Identify the variable(s) that are significantly correlated with loyalty.

Predict customer loyalty.
1. Run a correlation matrix on the relevant variables (that you predict loyalty). Identify the variable(s) that are significantly correlated with loyalty.
2. Next run a regression to predict customer loyalty with the significant variable(s), if the variable(s) makes sense as predictors of loyalty.
A) Explanation of test and sought after results
B) State hypotheses for each test,
C) Interpret the statistical findings (test results), and
D) Explain your findings in plain language (Non-statistical explanation).
Use nike data complete for analysis-1.sav ATTACHED**
VIEW ATTACHED EXAMPLE FOR FORMAT***.
Show the output

The assignment is to post a descriiption, in your own words, of a concept or idea from chapter 8.

Chapter 8 Vocabulary Discussion
The assignment is to post a descriiption, in your own words, of a concept or idea from Chapter 8. Please also include an example with a calculation.
Be careful not to copy directly from any source you may find. The idea is to try to convince others that you know what you are writing about.

Discuss how you determine the direction of the association between the two variables.

Recall that samples are used to generate a statistic, which businesses use to estimate the population parameter. You have learned how to take samples from populations and use them to produce statistics. For two quantitative variables, businesses can use scatterplots and the correlation coefficient to explore a potential linear relationship. Furthermore, they can quantify the relationship in a regression equation.
Prompt
This assignment picks up where the Module Two assignment left off and will use components of that assignment as a foundation.
You have submitted your initial analysis to the sales team at D.M. Pan Real Estate Company. You will continue your analysis of the provided Real Estate Data Spreadsheet spreadsheet using your selected region to complete your analysis. You may refer back to the initial report you developed in the Module Two Assignment Template to continue the work. This document and the National Summary Statistics and Graphs Real Estate Data PDF spreadsheet will support your work on the assignment.
Note: In the report you prepare for the sales team, the dependent, or response, variable (y) should be the listing price and the independent, or predictor, variable (x) should be the square feet.
Using the Module Three Assignment Template Word Document, specifically address the following:
Regression Equation: Provide the regression equation for the line of best fit using the scatterplot from the Module Two assignment.
Determine r: Determine r and what it means. (What is the relationship between the variables?)
Determine the strength of the correlation (weak, moderate, or strong).
Discuss how you determine the direction of the association between the two variables.
Is there a positive or negative association?
What do you see as the direction of the correlation?
Examine the Slope and Intercepts: Examine the slope and intercept .
Draw conclusions from the slope and intercept in the context of this problem.
Does the intercept make sense based on your observation of the line of best fit?
Determine the value of the land only.
Note: You can assume, when the square footage of the house is zero, that the price is the value of just the land. This happens when x=0, which is the y-intercept. Does this value make sense in context?
Determine the R-squared Coefficient: Determine the R-squared value.
Discuss what R-squared means in the context of this analysis.
Conclusions: Reflect on the Relationship: Reflect on the relationship between square feet and sales price by answering the following questions:
Is the square footage for homes in your selected region different than for homes overall in the United States?
For every 100 square feet, how much does the price go up (i.e., can you use slope to help identify price changes)?
What square footage range would the graph be best used for?
Criteria Exemplary Proficient Needs Improvement Not Evident Value
Regression Equation N/A Provides the regression equation for the line of best fit (100%) Shows progress toward proficiency, but with errors or omissions; areas for improvement may include an inaccurate equation (55%) Does not attempt criterion (0%) 10
Determine r Exceeds proficiency in an exceptionally clear manner (100%) Describes the direction, strength of correlation, and association between the variables (85%) Shows progress toward proficiency, but with errors or omissions; areas for improvement may include missing one or more of the following: direction, strength of correlation, or association between the variables (55%) Does not attempt criterion (0%) 20
Examine the Slope and Intercept Exceeds proficiency in an exceptionally clear manner (100%) Draws conclusions from the slope and intercept in context, makes predictions, determines the value of only the land (85%) Shows progress toward proficiency, but with errors or omissions; areas for improvement may include missing one or more of the following: conclusions from the slope and intercept in context, predictions, or the value of only the land (55%) Does not attempt criterion (0%) 20
Determine the R-squared Coefficient Exceeds proficiency in an exceptionally clear manner (100%) Determines the R-squared coefficient and explains it in context (85%) Shows progress toward proficiency, but with errors or omissions; areas for improvement may include an inaccurate determination of the R-squared coefficient or an explanation that is out of context (55%) Does not attempt criterion (0%) 20]
Conclusions: Reflect on the Relationship Exceeds proficiency in an exceptionally clear, insightful, or sophisticated manner (100%) Reflects on the relationship between square feet and sales price (85%) Shows progress toward proficiency, but with errors or omissions; areas for improvement may include a reflection on the relationship between variables that is missing components (55%) Does not attempt criterion (0%) 20
Articulation of Response Exceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative manner (100%) Clearly conveys meaning with correct grammar, sentence structure, and spelling, demonstrating an understanding of audience and purpose (85%) Shows progress toward proficiency, but with errors in grammar, sentence structure, and spelling, negatively impacting readability (55%) Submission has critical errors in grammar, sentence structure, and spelling, preventing understanding of ideas (0%) 10
Total: 100%

Research methods in practice: strategies for descriiption and causation (3rd edition).

Dear Writer,
For this assignment, please open the PowerPoint file I have uploaded for you and answer each exercise from #7a through #7e. Please make sure that each bullet question under each exercise is answered. Each exercise pertains to the small studies in the slides above them. Only exercise #7e is related to the Urban Trail article that I have uploaded separately. You can also find more information about this topic in chapter 15 of the textbook listed below. If you have any questions, please let me know. Thank you!
Textbook:
Remler, D.K., & Van Ryzin, G.G. (2022). Research methods in practice: Strategies for descriiption
and causation (3rd Edition). Thousand Oakes, CA: Sage Publications. ISBN-978-1544318424

Is he right or wrong?

I need a paper for the following article: https://www.nbcnews.com/politics/elections/how-big-data-broke-american-politics-n732901
• Please read and respond to his op-ed. Is he right or wrong? Or maybe he
is partially correct, but his argument requires more nuance.
• 2-3 page (single-spaced) essay responding to Todd.
• You are expected to do some outside research for this short essay.
• I do not care what citation style you use; just pick one

Which are

Please only answer what’s highlighted in red. Which are
f) How many students registered for a course for a total of 55 books sold by the university bookstore?
a) Determine the 4-period moving average for all the weeks in the four-month period.
b) Using the simple exponential smoothing approach and a smoothing constant of α=0.35, provide forecasts of gasoline prices if the initial forecast of gasoline price is 2.935 dirhams.
We solved everything but you need to solve these above questions. But please make sure to check the word document since you need the information there to answer the questions. And please try to send it within 12 hours since its urgent.

The variables in the data set provided are as follows:

Need knowledge of statictics
Data from a sample of 428 automotive vehicles from the same production year was collected in order to understand the relationship between the price (as measured by the MSRP) and descriptive variables for each vehicle. The variables in the data set provided are as follows:
Response Variables
Manufacturer’s Suggested Retail Price (MSRP) – this is the response of interest
Dealer Cost – an alternative response that is not of interest
Predictor or Independent Variables
Engine Size – measured in liters
Numbers of Cylinders in the engine
Horsepower of the engine
Miles per gallon for city driving (MPG – City)
Miles per gallon for highway driving (MPG – Hwy)
Vehicle Weight
Wheelbase of vehicle
Vehicle Length
Vehicle Width
Drive Wheels of each vehicle
Vehicle Type