Category: Statistics

The questions will be in the document that I shared.  For the last questions you will need to use the excel sheet that i have also shared.
Thank you.

please do the homework questions on the assignment paper
chapters are attached will the questions
FOLLOW THE WEEK 1 ASSIGNMENT DOC AND ANSWERS ALL QUESTIONS

MAKE SURE YOU WATCH THE VIDEO FROM MY PROFESSOR FIRST, TO SEE HOW THE ASSIGNMENT SHOULD LOOK.
http://us-lti.bbcollab.com/recording/5d70b8c8510c4440a4c9d74a57b0885e
PART 1: CONDUCT A SIMPLE REGRESSION
With the attached Data sheet, complete the following task:
1. Conduct a simple linear regression based on the following research question: Does a person’s job satisfaction predict their organizational commitment?
2. Report and evaluate the regression diagnostics.
Your part 1 submission should be in APA 7 FORMAT, in 4 pages. Results should include,
*A simple linear regression based on the research question
*A report and evaluation of the regression diagnostics
* Assumptions relating to the test, and
* A brief narrative explaining results
PART 2: CONDUCT A SIMPLE REGRESSION
With the datasheet attached complete the following task:
1. Conduct a multiple linear regression based on the following research question: Does a person’s job satisfaction and leadership preference predict their organizational commitment?
2. Report and evaluate the regression diagnostics.
Your Part 2 submission should be completed in APA 7 FORMAT with a minimum of Four pages, with the results including,
* A multiple linear regression based on the research question
* A report and evaluation of the regression diagnostics
* Assumptions relating to the test, and
* A brief narrative explaining results.

Hi there , this is STAT 101 class and i am requesting the writer 325247 he/ she did my order. #545824358 on November 13 2023. so my order had 3 parts and he did the 3rd part wrong so i am requesting again for doing ONLY the 3rd part. Note – I uploaded a picture of my instructors feedback please correct it, Take the notes into consideration
PART 3 The Steps To Take:
When you have chosen your INTERVAL variable: Gather the frequency distribution for your variable and be sure you are using the numbers for the 2022 survey year. You will use the frequency distribution to find the mode, median, and range, when relevant. Remember to ignore any category that is for a “non” answer, e.g., don’t know, no answer, no response, etc. Be sure to note the names of the categories for your nominal and ordinal variables – they may be coded with numbers but those do not mean anything – use the names for each category! To get mean and standard deviation, please use this list. DO NOT CALCULATE THOSE YOURSELF. (You have too much to do right now and it’s not always possible, depending on which variable you chose.) Analyze only your INTERVAL variable in this part. If you would like more guidance on how to choose and deal with your variables, check out the examples tab. Use the outline to write up your analysis. There is no great need to include the frequency distributions – but if you do want to include them, put them in an appendix (optional). then have a paragraph describing your appropriate central tendency and variability statistical patterns for your variable in your own words. Use This Outline Interval Variable– Describe the distribution of your data for this variable. Interpret the frequency distribution and appropriate measure(s) of central tendency (Mean, Median, Mode, skew, best measure) and variability (Range, sd). Introduction – Tell us what your variable is, in everyday words and, briefly, why you chose it. Discussion: Description of the statistical patterns of central tendency and variability, in everyday words. Use ONLY the relevant statistics for the level of measurement. Please send it as a word pdf.INTERVAL variable. Please also check the list which I uploaded to get mean and standard deviation for the 3rd part of this assignment , please use the list given!! just like in the examples provided! please check the details list as well. if you have any question please contact me.

In Unit 3 you were introduced to correlations and the relationship that exists between variables. We deal with and hear about correlations frequently in our everyday lives (Ex: The bus is running late, there must be a lot of traffic. My computer’s internet is running slow, there must be a lot of people on the Wi-Fi. Gas prices are going up, must be Bidens fault, etc.). The interesting part about these “correlations” is that they are all not necessarily true or related, we can sometimes make ourselves believe they are. For this discussion I want you to search the internet for a common correlation we see in society now a day. You can use social media, google, articles YouTube, etc., just make sure they are reliable and appropriate for class. Without doing further research explain how you think this correlation can be tested. What two variables would we have to measure in order to show a relationship for the topic you shared. Of course, we learned that correlation does not equal causation. So the goal of this exercise is to put that into practice and learn about what common correlations are out there that in fact could be misconceptions.

