Statistics homework help

 
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Dr. Beeper, an Educational Psychologists who studies issues related to higher education, is interested in studying key factors that impact year to year persistence among college students.  His review of the literature identifies several factors that appear to be causally related to persistence. Specifically, academic aptitude, goal commitment, institutional commitment, and the number of work hours.
To test the importance of these factors, Dr. Beeper administers a set of questionnaires to 100 randomly selected first-time, full-time freshmen college students (50 male and 50 female) that attended the Freshmen Orientation in the Fall of 2016, at Newton Young University (NYU) in Nebraska.
Measures:
Institutional Commitment (IC) represents the importance that students place on graduating from the college they are currently attending.   Institutional Commitment was measured with five-item questionnaire. Each item was rated on a 0, 1, or 2 scale.  The possible range of scale scores are zero to 10, where values close to zero indicate little to no importance, and values close to 10 indicate high importance.
Goal Commitment (GC) represents the importance that students place on obtaining a college degree.  Goal Commitment was also measured with five-item questionnaire.  Each item was rated on a 0, 1, or 2 scale.  The possible range of scale scores are zero to 10; where values close to zero indicated little to no importance to obtaining a college degree, and values close to 10 indicated a high importance to graduating from college.
Academic Aptitude was represented as scores on both the SAT-Math and the SAT-Verbal tests.  SAT scores for all participants were obtained from high school transcripts.
Hours works, represents the anticipated number of hours the student expected to work throughout the semester.
Finally, Year-to-year persistence was determined by examining the enrollment records for the sample of 100 students. A student that was registered for registered for the Fall 2017 classes was classified as a “Persister”, and given a code of 1, a student that did not re-enroll for classes at NYU, or any other college/university (based on follow-up phone interviews) was considered a “Non-persister”, and was given a code of 0.  Therefore, the SPSS variable Persist has two levels, 0 and 1.
The assignment is, using the attached SPSS data file, conduct a binary logistical regression analysis in which IC, GC, SAT-MathSAT-Verbal, and Hours Worked are the predictor. variables (covariates in SPSS), and the variable Persist is the outcome (DV in SPSS). Use my sample summary as a model for your summary.
The specific elements of the assignment are:
1) Create a Null and Alternative Hypotheses for the Logistical Regression Analysis
2) State the Goals of the analysis
3) Summarize the results and interpret findings the overall model (for example the Chi Square results, Nagelkerke R-Square or Cox Snell R-Square).
4) Summarize and interpret the results for each predictor;  and present, summarize and interpret the results for each significant predictor (i.e., B, Wald’s test, df, p and OR (ExpB). Interpret the significant OR using the effect size conventions I posted in last week’s (8) discussion board.
5) Include and refer to the appropriate tables within the summary.
Please read my sample summary see what statistics to report, and how to report and interpret them in correct APA style, as well as the tables to include.
You’ll see that in my sample summary I also include t-tests. You may  want to conduct t-tests that compare “persisters” and non-persisters, on the predictor variables (covariates).  Please note that the t-test are optional, and will have no impact on your grade whether you include them or not.  The t-test  are very informative about the bivariate relationship between the predictor variables (covariates in SPSS) and the binomial outcome (DV in SPSS) .
Please note that you are not required to conduct the t-tests, or to compute and report Cohen’s d.
Here’s the syntax for my sample summary.
T-TEST GROUPS=BO(0 1)
/MISSING=ANALYSIS
/VARIABLES=teachsat ressat wkoverld
/CRITERIA=CI(.95).
LOGISTIC REGRESSION VARIABLES BO
/METHOD=ENTER teachsat ressat wkoverld
/PRINT=GOODFIT CI(95)
/CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).
  • attachment

    Week5CollegePersistence.sav
  • attachment

    APASummaryforLogisticalRegression_2_pratice5.pdf
 
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Statistics homework help

 
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Write a 2- to 3-page critique of the research you found in the Walden Library that includes responses to the following prompts:

