For this week’s discussion, you will discuss the following:

1. Differences between Predictive Analytics (PRA), Prescriptive Analytics (PSA), and Experimental Analytics (EXA) based on your learning.
2. Give an example of each of the analytics type

Complete the project to practice both using Power BI and analyzing data.

Save all changes described in the project and make three to five of your own changes that enhance data analysis.

Submit a Word document report of fewer than eight pages with the following level one headings and content. Use level two and three headings as needed.

• Introduction
• Changes
  • Describe the changes you made and why you made each change.
  • Insert figures (screenshots of your changes). Ensure these are properly labeled per APA 7.
• Analysis
  • Describe insights gleaned from your data analysis.
  • Insert figures (screenshots of visualizations from Power BI).
• Conclusion

Requirements

• Submit only one Word document.
• APA version 7 format.
  • Include a cover page and abstract.
  • Do not include a table of contents.
  • Use for guidance.
• Review the rubric to ensure you understand how you will be assessed.

Rubric

Lab 20 2024

Lab 20 2024

Criteria	Ratings	Pts
This criterion is linked to a Learning OutcomeChangesDescribes how and why changes are made. Inserts images of changes with proper labeling. The best changes make the information more significant than before.		20 pts
This criterion is linked to a Learning OutcomeAnalysisDescribes insights gained from analysis of the data and visualizations. Provides properly labeled figures showing the insights. The best insights are significant interpretations based on the data.		20 pts
This criterion is linked to a Learning OutcomeWriting/Grammar/APAClearly written with no stylistic or grammar errors. Business writing must hold the reader’s interest as well as describing precisely and concisely the subjects being discussed. APA conventions are followed.		10 pts

Total Points: 50

Please use attached excel file- question 1 tab 1, Question 2 tab 2

Question 1: Bivariate analysis

Copy the dataset under the first tab, labelled Question 1, into a new Microsoft Excel workbook.

What is a stock market index?

A stock market is a collection of selected stocks, also called shares, and the related market index is computed from the prices of these stocks. Indices can be classified in various ways, the most common of which is by performance.

Examples of performance-based indices are the American Standard & Poors 500 (S&P 500), the British Financial Times Stock Exchange 100 (FTSE 100), and the Japanese Nikkei 225. The FTSE 100, for example, is a share index of the 100 companies listed on the London Stock Exchange that have the highest market capitalisation (as capitalisations change over time, the composition of these leading 100 companies is periodically reviewed).

Stock prices often correlate with the stock market index and tend to change as the market index changes. Investigate the relationship between the market index and each of the two stock prices included in the dataset, by following these steps:

Determine the explanatory and response variables.

Run a regression analysis for each of the two stock prices against the index price.

Interpret the results by answering the following questions:

Plot each of the two stocks against the market index on a scatterplot. Include these scatterplots in your submission. What are the expected correlations that might exist between each of the stocks and the market index?

What are the calculated correlation coefficients? Compare these to your plots. Were your initial expectations correct?

Comment on the coefficients of determination. Which of the two models has the higher explanatory power?

What are the beta coefficients for each of the two stocks?

Suppose you were to purchase one of these two stocks, and your decision relied on their volatility in relation to the market index (i.e. their beta coefficients); which of the two stocks would you purchase if you were interested in buying a volatile stock?

(Max. 200 words)

Start writing here:

Question 2: Multivariate analysis

Copy the dataset under the second tab, labelled Question 2, into a new Microsoft Excel workbook.

Sales figures are usually related to more than one variable, whether it is marketing expenditure, advertising material, shelf placement, or product pricing structures. In this question, total sales figures were found to have a correlation with marketing expenditure and the price of the product. Logically, it could be argued that an increase in marketing expenditure should result in an increase in sales. Similarly, an increase in product price could reduce sales figures.

Using the data provided, perform the following analysis:

Determine the explanatory and response variables.

Run a multivariate regression analysis on all three variables.

Interpret the results by answering the following questions:

What is the calculated correlation coefficient? Do the sales figures correlate with the marketing expenditure and price?

