Category: Accounting homework help

 Mini-Research Proposal: Using the previous weeks’ assignments, develop a 10-12 page mini-research proposal using this template that outlines a feasible, original research project within your field of study that includes 
References, formatted in APA 7th edition. 
Without Plagiarism

 
What have been your greatest challenges and successes in this project so far?
What is the most interesting, educational, or personally relevant part of the project so far?
What strategies will you use to support your successful project completion?

Since the COVID tracking project has discontinued, there is no single federal database with all covid data.  However, the Center for Disease Control (CDC) COVID Data Tracker contains links out to covid data for states and counties. 
Use the links provided by the CDC COVID data tracker to find the covid data for your state: https://data.cdc.gov/Case-Surveillance/United-States-COVID-19-Cases-and-Deaths-by-State-o/9mfq-cb36/data
Sort the data by state and then by submission date.  Copy all of the data for your state to a new sheet.
Create a new column AR in the database labeled % positive. The formula to calculate % positive should be = AD1/AP1. Format the cell for percentage. Copy the cell down the column for all dates of your state.
Using the data, develop a linear regression time series analysis for deaths (column D), % tested, and % positive. Answer the following questions:

What is the null and alternative hypothesis for each variable?
What was the r squared for each variable? What does this mean?
What was the p-value of each test? What does this mean?
For those tests which were significant, use the model to predict the value of the variable seven days after the end of the workshop.

Write a short report (1 to 2 pages for each variable) that includes the results of your analysis. Present the results and discuss the implications of your findings. Include whatever graphs or statistical output you may have generated in answering these questions along with a short explanation of your analysis. What conclusions concerning COVID19 may you draw from your analysis?

 Participation will consist of locating, submitting and commenting on current articles related to real estate. Links to these articles are to be posted to Article Participation under the Discussion Board. Do not post the article itself, just its link. You are to read these articles and then post your comments/thoughts about the article. When submitting an article, YOU MUST begin your comment with the phrase “What I found interesting about this article is…” If this is not the first sentence in your comment, no credit will be given.DO NOT submit a summary of the article. Summaries will not receive any credit. I am looking for your comments / thoughts about the article. These articles must be current and pertain to any aspect of real estate, or anything that impacts real estate. These articles can be found online, in publications or any other source you may uncover. To receive credit, comments must be substantive, meaning not just a quick line or two. I am looking for at least four (4) lines of meaningful, thoughtful commentary. Now, how many articles do you need to submit in order to earn the full 10 participation points? two articles.  
 
 
DO NOT use the following articles:
– https://doi.org/10.1108/jpif-06-2023-0053
– https://doi.org/10.1080/02723638.2018.1524653
–  https://research.skylineuniversity.ac.ae/id/eprint/34/
–  https://www.sciencedirect.com/science/article/pii/S2199853123001786 
– https://doi.org/10.1186/s41937-023-00111-0
–  https://doi.org/10.3390/land12040740

 
What have been your greatest challenges and successes in this project so far?
What is the most interesting, educational, or personally relevant part of the project so far?
What strategies will you use to support your successful project completion?

Since the COVID tracking project has discontinued, there is no single federal database with all covid data.  However, the Center for Disease Control (CDC) COVID Data Tracker contains links out to covid data for states and counties. 
Use the links provided by the CDC COVID data tracker to find the covid data for your state: https://data.cdc.gov/Case-Surveillance/United-States-COVID-19-Cases-and-Deaths-by-State-o/9mfq-cb36/data
Sort the data by state and then by submission date.  Copy all of the data for your state to a new sheet.
Create a new column AR in the database labeled % positive. The formula to calculate % positive should be = AD1/AP1. Format the cell for percentage. Copy the cell down the column for all dates of your state.
Using the data, develop a linear regression time series analysis for deaths (column D), % tested, and % positive. Answer the following questions:

What is the null and alternative hypothesis for each variable?
What was the r squared for each variable? What does this mean?
What was the p-value of each test? What does this mean?
For those tests which were significant, use the model to predict the value of the variable seven days after the end of the workshop.

