Category: Statistics homework help

 
In this Assignment, you will import an Excel file and produce a data dictionary. To complete the Assignment, follow the steps outlined below:
Import the SPSS Skills Data Set Excel file into SPSS.
Produce the Data Dictionary.
Export the Data Dictionary from the Output Window of SPSS into a Microsoft Word document.

FIRST ONE!!
Use JASP for this investigation
Tables, charts, and graphs should be APA formatted as expected. Copy and paste the numerical prompts below into your submission document and record your responses directly beneath. Include the following in your submission:
1.  Use this Kaggle dataset
https://www.kaggle.com/datasets/uciml/student-alcohol-consumption
2.  Select a variable to be used as the Response Variable. List it here.
3.  Select three continuous variables to serve as explanatory variables
4.  Generate a Numerical Summaries table, Correlation table, and histogram on each interval.  (Interpret Model 2 row in JASP)
5.  Run the multiple regression and report the 3 regression output tables
6.  Interpret R, Adjusted R square values
7.  Interpret p-value from Regression table
8.  Interpret p-values from Coefficient table
9.  Check VIF (collinearity diagnostics) and Durbin-Watson and interpret
10.Check residuals vs predicted plot. Interpret
11.Check residuals histogram. interpret
12.Use a variable selection process (stepwise, forward, etc …) , indicate which process you used, to remove explanatory variables. 
13.Show all 3 final regression output tables after the variable selection process has completed.  Interpret relevant statistics within the tables
14.Report final regression equation
SECOND ONE!!!!
Your report is a continuation on your work with questions above. Complete in JASP.  APA formatting is expected. Use the same dataset as used with the final
1) Select 1 variable as the response variable. Select one continuous and one categorical variable as explanatory variables. Report your variable choices.
Compute and interaction term , in JASP, by multiplying together the categorical variable with the continuous variable independent variable.
You will use both independent variables and the computer interaction term in the regression analysis
Complete the following:
1) Run a regression test. Report all 3 output tables
2) Is there an interaction effect detected? Explain
3) Run the analysis without the interaction term. Report the 3 resulting regression tables
4) How has the output changed? (R, Adjusted R squared, ANOVA table p-value, and Coefficient table p-values)
THIRD ONE!!!
Your Final presentation is to be a collection of presentation slides that report on the work completed  and final report. 
Please use Powerpoint. 
Submit all tables and charts generated or created for the questions and final report. Font size of 18 pt or higher. Use a colorful design theme for your presentation. APA formatting expected
Your presentation slides are to include (title each slide so that it is clear what you are presenting):
1.  Title Slide
2. slide of each table and chart reported
will need notes for each page for presentation. 

Working with datasets given; providing outputs from the list of the tasks through R program language. No need for further explanations and writing whole assignment, just providing R notebook with codes and outputs per sections with short comments on what you did so I can continue on writing the report. 

 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. 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?

 
Unit 1 Assignment: S WOT and Linear Regression
Outcomes addressed in this activity: 
Unit Outcomes: 
Describe types of risks in order to prioritize them.
Distinguish the difference between risks and issues.
Explain root causes and consequences of risk. 
Course Outcome: 
IT528-1: Enumerate common types of risks and their potential ramifications for modern business.
Purpose 
The purpose of this Assignment is to practice developing a SWOT analysis to identify and plan for risk mitigation, and then to prepare a linear regression model in R® that will address that risk. You will be expected to complete both a SWOT analysis and a linear regression model in this Assignment. 
Assignment Instructions 
Complete the following steps: 
In a Microsoft® Word® document, create a SWOT table for the following scenario: 
Home & Hearth is an American company that distributes heating oil for homes in rural areas across the country. These homes are remote enough that they cannot connect to natural gas services that are a normal part of town and city life. They must purchase heating oil to be delivered to their properties by truck, usually once or twice a month, though sometimes more frequently in colder months. Home & Hearth has been delivering heating oil to such homes all across America since in 1976. The company has a strong network of suppliers of crude oil, and owns its own refineries in eight regional locations around the country to process the crude into heating oil. Although it has more than forty years of experience, the company has been caught off guard from time to time with too little crude oil on-hand when demand for their heating oil has increased, sometimes due to new accounts, sometimes due to harsher or longer than expected winters in some areas. When winters are short or mild, the company is sometimes left with tens of thousands of gallons of crude or refined heating oil on-hand. Heating oil can turn rancid (unusable) if it is not used within a few months, though there are some preservation techniques that can extend the shelf life of heating oil by refrigeration. The price of oil seems to be changing all the time, which frustrates the company’s management as well. Over the years of their existence, oil burning stoves, furnaces, and hot water tanks have also become much more efficient, and the technology continues to improve. As cities and towns across America have continued to grow, some of their customers have gained access to natural gas hookups, but the company has also seen an influx of new customers moving to the country to escape the congestion and bustle of more metropolitan areas.
Note that although there is no hard-and-fast number of items, the paragraph gives enough information that every quadrant of your SWOT table should have at least two items, and could have more depending on your research and knowledge of the energy industry and supply chain concepts. Your lists should include both risks and issues Home & Hearth faces, and should distinguish between them.
Download the HeatingOil.csv data set file from Course Documents. Import it into R using this command: HeatingOil <- read.csv(file.choose(), header=T) Create a linear regression model to predict heating oil usage based on the other variables in the data set. Place a screenshot of your linear regression model into your Word document. Write an interpretation of the predictive ability of your model and independent variables, with specific attention paid to independent variable coefficients and p-values. Conduct research about the energy industry, focusing specifically on SWOT/risks this industry faces. Write a summary of how your linear regression model could help Home & Hearth respond to risk. Contextualize your summary using the research that you found. You should cite a minimum of five sources. These should be related to SWOT, linear regression, and/or risk management in the energy sector. Do not cite the data set or the course textbook.  Assignment Requirements  Prepare your Assignment submission in Microsoft Word following standard APA formatting guidelines: Double spaced, Times New Roman 12-point font, one inch margins on all sides. Include a title page, table of contents and references page. You do not need to write an abstract. Label all tables and figures. Cite sources appropriately both in the text of your writing (parenthetical citations) and on your references page (full APA citation format). 

Use DBS2_1.1. and DataSet2.xlsx  to answer the questions in project questions and Instructions-1.docx. Please see attached documents and complete on time. Correct answers only.