts 1, 2 and 8 of the template.
Address all bullets
Be sure to
address ALL analyses by name (example, exploratory scatterplot and
correlation analysis of total number of wins and average points scored).
IMPORTANT:
Part 2 calls for more details than was expected in previous projects.
You are NOT to simply copy/paste the generic variable names. You must
expand/explain it to a lay person so it’s clear that you understand what
these variables mean.

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