Complete each of the following statistical analyses using the SASHELP.HEART data and cut and paste your output on to this document.

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.
https://www.mercer.com/insights/total-rewards/talent-mobility-insights/cost-of-living/#rankings
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 descriiptive 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 descriiptive 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?

Instructions
For this discussion post, we are going to construct a confidence interval for the sample mean using the Z-distribution: 
We would like to create an interval to estimate the average recovery time for patients undergoing a new ACL tear recovery program. We sampled 45 patients who underwent this new recovery program and saw the average recovery time to be 285 days. If the population standard deviation can be assumed to be 100 days, compute the 90% confidence interval for the mean recovery time. 
Discussion Prompts
Answer the following questions in your initial post: 
The Z-distribution will be used to create the confidence interval for the mean. Why are we able to use this distribution for this problem?
Create your confidence interval and report what it is. 
The current ACL recovery program averages 320 days to fully recover. Based on the confidence interval you constructed, where does this value fall?
Based on the confidence interval, do you think we have enough evidence from a statistical standpoint to say the new procedure is significantly better than the current procedure? Why or why not?
Supporting Resources: https://www.youtube.com/watch?v=DT-fPG0Hff8Links to an external site. 

Statistics Project Description
You are about to embark on an adventure which will merge the mathematics you are studying with the world around you.  Data sets will be provided and are different for each student; hence this is an individual project and assessment.  Follow the project outline below in constructing your paper.  The length will range from 5-8 pages including text, tables and graphs.  It will be typed in 12-point font, paginated, double spaced with one-inch margins.  A cover page is optional and does not count towards paper length.  Incorporate Geogebra results and graphs.  It is okay to write out any calculations and graphs by hand.  Check the rubric for grading details.
Statistics Project Outline Template
Introduction
Consider your assigned data sets.  What topics might you investigate and why? Consider comparisions among groups, aggregated data(e.g. separated by gender, location, relationship status, health condition etc.) and disaggregated data.
Research questions(at least two): What you are interested in finding out?  These questions will be answered using your assigned data sets. Examples: https://www.bl.uk/business-and-ip-centre/articles/what-are-typical-quantitative-research-questionsLinks to an external site.
Data
Source of data
Identify the variables
Describe the types of variables(qualitative or quantitative)
Give the level of measurement for each variable
Findings
Descriptive statistics
For quantitative data, provide sample sizes, means, and standard deviations
For qualitative data, provide counts, sample sizes, and p’
If relevant to your research question, disaggregate the above data by age, gender, etc.
Relevant tables, graphs, and charts(you must have at least two graphs)
Confidence Intervals(include type, statistics, conditions, confidence level, critical value, error bound, confidence interval and sentence)
Interval 1
Interval 2
And so on for each additional interval(you must have a least two intervals)
Estimate the sample size for a “nice” error bound for one of your confidence intervals
Hypothesis Tests(include type, hypotheses, significance level, statistics, conditions, standardized test statistic, p-value, p-value sketch, conclusion and sentence)
Test 1
Test 2
And so on (Use a hypothesis for each of your research questions)
Conclusion
Answer your research questions 
Discussion
Provide a brief summary of the contents of the report including a concise statement of the research questions and results
Reflection
Reflect on your conclusions
Address any possible flaws that could have biased the data 
What have you learned from this project
Provide recommendations of new questions for future research