Write a short report (1 to 2 pages for each variable) that includes the results of your analysis. Present the results and discuss the implications of your findings. Include whatever graphs or statistical output you may have generated in answering these questions along with a short explanation of your analysis. What conclusions concerning COVID19 may you draw from your analysis?

 Participation will consist of locating, submitting and commenting on current articles related to real estate. Links to these articles are to be posted to Article Participation under the Discussion Board. Do not post the article itself, just its link. You are to read these articles and then post your comments/thoughts about the article. When submitting an article, YOU MUST begin your comment with the phrase “What I found interesting about this article is…” If this is not the first sentence in your comment, no credit will be given.DO NOT submit a summary of the article. Summaries will not receive any credit. I am looking for your comments / thoughts about the article. These articles must be current and pertain to any aspect of real estate, or anything that impacts real estate. These articles can be found online, in publications or any other source you may uncover. To receive credit, comments must be substantive, meaning not just a quick line or two. I am looking for at least four (4) lines of meaningful, thoughtful commentary. Now, how many articles do you need to submit in order to earn the full 10 participation points? two articles.  
 
 
DO NOT use the following articles:
– https://doi.org/10.1108/jpif-06-2023-0053
– https://doi.org/10.1080/02723638.2018.1524653
–  https://research.skylineuniversity.ac.ae/id/eprint/34/
–  https://www.sciencedirect.com/science/article/pii/S2199853123001786 
– https://doi.org/10.1186/s41937-023-00111-0
–  https://doi.org/10.3390/land12040740

  
Your Case Study: Historical Financial Analysis Assignment paper must include:
1. Historical Financial Statements (Income Statement, Balance Sheet and Statement of Cash Flows) from the 3 most current years for the firm. These should be downloaded from the SEC website. The financial statements must include horizontal (shown between the years) and vertical analysis (shown to the right of the last year of historical data).
2. Ratio analysis for the ratios shown on Table 1 in the Guide to Case Analysis (CA) of the textbook:
a. Profitability ratios
b. Liquidity ratios
c. Leverage ratios
d. Activity ratios
e. Price-to-earnings ratio
f. The changes between years are included in the calculations.
3. Competitor ratios to compare with the ratios that were calculated in item 2. These should be included on the same tab as the ratio analysis for the firm.
4. Financial analysis should include comparisons to the firm’s main competitor as well as to the industry. How does the financial position of the firm influence the strategic direction of the company? This section should not be used to define what each ratio is rather it should clearly provide analysis based on the calculations as to the strategic choices and implications of the firm’s financial position. A compare and contrast with the main competitor should be included in this section of narrative.
Place the results of Case Study: Historical Financial Analysis, in the Case Study: Historical Financial Analysis submission link in Module 6: Week 6. 
Options to Download SEC Financial Data into Excel Spreadsheets:
There are two ways to pull financial data in Excel format from the SEC site, depending on how recent the information is.

  
Your Case Study: Historical Financial Analysis Assignment paper must include:
1. Historical Financial Statements (Income Statement, Balance Sheet and Statement of Cash Flows) from the 3 most current years for the firm. These should be downloaded from the SEC website. The financial statements must include horizontal (shown between the years) and vertical analysis (shown to the right of the last year of historical data).
2. Ratio analysis for the ratios shown on Table 1 in the Guide to Case Analysis (CA) of the textbook:
a. Profitability ratios
b. Liquidity ratios
c. Leverage ratios
d. Activity ratios
e. Price-to-earnings ratio
f. The changes between years are included in the calculations.
3. Competitor ratios to compare with the ratios that were calculated in item 2. These should be included on the same tab as the ratio analysis for the firm.
4. Financial analysis should include comparisons to the firm’s main competitor as well as to the industry. How does the financial position of the firm influence the strategic direction of the company? This section should not be used to define what each ratio is rather it should clearly provide analysis based on the calculations as to the strategic choices and implications of the firm’s financial position. A compare and contrast with the main competitor should be included in this section of narrative.
Place the results of Case Study: Historical Financial Analysis, in the Case Study: Historical Financial Analysis submission link in Module 6: Week 6. 
Options to Download SEC Financial Data into Excel Spreadsheets:
There are two ways to pull financial data in Excel format from the SEC site, depending on how recent the information is.