  • Why did the authors select binary logistic regression in the research?
  • Do you think this test was the most appropriate choice? Why or why not?
  • Did the authors display the results in a figure or table?
  • Does the results table stand alone? In other words, are you able to interpret the study from it? Why or why not?
  • attachment

    DifferentialAnalysisofDiseaseRisk.pdf
 
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Statistics homework help

 
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 Instructions

Final Project Assignment Instructions

Scenario Background:

A marketing company based out of New York City is doing well and is looking to expand internationally. The CEO and VP of Operations decide to enlist the help of a consulting firm that you work for, to help collect data and analyze market trends.
You work for Mercer Human Resources. The Mercer Human Resource Consulting website lists prices of certain items in selected cities around the world. They also report an overall cost-of-living index for each city compared to the costs of hundreds of items in New York City (NYC). For example, London at 88.33 is 11.67% less expensive than NYC.
More specifically, if you choose to explore the website further you will find a lot of fun and interesting data. You can explore the website more on your own after the course concludes.
https://mobilityexchange.mercer.com/Insights/ cost-of-living-rankings#rankings

Assignment Guidance:

In the Excel document, you will find the 2018 data for 17 cities in the data set Cost of Living. Included are the 2018 cost of living index, cost of a 3-bedroom apartment (per month), price of monthly transportation pass, price of a mid-range bottle of wine, price of a loaf of bread (1 lb.), the price of a gallon of milk and price for a 12 oz. cup of black coffee. All prices are in U.S. dollars.
You use this information to run a Multiple Linear Regression to predict Cost of living, along with calculating various descriptive statistics. This is given in the Excel output (that is, the MLR has already been calculated. Your task is to interpret the data).
Based on this information, in which city should you open a second office in? You must justify your answer. If you want to recommend 2 or 3 different cities and rank them based on the data and your findings, this is fine as well.

Deliverable Requirements:

This should be ¾ to 1 page, no more than 1 single-spaced page in length, using 12-point Times New Roman font. You do not need to do any calculations, but you do need to pick a city to open a second location at and justify your answer based upon the provided results of the Multiple Linear Regression.
The format of this assignment will be an Executive Summary. Think of this assignment as the first page of a much longer report, known as an Executive Summary, that essentially summarizes your findings briefly and at a high level. This needs to be written up neatly and professionally. This would be something you would present at a board meeting in a corporate environment. If you are unsure of an Executive Summary, this resource can help with an overview. What is an Executive Summary?

Things to Consider:

To help you make this decision here are some things to consider:

  • Based on the MLR output, what variable(s) is/are significant?
  • From the significant predictors, review the mean, median, min, max, Q1 and Q3 values?
    • It might be a good idea to compare these values to what the New York value is for that variable. Remember New York is the baseline as that is where headquarters are located.
  • Based on the descriptive statistics, for the significant predictors, what city has the best potential?
    • What city or cities fall are below the median?
    • What city or cities are in the upper 3rd quartile?
  • attachment

    Math302FinalProject.xlsx
  • attachment

    FinalProjectGradingCriteria.pdf
 
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Statistics homework help

 
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Before beginning work on this week’s discussion post, review the following resources:

From the below list, select one topic for which you will lead the discussion in the forum this week. Early in the week, reserve your selected topic by posting your response (reservation post) to the Discussion Area, identifying key words about your topic in the subject line.
By the due date assigned, research your topic and start a scholarly conversation as you respond with your initial or primary post to your own reservation post in the Discussion Area. Make sure your response does not duplicate your colleagues’ responses:
Topic:

  • Distinguish between parametric and non-parametric tests.

As the beginning of a scholarly conversation, your initial post should be:

  • Succinct—no more than 500 words.
  • Provocative—use concepts and combinations of concepts from the readings to propose relationships, causes, and/or consequences that inspire others to engage (inquire, learn). In other words, take a scholarly stand.
  • Supported—scholarly conversations are more than opinions. Ideas, statements, and conclusions are supported by clear research and citations from course materials as well as other credible, peer-reviewed resources.
 
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