Category: Statistics

Complete the following assignment by filling all requested information into the worksheet. You will need to utilize SPSS and the GSS data set provided in class to complete it. Use a different, but legible, color font for your responses. This assignment is intended to help you complete the writing of a quantitative research essay/article, with particular emphasis on the Findings and Conclusion sections.
gnment 2: Final Project Guide to Completing the Research Study
Instructions
Overview:
One of the most crucial components of this course is developing a research project from conceptualization to completion. Throughout the class, you created a research study based on publicly available data from the General Social Survey (GSS). You chose data which were representative of your interests and satisfied your research question and hypotheses. The Final Project: Guide to Completing the Research Study is where you pull together the research you’ve been working on the first six weeks of class. 
Instructions:
Complete the following assignment by filling all requested information into the worksheet. You will need to utilize SPSS and the GSS data set provided in class to complete it. Use a different, but legible, color font for your responses. This assignment is intended to help you complete the writing of a quantitative research essay/article, with particular emphasis on the Findings and Conclusion sections.
This assignment is to be completed and submitted no later than the Sunday of Week 7 by 11:55pm ET. It is worth 100 points.
General requirements:
Submissions should be typed, double-spaced, 1″ margins, times new roman 12 pt font, and saved as .doc, .docx, or .pdf.
Use APA format for citations and references
View the grading rubric so you understand how you will be assessed on this Assignment. 
Disclaimer: Originality of attachments will be verified by Turnitin. Both you and your instructor will receive the results.
The research question is : How does one’s degree level affect one’s income level. The variables to be used at DEGREE and RINCOM16.
Attached is a copy of the assignment questions using this question and these variables.

Steps to Complete the Week 7 Lab
Step 1: Find these articles in the Chamberlain Library. Once you click each link, you will be logged into the Library and then click on “PDF Full Text”.
First Article: Confidence Intervals, https://chamberlainuniversity.idm.oclc.org/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=c8h&AN=104521394&site=ehost-live&scope=site
Second Article: Confidence Intervals, https://chamberlainuniversity.idm.oclc.org/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=c8h&AN=104457984&site=ehost-live&scope=site
Step 2: Consider the use of confidence intervals in health sciences with these articles as inspiration and insights.
Step 3: Using the data you collected for the Week 5 Lab(see below) (heights of 10 different people that you work with plus the 10 heights provided by your instructor), discuss your method of collection for the values that you are using in your study (systematic, convenience, cluster, stratified, simple random). What are some faults with this type of data collection? What other types of data collection could you have used, and how might this have affected your study?
Step 4: Now use the Week 6 Spreadsheet (see below)to help you with calculations for the following questions/statements.
a) Give a point estimate (mean) for the average height of all people at the place where you work. Start by putting the 20 heights you are working with into the blue Data column of the spreadsheet. What is your point estimate, and what does this mean?
b) Find a 95% confidence interval for the true mean height of all the people at your place of work. What      is the interval? [see screenshot below]
c) Give a practical interpretation of the interval you found in part b, and explain carefully what the output       means. (For example, you might say, “I am 95% confident that the true mean height of all of the              people in my company is between 64 inches and 68 inches”).
d) Post a screenshot of your work from the t value Confidence Interval for µ from the Confidence                  Interval tab on the Week 6 Excel spreadsheet
Step 5: Now, change your confidence level to 99% for the same data, and post a screenshot of this table, as well.
Step 6: Compare the margins of error from the two screenshots. Would the margin of error be larger or smaller for the 99% CI? Explain your reasoning.
Week 5 lab: https://chamberlain.instructure.com/courses/148328/assignments/4667110/submissions/329546?download=29515873
link to week 6 speadsheet:
https://cdn.brandfolder.io/74235FBJ/at/p2hg33r93pm5t8nsw4xnt/MATH225_W6_ConfidenceIntrvals.xlsx
More info:
https://cdnapisec.kaltura.com/index.php/extwidget/preview/partner_id/2363221/uiconf_id/43522921/entry_id/1_bgj2e6bt/embed/dynamic
****complete the attached template

This week’s lab highlights the use of probability and normal distribution.
Follow the directions below to gather data, calculate using Excel spreadsheets, and interpret the results.

This is a statistics course as part of a Psychology
degree.
Please follow the directions as advised and
follow the rubric to in order to meet the requirements. It’s strongly
recommended to use JASP service as recommended by the university.
·        
For quantitative,
no references are required
·        
For
qualitative, follow guidelines where necessary

Complete steps 1-8
You will analyze data from a sample of home runs hit per season from 2000 – 2023 (excluding 2020).  You can either download the Excel file or work in Office 365 or Google Drive.  

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. How to Write an Executive Summary That Gets the Job Done 2023.pdf
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?

Please complete the remaining questions, beginning at 28.
The link to the training video is embedded in the file.

Open the document that I attched on addional files and answer the
questions that are present on the document. The questions are on: probability, mutual exclusivity, nean, Standard deviation, IQR etc

There is three assignment needed in being completed. Followed the instructions giving,
as well the rubrics.

In this assignment, you will test for a significant difference
between the average resting heart rate of males and the average resting
heart rate of females in your heart rate data.  You have observed that
the mean rates are not exactly the same, but are they significantly
different?  You may use either of the two methods for testing a
hypothesis illustrated in Realizeit:  compare the two confidence
intervals or use the data analysis tool to run a two-sample test with
unequal variances, as shown in the topic of testing two samples.
Steps
Write the null hypotheses being tested.
Run the analysis either by using data analysis and the two-sample test or by comparing the two confidence intervals.
Interpret your data to determine if the resting male heart rate is
the same as the resting female heart rate. Remember, you are looking for
whether the difference is a significant one, not just whether they are
not the same.