Overview
Confidence intervals come into play when we want to create a better approximation for what the true value of a parameter is. In this module, we will discuss the confidence interval for the sample mean. Up to this point, we have created point estimates, which is what we get when we compute the sample mean. This approximation is almost surely incorrect, so we can be better suited using an interval estimate, in this case the confidence interval.  
The concept here is we buffer our prediction of the mean using a margin of error, which uses the Z distribution, as well as a level of confidence, c. Common confidence intervals we create are 80%, 90%, 95%, and 99% confidence intervals. The approach of a confidence interval is this: If we collect sample data and run this approach repeatedly, then approximately 100*(1-c) % of the confidence intervals will contain the true value of the parameter. So, if we construct 95% confidence intervals, we expect that approximately 95% of the intervals we create will contain the true value of the parameter of interest.  
The common formula we use when construction confidence intervals for the mean is this:  
𝑥
¯
±
𝐸
where E is our margin of error. This is the value that will change depending on which distribution we are using.
If we are using the Z-distribution, then 
𝐸
=
𝑍
𝑐
𝜎
𝑛
where 
𝑍
𝑐
is our critical Z value. Now we have to figure out what our critical Z values are.  
Critical Z values will never change and are as follows:   
80% confidence interval: 
𝑍
𝑐
= 1.28
90% confidence interval: 
𝑍
𝑐
= 1.645
95% confidence interval: 
𝑍
𝑐
= 1.96
99% confidence interval: 
𝑍
𝑐
= 2.576
So, let’s walk through a confidence interval calculation using the Z distribution: Suppose we have a sample of data with a mean of 50, a population standard deviation of 10, and a sample size of 64. We want to create a 95% confidence interval for this sample: 
𝐸
=
𝑍
𝑐
𝜎
𝑛
= 
1.96
⋅
10
64
= 2.45.
Lower bound: 
𝑥
¯
−
𝐸
=
50
−
2.45
=
47.55
Upper bound: 
𝑥
¯
+
𝐸
=
50
+
2.45
=
52.45
Then we write our final answer as such: (47.55, 52.45). We can then say that we are 95% confident the true value of the population mean falls between 47.55 and 52.45.  
If we have a scenario in which we are computing a confidence interval for the population proportion, we need to ensure the following conditions have been met: Each trial is independent of one another, and we have seen at least 5 successes and 5 failures (𝑛𝑝≥5  and   𝑛(1−𝑝)≥5  ). If we meet these conditions, then the distribution of the sample proportion can be approximated using the Normal distribution, and we can use the critical Z values discussed above. 
The process of constructing the confidence interval for the population proportion will be similar to that for the mean, and constructed using 
𝑝
^
±
𝐸
, where the margin of error, E, is found as: 
𝐸
=
𝑍
𝑐
𝜎
𝑛
.
So, let’s walk through an example. A survey of 500 nurses was done to see if they were satisfied with their current employer. Of these 500 nurses, 415 claimed they were satisfied. Construct a 90% confidence interval for the population proportion. 
First, we want to compute the value of 
𝑝
^
We do that by taking the number of successes, in this case a nurse being satisfied, over the total number of nurses surveyed. This gives us 
𝑝
^
=
𝑥
𝑛
=
415
500
=0.83.
Once we have this, we can identify that 
𝑞
^
=
1
−
𝑝
^
=
1
−
0.83
=
0.17
. Next, we want to verify we can use the Normal distribution by seeing at least 5 successes and 5 failures. We have definitely met this requirement as we have 415 successes and 85 failures. So now we can compute the margin of error, E, using our appropriate critical Z value. Here is the calculation: 
𝐸
=
𝑍
𝑐
𝑝
^
𝑞
^
𝑛
=
1.645
0.83
⋅
0.17
500
=
0.0276.
Lower bound: 
𝑝
^
−
𝐸
=
0.83
−
0.0276
=
0.8024
Upper bound: 
𝑝
^
+
𝐸
=
0.83
+
0.0276
=
0.8576
Then we write our final answer as such: (0.8024, 0.8576). We can then say that we are 90% confident the true value of the population proportion falls between 0.8024 and 0.8576.  
Instructions
For this discussion post, we are going to construct a confidence interval for the sample mean using the Z-distribution: 
We would like to create an interval to estimate the average recovery time for patients undergoing a new ACL tear recovery program. We sampled 45 patients who underwent this new recovery program and saw the average recovery time to be 285 days. If the population standard deviation can be assumed to be 100 days, compute the 90% confidence interval for the mean recovery time. 
Discussion Prompts
Answer the following questions in your initial post: 
The Z-distribution will be used to create the confidence interval for the mean. Why are we able to use this distribution for this problem?
Create your confidence interval and report what it is. 
The current ACL recovery program averages 320 days to fully recover. Based on the confidence interval you constructed, where does this value fall?
Based on the confidence interval, do you think we have enough evidence from a statistical standpoint to say the new procedure is significantly better than the current procedure? Why or why not?
Supporting resources: https://www.youtube.com/watch?v=DT-fPG0Hff8