 Sales_Data_.xlsx (129.279 KB)
You have been hired as a marketing analyst by a rapidly growing mid-sized retail company that has accumulated a significant amount of sales data. Despite their growth, the company is struggling to extract actionable insights due to fragmented and disorganized reporting processes. The leadership team is eager to identify the main drivers of profit, recognize top-performing products and customers, and optimize sales strategies across different states and market segments. However, their ability to make informed, data-driven decisions is currently hindered by the absence of a comprehensive, user-friendly dashboard.Your assignment is to develop a comprehensive sales dashboard that consolidates all of the company’s sales data into a single, interactive platform. This dashboard should empower the company’s leadership and sales teams to quickly assess key performance metrics, identify trends, and make informed decisions that will drive more effective and strategic business actions.Objective: The dashboard should visually represent the sales data provided, modeled after the example dashboard shown in the provided video. The key metrics and visualizations should include:
Total Sales
Total Profit
Profit Percentage
Units Sold
Top Selling Product
Sales and Profit by Month
Sales Generated by Customer
Sales by States
Sales Breakup by Segment
You must use Excel to create the dashboard.Ensure that your submitted files include a sheet demonstrating the thoroughness of your analysis.Any dashboard generated using AI will be marked zero.Data provided contains the following columns:
Segment: The market segment where the product was sold (e.g., Franchise, Retail, Wholesale, Online).
Customer_ID: Unique identifier for customers.
Product_ID: Unique identifier for products.
Discount Band: The discount level applied (e.g., Low, Medium).
Units Sold: The number of units sold.
Manufacturing Price: The cost to manufacture the product.
Sale Price: The selling price of the product.
Discounts: Total discounts given.
Date: The date of the sale.
Customer_Name: The name of the customer.
Product_Name: The name of the product.
State: The state where the sale occurred.
Gross Sales: Total sales before deductions.
Sales: Total sales after deductions.
COGS: Cost of Goods Sold.
Profit: Profit generated from the sales.
Profit (‘000): Profit in thousands.
Month: The month of the sale.
Quarter: The quarter of the sale.
Year: The year of the sale.
Steps:

Data Cleaning and Preparation:

Ensure data consistency and accuracy.
Handle missing values and correct any data inconsistencies.
Derive additional columns if needed (e.g., Monthly Sales, Yearly Profit, etc.).

Visualizations:

Total Sales & Profit: Display total sales and total profit.

Profit Percentage: Calculate and display the profit percentage.

Units Sold: Display total units sold.

Top Selling Product: Identify and display the top-selling product.

Sales & Profit by Month: Create a bar chart showing sales and profit for each month.

Sales Generated by Customers: List customers and their corresponding sales.

Sales by States: Visualize sales distribution across different states.

Sales Breakup by Segment: Pie chart showing the percentage of sales by different market segments.

Dashboard Design:

Design a dashboard that is clear, visually appealing, and easy to interpret.
Use appropriate chart types, colors, and labels to enhance readability.

Analysis and Insights:

Analyze the data and provide insights based on the visualizations.
Identify trends, patterns, and any notable observations from the data.

Presentation:

Prepare a brief report or presentation summarizing the findings.
Highlight key metrics and insights from the dashboard.
Include a 20 – 25 minute presentation video where you walk through the workings of the dashboard and a brief summary of the analysis. The presentation should cover:

Overview of the Dashboard: Introduce the key metrics and visualizations included.

Data Sources and Preparation: Explain the data cleaning and preparation steps and highlight key aspects of your analysis. 

Detailed Walkthrough: Go through each visualization, explaining what it shows and why it is important.

Key Insights and Observations: Summarize the main findings and insights from the data.

Technical Aspects: Briefly discuss any technical challenges or interesting techniques used in creating the dashboard.

Submit the Excel file containing the final dashboard, along with a sheet demonstrating the thoroughness of your analysis. Include a report or presentation with your analysis and insights. Additionally, submit the recorded presentation video file.