Comment on the coefficient of determination. What percentage of the response data can be explained by the explanatory variables?

Determine the multiple regression line equation in the form:

= (intercept) + (coefficient) marketing + (coefficient) price

Using the regression equation formulated, what is the amount of expected sales (in pounds), if the price is set at ?3.50 and the amount spent on marketing is ?300?

Interpret the variables in the regression equation. What impact does each of the factors (marketing and price) have on the sales figures?

(Max. 200 words)

Start writing here:

Purpose

In real-world analytics projects, analysts rarely begin with clean, well-documented datasets. Instead, they must first understand what data exists, how it is structured, and what level of detail it contains before any analysis can occur.

The purpose of this assignment is to practice creating a data inventory for real organizational reports related to fundraising activities. This process will help you determine what questions the data can reasonably support and what limitations exist prior to analysis.

Data for This Assignment

You are provided with fundraising reports for three years (20232025).
Each year includes two Excel files related to fundraising activity.

For this assignment, you will:

• Complete a detailed data inventory for the 2023 fundraising files
• Perform a structural check for the 2024 and 2025 files to confirm whether the same structure is present

No calculations, visualizations, or statistical analysis are required.

Part A: Data Inventory (2023 Fundraising Files)

(6 points)

Using the 2023 fundraising files only, complete a data inventory for each Excel file.

For each file, document the following:

File Information

• File name.
• Number of worksheets (tabs).

Worksheet (Tab) Inventory

For each tab in the file, record:

• Tab name.
• Brief description of what the tab appears to contain.
• Level of data:
  • Granular (for example, individual players, transactions, dates), or
  • Aggregated (for example, summaries by category, totals, grouped data).
• Number of rows.
• Number of columns.

You may present this information using a table or clearly organized bullet points.

File-Level Reflection (Answer in complete sentences)

For each 2023 fundraising file, answer:

1. What types of questions might this file help answer?
2. What types of questions would be difficult or impossible to answer using only this file?

Part B: Structural Consistency Check (20242025)

(4 points)

Next, review the 2024 and 2025 fundraising files.

You do not need to repeat the full data inventory for these years.

Instead, answer the following questions:

1. Do the 2024 and 2025 files appear to follow the same structure as the 2023 files?
   (Consider file types, tab names, units of analysis, and aggregation level.)
2. Note any meaningful differences you observe, such as:
   • Additional or missing tabs
   • Changes in variable names
   • Differences in aggregation
   • New or missing types of information
3. Briefly describe one potential challenge these differences could create if you were combining data across years.

Submission Instructions

• Submit a single document (Word) to this assignment link.
• Organize your work clearly with headings for:
  • Part A: 2023 Data Inventory
  • Part B: 20242025 Structural Check
• This assignment focuses on organization, clarity, and thoughtful observation, not technical analysis.

Week 3 – Assignment: Homework Problem Set – Due

Jan 25, 2026 11:59 PM

BUSN660 B001 Winter 2026

Assignment Directions:

• End of Chapter Exercises 1-2, Chapter 4 of Analytics for Managers: With Excel
• Submit the assignment here.

Submission Instructions:

• Use excel to calculate the solutions and submit as directed in the text.

Be sure to review the following prior to submitting your assignment:

This assignment aligns with the following:

Resources & Supports

• : You have free access as an APUS student. Sign in with your MyCampus Email credentials.
• : Watch this 3-minute video if you need guidance on submitting your assignment.

Due January 25 at 11:59 PM

This first assignment aims to familiarize you with essential Excel functions and tools for data manipulation, calculations, and organization. Clear communication of your findings is equally important, making business writing a key part of the process. Mastering these skills is crucial for effective data analysis and decision-making in business contexts.

You will work with a USDA weekly retail food sales data for three Western states. The data set includes variables such as state, category, dollars, and unit sales. This exercise will guide you in using Excel functions such as SUM, AVERAGE, COUNT, MAX, and MIN to perform calculations and gain insights from the dataset.

