This is the work we have done so far. We are testing in SPSS. I need help figuring out the PREPARE my DATA section.

Link to the data-

https://docs.google.com/spreadsheets/d/14qbv32zr33Qs0truVdQVszsRz-KmDAse/edit?usp=sharing&ouid=100970127357673955427&rtpof=true&sd=true

Business Analyst Consultant to a Global Retail Company about Sales

You are proud to be working for a global company truly dedicated to "WOWing" their customers with superior products and services. It is well known to be one of the best at putting customers first and going above-and-beyond.

The company is seeking to understand several facts and relationships between promotional markdowns and total sales at four international stores: Munich, Dubai, London, and New York. The company collected weekly sales data for a year across the stores as well as data related to weather, fuel costs, unemployment, and costs of living.

As a business analyst for this company, your global executive team is seeking your advice on what to do next to address how promotional markdowns are related to sales. You are to help the executives make a business decision based on data and analytics. If successful, you will help improve sales and continue to improve the company's reputation.

State your research goal(s) Section 1 (Our Goals)

Our research aims to examine the relationship between promotional markdowns and total sales at four international retail locations in stores, London, New York, Munich, and Dubai. By analyzing the weekly sales data collected over for 52 weeks, we aim to gain insights that will enable the company to

1. Increase company revenue,
2. Make more meaningful investment of marketing resources,
3. Create predictable outcomes, thereby improve product planning and subsequently lower operating costs,
4. Potentially increase market share,
5. Increase shareholder value, and
6. Improve the company's reputation.

Clarify your hypotheses Section 2

Client Questions:

1. Did Total Sales for the year exceed $3 million?
   • Frequencies or Descriptives
2. Did the Average of Total Sales for the year exceed $20,000?
   • Frequencies or Descriptives or Explore
3. Was the typical variability of Total Sales greater than $10,000?
   • Frequencies or Descriptives or Explore
4. Are Total Sales for the year equal across all four Stores?
   • Frequencies or Descriptives or Explore
5. Are Total Sales from promotional Markdowns for the year equal across all five departments?
   • Frequencies or Descriptives or Explore
6. Are average Total Sales for the year on Holidays equal to average Total Sales on Non Holidays?*
   • Independent Samples T Test
7. Comparing average Total Sales across locations, was Munich the top performing store by more than $10,000?*
   • General Linear Model Univariate (One-Way ANOVA)
8. How is the Consumer Price Index (CPI) and Total Sales for the year related?*
   • Correlate-->Bivariate or Regression-->Linear
9. How are Unemployment and Total Sales for the year related?*
   • Correlate-->Bivariate or Regression-->Linear
10. How are the Temperature and Total Sales for the year related?*
    • Correlate-->Bivariate or Regression-->Linear
11. Comparing the CPI, Unemployment and Temperature, is CPI the best predictor of Total Sales for the year?*
    • Regression-->Linear
12. Is Munich the top performing store for Housewares (selling significantly more Housewares on average than other stores)?*
    • General Linear Model Univariate (One-Way ANOVA)
13. Your client is interested in you framing a question of your own. Please state a question and then form an appropriate Null and Research Hypothesis.

(Our Hypothesis)

H1. Timing of the promotions adjacent to holidays will have a greater impact on promotions compared to similar promotions not adjacent to holidays.

Null hypothesis will be promotional revenues adjacent to holidays will not have more than a 3% gain over promotions not adjacent to holidays.

H2. There will be a direct correlation between product line promotions' presumed targeted gender audience and sales of presumed gender specific product lines, compared to other weekly averages.

Automotive Promotions will have a positive correlation to Men's Clothing Sales.

Null hypothesis:Automotive Promotions will not have a positive correlation to increased Men's Clothing Sales.

Housewares promotions will have a positive correlation to increased Women's Clothing Sales.

Null hypothesis: Housewares promotions will not have a positive correlation to increased Women's Clothing Sales.

H3. Unemployment levels will not have a statistically significant impact on promotional effectiveness.

Null hypothesis:Unemployment levels will have a statistically significant impact on promotional effectiveness.

H4. Multiple promotions in one product line will outperform overall revenues compared to running an equal number of promotions in each product line.

Running twice annual Women's clothing promotions will outperform, once annual promotions for Women's clothing and once annual promotions for Housewares.

Null hypothesis: A once annual Women's clothing promotion and once annual Housewares promotions will produce better annual revenues.

Repeat tests for other combinations? Yes?

H5. Promotion weeks will produce different revenues in each territory.

Null hypothesis: Promotions will be equally productive in each territory.

H5.1 Average weekly sales revenues are equally distributed in Non-Holiday weeks?

Null hypothesis: Average weekly sales are not equally distributed in Non-Holiday weeks.

H5.2 Relative sales as a percentage of annual revenues are similar in each territory.

Null hypothesis: Percentages of categorical sales revenues differ in each terri

H6.!

Extreme weather conditions have an effect on weekly sales (extreme weather is anything outside of 2 standard deviations).

The null hypothesis would be that extreme weather conditions do not have an effect on weekly sales.

H7.!

Holidays have an effect on weekly sales.

The null hypothesis would be that holidays do not have an effect on weekly sales

H8..Could be easy to prove wrong which would be great!

Periods of high unemployment (do we have periods of relatively high unemployment) will have an effect on sales.

The null hypothesis would be high unemployment do not effect sales.

H9.

Periods of high CPI will have an effect on weekly sales.

The null hypothesis would be that CPI will not affect sales.

Prepare my data- (Need help here) What steps do you plan to take to prepare the data for analysis?

• Hint: Data used for analysis should be checked for anomalies such as outliers and data entry errors.
• Frequency analysis and/or Explore analysis of all relevant variables used in your project with discussion of any data anomalies or outliers [see Module 2-3]
• Hint: Create table that identifies the variables you are using and label each as continuous (scaled), categorical (nominal, ordinal) or counts.
• Hint:(This competency is covered in your Module 1 Assignment)

Variable Name	Variable Type (Scale, Ordinal, Nominal)
Store, Is Holiday	Categorical (Nominal)
Week, Temperature, Fuel_Price, CPI, Unemployment, MarkDown1-5, Total_Sales	Continuous (Scale)