Category: Statistics homework help

The following sample Excel datasets can be found at the following site
https://www.contextures.com/xlsampledata01.html#office
Access the practice dataset associated with the Z, then:
Select 3 continuous variables, from the dataset, select 1 to serve as the dependent variable. List your choices
Using Excel, generate a histogram of the dependent variable. APA formatting is expected
Using Excel, follow the tutorial video and generate multiple regression tables
Using JASP (you may need to save the Excel file as a .csv file), follow the demonstration in the JASP tutorial video posted in Week 3 and generate multiple regression tables.
Report all generate Multiple Regression tables. 
All generated Tables should be numbered
Report your histogram and multiple regression tables in PDF format

You will use the following Kaggle dataset for this assignment: 
https://www.kaggle.com/datasets/yasserh/student-marks-dataset

 
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). 

Dataset Options
In many cases, researchers may have the data from their study in another software package like Microsoft Excel. However, if the data is not available in a software spreadsheet you can manually enter the data. Option 2: Manual Data Entry
In the Worksheet window, type “Age” in C1. Enter the numbers as shown in the dataset below. Enter the remaining data as shown below (set up your column labels i.e., variable). The measure reflects math anxiety and the study variables (cringe, uneasy, afraid, worried, understand) the math anxiety range is from 1–5 with low being the least and 5 the highest.
 ********See picture attached**********
Step 2: Click on Excel tab for Add Ins; if you do not see statistics; you will need to open the file option; click on Add ins; click on ok; a box will open which will allow you to choose Statistics package; place a check mark in the box and click ok. How to Run Descriptive Statistics
Now that your data is in Excel, you will look at the descriptive statistics for this dataset. Select the data in all the columns except the top that has words for the columns; however you have the file already completed and a picture of the descriptive statistics..See end of page for a copy of the excel sheet and descriptive statistics output.
Discussion Question Part 1
How could you use Excel descriptive statistics for data analysis research? Write about your experience running descriptive statistics. Use the results in the Session Window to support your response. Then add to your discussion with the information you learn writing up your analysis.
Step 3: Excel and Graphs
You will now look at graphing. Select insert graph located at the top of the sheet; highlight the data you want to use for a chart; select the type of chart; select ok. Try using the histogram  feature for one of the variables and select “Ok”. You can create other Histogram graphs by choosing different variables. You can also choose from the other ten graph choices shown on the insert chart function.
Discussion Question Part 2
What are your plans for learning more about Excel and how will the information you learned about this software be of benefit in your future analysis of research data? Copy and paste your graph(s) in a Word document and attach to your discussion response.

https://ronellekriegerprofile.weebly.com/uploads/7/4/8/4/7484534/the_importance_of_assumptions_in_multiple_regression_and_how_to_test_them.pdf
https://ics.uci.edu/~jutts/110/Lecture3.pdf
Initial Post (Due Wednesday, May 8) Copy the questions in your post.  Present your response directly below the question so that it is clear to what question you are responding to
Using the dataset associated with this thread. Select 2 explanatory continuous variables and one continuous response variable (Your choice).  
List your variables and the variable descriptions
Run a multiple regression test using either JASP or Excel.  Post all 3 of your multiple regression output tables to this thread.
Interpret the R, Adjusted R squared, ANOVA table p-value, the coefficient table p-values
Select ONE technique for assumption checking for multiple regression.  Run that technique on the variables that the STUDENT used in their post (not your variables)
Present the results (chart, table, numerical summary … whatever your evidence is that you generated) and interpret them.  Has the assumption been met?  Explain.