Task

You will use the USDA weekly retail food sales dataset for three Western states, found in the resources below. Once you have the data, follow the instructions below:

Part A: Data Filtering and Descriptive Statistics

1. Filter the data, copy it to a worksheet for further analysis and calculate Total Dollars and Total Unit Sales (SUM function):
   • Using the Filter function dropdown, select Colorado in the state column and the week 2019-10-06 from the date category
   • Copy the heading row and the filtered rows into the Colorado 2019-10-06 worksheet. This is necessary as Excel functions like SUM will include hidden rows from the Filtered data.
   • Use the SUM function to find the overall total sales for the Dollars and Unit sales columns.
2. Insert a column for $/Unit and calculate average $/Unit (AVERAGE function):
   • Insert a column to the right of ‘Unit Sales and add the heading $/Unit. Format the column using “Currency” and two decimal points.
   • Beneath the heading, enter a formula to divide the amount in the Dollars cell to the left by the amount in the Unit sales column to the left (e.g. =F9/E9) . Verify the result is correct (around $3) and then copy that formula for all remaining rows.
   • At the bottom of the column, use the AVERAGE function to calculate the mean $/unit across all categories. Enter the label Mean in the cell to the left.
3. Find Maximum and Minimum $/Unit amounts (MAX and MIN functions):
   • In the cells beneath the Mean label, enter the labels Max and Min.
   • Apply the MAX and MIN functions to find the highest and lowest $/Unit values for the State and date filtered.
4. Save your workbook before continuing and add your last name to the end of the file.

Be sure to name your files as follows:

• Excel Workbook: LastName_Unit1.xlsx
• Word Document: LastName_Unit1.docx

Part B: Data Filtering and Visualization

1. Return to the original By State and Product Category worksheet
2. Create a visualization for Dollars by State for a single product Category for week ending 2019-10-06
   • Use the Filter dropdown arrow in the State column and click on Select All and then OK to reveal all states, but leave the Date filter as is to show all data for all states for the selected week 2019-10-06.
   • Use the Filter dropdown arrow in the Category column to select any single product category .
   • Use the Dollars category to sort the dataset in descending order Largest to Smallest to view which state has the highest total dollar sales for that category.
   • Create a 2-D Clustered Column chart showing Dollars by State
     1. Hold the CTRL key down and select the range of State names with your mouse. Do not include the column name State in your range.
     2. While continuing to hold the CTRL key down, select the range of Dollar values
     3. Release the CTRL key and verify the desired data in the two columns is highlighted
     4. Use the Insert menu and select the Recommended Charts to create a 2-D Clustered Column chart
     5. Edit the chart title to Total Sales by State for Week Ending 2019-10-06
     6. Create a Word document that will be your written summary described in Part C below. Copy the chart and Paste Special to the Word document by right-clicking and choosing the Picture option. Then select the chart in the Word document and use the Layout Options tab that appears to the top right to choose Top and Bottom. This will keep your text paragraph additions above and below the chart.
     7. Alternatively, you can Copy and Paste the chart as a picture within the Excel workbook but the data for the chart will change in the next visualization task so you must do one of these options before continuing.
3. Create a Visualization for Dollars by Category for an Individual State
   • Use the Filter dropdown arrow in the Category column and click on Select All and then OK to reveal all categories, but leave the Date filter as is to show all data for all states for the selected week 2019-10-06.
   • Use the Filter dropdown arrow in the State column to select any single state.
   • Use the Dollars category to sort the dataset in descending order Largest to Smallest to view which category has the highest total dollar sales for that state.
   • Create a 2-D Clustered Column chart showing Dollars by Category
     1. Select the chart and delete it by right-clicking and using the Cut option
     2. Hold the CTRL key down and select the range of Category names with your mouse. Do not include the column name Category in your range.
     3. While continuing to hold the CTRL key down, select the range of Dollar values
     4. Release the CTRL key and verify the desired data in the two columns is highlighted
     5. Use the Insert menu and select the Recommended Charts to create a 2-D Clustered Column chart
     6. Edit the chart title to Sales by Category for [state] for Week Ending 2019-10-06
     7. Go to your Word document and enter 2 or 3 blank paragraphs to make room for the new chart
     8. Copy the chart and Paste Special to your Word document by right-clicking and choosing the Picture option. Then select the chart in the Word document and use the Layout Options tab that appears to the top right to choose Top and Bottom. This will keep your text paragraph additions above and below the chart.
   • Save your workbook.

