Category: Statistics homework help

– WEEKLY DISCUSSION BOARD
– WEEKLY LEARNING ACTIVITY BASED ON THE STATISTICAL ANAYLYSIS RUN A MANAGERIAL REPORT
– WEEKLY ASSIGNMENT(CHAPTER ACTIVITIES)

 
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). 

 
As a student at UMGC, you have been asked to join a fictional committee that will partner with new students in various programs of study. You will work alongside UMGC students from other programs to coordinate a weekend event that includes a tour of the campus, an informal meeting with students who are interested in your program, and a lunch-and-learn session with a panel of experts from various fields. During the meeting with students who may be interested in your field of study, one student mentions that a program requirement is statistics. That student asks you why statistics is needed in this program.
Do research online and create a thoughtful reply to the student, including a list of at least 3 specific ways in which statistics is used in your field of study. Include references from the online sources. Don’t forget to cite your sources in APA format! (see the Announcement here for additional information: Where to find information on APA format). This serves as your initial post to the discussion and is due by 11:59 pm EST on Saturday.

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.

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.

 Calculate the hypothesis test p-value for the population mean with the given z-score. (Note: With two (2) tail tests you must add both tail p-values.) a. ????0: ???? ≤ 1.07 and ????a: ???? > 1.07, ???? = 2.27 

For this Final project, you will be analyzing data that was collected from the survey that I sent to you all during the first couple weeks of class! I hope you have fun learning a little more about your classmates in this Final Project.:) This dataset contains information from 178 students (98 students in STA 2023 and 80 students in MAC 1105).
NOTE: You DO NOT need to work with the actual data set for this. I have included all of the relevant summary statistics in the statements of the problems.
Complete the assignment either on paper or on the computer.

Make sure to answer all questions. 
Please try to include any sketches and work on the worksheet. If you are not able to, however, you may submit them as a separate document. (It’s just a little easier to grade when it’s all in one document.)
If you do not have access to a printer, you can hand write your asnwers on a separate sheet and upload a picture.

Upload completed worksheet to this assignment in Canvas.
If you have any questions, don’t hesitate to ask! 
NOTES/HINTS:
The degrees of freedom for these problems is large, you may need to use StatCrunch or an online calculator to find the critical values for the t-distribution:
please follow the template attached

  1. Abstract: A brief statement (few sentences at most) summarizing the purpose of the report as well as the results and what they mean in substantive rather than statistical terms. Be brief and to the point, stimulating your reader’s interest. You essentially have 15 seconds to let the reader know what’s in the report and if they should read it. 
2. Introduction: Give background and motivate the question to be investigated. Introduce the data, perhaps with visualization or descriptive statistics, but only if you think it significantly adds to the narrative. A reader could jump from here to Results. While a formal research study has explicit hypotheses, you likely won’t have any, but at least try to suggest which variables in what form you expect to be important predictors. 
3. Methodology: Describe the approach used to analyze the problem while keeping in mind that your reader likely never took or doesn’t remember ST 625. What was your approach? Why is your approach is appropriate? What are the assumptions? Are there any concerns about these assumptions? 
4. Results: Present the recommendation simply and clearly. Use graphical display, table, and discussion as you see appropriate. You are providing an answer to the question outlined in the introduction. 
5. Conclusion: Briefly summarize everything. Does the model make sense? Do the predictors seem reasonable? What does it all mean? Suggestions for further analysis or other data might be appropriate.
 6. Appendix: Screenshots of recommended R model 
Using the range of models, tools, and techniques studied in ST 625, build and present two models: one for predicting casual bike rentals using the independent variables, and another for predicting registered bike rentals. Your ultimate goal is to explain the factors that influence bike demand, and as such your model/variable selection should be based both on context and statistics. Model interpretation will be very important part of your report! What influences demand for bikes, and how, and to the extent plausible why? You should at a minimum perform linear regression using all the available independent variables as well as consider some types of complex model (terms that are higher-order, interaction, dummy), then perform variable selection/compare models. And to be very clear, casual should not be a variable used to predict registered, nor vice-versa 

 
Instructions
Scenario:
A generation ago, people used to see their doctor only when they were sick or dying. Today, preventative health care is becoming commonplace as people become more educated and empowered about their own health. Regular, routine medical check-ups can help find potential health issues before they become a problem. Early detection of problems gives the best chance for getting the right treatment quickly, avoiding any complications.
You have been employed as part of an active public health campaign that is aiming to increase routine 12-monthly check-ups. Your job is to identify groups of people with lower rates of check-ups in the last 12 months where a targeted campaign would be of most benefit.
The Behavioral Risk Factor Surveillance System (BRFSS) is a collaborative project between all of the states in the United States (US) and participating US territories and the Centers for Disease Control and Prevention (CDC). The BRFSS is a system of ongoing health-related telephone surveys designed to collect data on health-related risk behaviours, chronic health conditions and use of preventive services from the non-institutionalised adult population (≥18 years) residing in the United States. Using the prepared BRFSS data, identify demographic, social and behavioural factors that are associated with routine check- up attendance.
Dataset:
BRFSS 2024 data
Format:
Your written briefing document must consist of a 250-word executive summary and a detailed structured results section. This template will assist you with the format and information required.
Executive Summary (Marks: 25)
The 250-word summary should identify demographic, social and behavioural factors that are associated with routine check-up attendance in a statistically valid, clear and concise manner that can be understood by someone with minimal knowledge of epidemiology and biostatistics. You must identify a group or groups of people where a targeted campaign would be of most benefit.
Results:
The BRFSS:
A short summary of the study design of the BRFSS and a brief discussion of its limitations (no more than 250 words (Marks: 6)
Find a peer-reviewed primary quantitative research study in the literature that investigates the determinants of routine check-up attendance. Compare the designs between the study described in that paper and BRFSS (not more than 150 words). (Marks: 4)
Description of the population and analysis:
1) By analysing the BRFSS dataset, answer the following questions:
In your dataset, what percentage of participants reported routine check-up attendance? (Marks: 5)
Create a table of routine check-up attendance and 3 demographic factors, one of which must be binary, one numerical and one multi-category categorical (either nominal or ordinal). (Marks: 15)

Each cell should contain the appropriate summary measure and 95% confidence interval
The final column in the table should contain the p-value for statistical tests of difference or independence (i.e., tests that we covered in week 6). Footnotes should be used to indicate which statistical tests were used.

2) Examine the association between 4 social and/or behavioural factors and routine check-up attendance:

In an appropriate manner, present the results of analysis into the effect of four social and/or behavioural factors on routine check-up attendance. You must analyse a binary, numeric, nominal and ordinal factor. (Marks: 20)

For each factor you should report:

Variable name and data type
Name of measure  calculated
Results of statistical analysis performed
Statistical interpretation
The Stata output (including visible code) e.g.

For one of the identified factors, you should explore the possibility of confounding or effect modification by sex. (Marks: 10)

Perform appropriate analysis
Present STATA output (including visible code)
Report the results in a table
Interpret your result

Conduct a multivariable regression and present the results of the adjusted regression model by including the four factors you examined in your analysis of social and behavioural factors. (Marks: 10)

Present STATA output (including visible code)
Report the results in a table.
Interpret your result