Part C: Written Summary

In the Word document, write a brief summary (2-3 paragraphs) of your findings from the analysis. Use professional business writing to communicate your insights clearly and effectively. Your summary should be concise, well-organized, and appropriate for a business audience. Note: Copy both of your charts (Dollars by State and Dollars by Category) into this Word document. Use Paste Special > Picture format so the chart’s appearance doesnt change. Place each chart directly below your summary paragraph describing it.

Your summary should include:

• Insights into your charts of states and categories with the highest total sales, including their total sales figures. Put your insights directly above each chart.
• What trends or outliers stand out in your chart? Why might some states or categories outperform others?
• A copy of your Part A work above from the workbook and observations from your $/Unit calculations and Descriptive Statistics calculations of Average, Maximum, and Minimum. Tip: You do notneed to copy the whole table from Excel. Just include the key results in your paragraph – mention the Total Dollars, Total Units, Mean $/Unit, Max, and Min. You may summarize these in your own words rather than pasting the data.
• An assessment of how this data could inform business decisions related to pricing, marketing, or inventory management.
• Reflect on your experience using Excel. Identify one skill you feel confident in after this assignment (e.g., using formulas, formatting charts), and one area you’d like to improve in future assignments.

Week 2 – Assignment: Homework Problem Set

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Instructions
Assignment Directions: Week 2 Homework Assignment: Decision Analysis in Marketing Strategy Background: TechTrend, a leading electronics firm, is considering launching a new smartwatch model to rival its competitors. The marketing team has conducted a preliminary analysis, gathering data about potential sales, marketing strategies, and costs. Your task is to assist in the decision-making process using the concepts learned in Week 2. Data Table: Strategy Marketing Cost Expected Sales (Units) Expected Price per Unit ($) Competitor-response Probability Potential Market Share Loss due to Competitor A 500,000 60,000 200 0.6 15 B 700,000 80,000 220 0.7 20 C 900,000 210 210 0.8 25 Questions: For each strategy, calculate the potential revenue without considering competitor response. Which strategy offers the highest potential revenue? Using the concept of expected value, estimate the revenue for each strategy considering the potential loss of market share due to competitor response. Construct a decision tree for Strategy A detailing the potential outcomes with and without competitor response. What is the expected value of Strategy A considering both scenarios? Which strategy carries the highest risk, given the combination of marketing costs and competitor response probability? Using sensitivity analysis, determine how much the Expected Sales would have to increase for Strategy C to be the most favorable option in terms of expected value. If TechTrend is risk-averse, which strategy would you recommend they consider? Justify your answer. Given a fixed budget of $800,000 for marketing, which strategies can TechTrend afford? Calculate the return on investment (ROI) for each strategy without considering competitor response. Which strategy offers the best ROI? Suppose TechTrend has prior data that suggests a 10% increase in market share loss for every 5% increase in competitor response probability. Recalculate the expected values based on this new information. Does the optimal strategy change? If a new market survey suggested that Strategy B’s price per unit could be increased to $240 without affecting sales volume, how would this change your recommendation? Calculate the new expected revenue for Strategy B. Submission Instructions: A 35-page Word Document including title page anda references page Must include a title page, abstract, and references. These are not counted in the page count/slide count. Must include your original Excel Sheet. Be sure to review the following prior to submitting your assignment: This assignment aligns with the following: Resources & Supports : You have free access as an APUS student. Sign in with your MyCampus Email credentials. : Watch this 3-minute video if you need guidance on submitting your assignment.
Due on Jan 18, 2026 11:59 PM