Topic: Assume you are working in the marketing department of Walmart. The compan

Topic: Assume you are working in the marketing department of Walmart. The company wants to supply a new brand of clothing. To make an informative decision, your manager asked you to estimate the percentage of customers who would be interested in the new brand. How do you approach this task? What assumptions do you need to make and what data do you need to collect? If your manager does not know anything about statistics, how would you interpret your results for him/her?
Respond to Peer Post 1 – 150-200 words
How do we approach this task?
There are three main items to consider with respect to this question:
How will we design the study such that it answers the above question?
The parameter for this study will be “Customer is likely to purchase new brand products” (Yes or No)
The population for this study is all customers who shop at stores where this product is in consideration over the course of a given period. Let’s assume the new product is seasonal, aimed at fall purchases, so we will consider the number of customers from Q3.
The study will be conducted through statistical analysis of purchase history of similar brands and products already sold at Walmart, whereby, the designer has identified the similarities through a simple random sample, e.g., group the brands by association, style, or likeness, of customers within the population of the main study (a smaller study, to complete a larger study).
What confidence must we have in the study results to deem it a successful study?
According the NEDARC, the National EMSC Data Analysis Resource Center (2019), “a confidence interval of 95% or greater is ideal”. It appears to me that, the necessary confidence interval depends on the risk tolerance of the organization e.g., size of investment (consequence), frequency of success (or failure).
How do we effectively present this information to our Management for a yes/no decision on accepting the new product?
We’ve learned that how you present your data, is every bit as important as the data itself. I would identify the structure of the study in simplest forms, and then highlight the results of the study with the confidence level achieved, being 95% or greater (as suggested by NEDARC) for final approval.
What assumptions must you make?
We will need to assume that because a customer purchased a similar brand or product, they will be just as likely to purchase this new brand or product.
What data do you need to collect?
We will need to firstly understand the comparable products to analyze among our existing purchases for said new product. Second, we will need data from all stores in consideration, during the identified time (Q3 in my example, fall products), to understand what % of customer purchases included similar products or brands.
Holmes, A., Illowsky, B., Dean, S., Hadley, K. (2017) Introductory Business Statistics. OpenStax.
NEDARC – The National EMSC Data Analysis Resource Center, U. of U. (2019, August 5). Confidence intervals. NEDARC. Retrieved May 19, 2022, from
Respond to Peer Post 2 in 150-200 words
A survey is needed to gather fashion data and client feedback to approach this task. We could perform online, social media, and Walmart customer surveys to find what clothes people need/want. What is their clothing budget? What clothes brands do they want? The survey may be expanded to predict which brands will sell the most. From the survey’s demographics, you can discover which gender/age group is more prevalent and which brand is more attractive to most customers.
The assumption is that each sample is:
~A large amount. (Statisticians ran into problems when the sample size was small, which caused inaccuracies in the confidence interval)
~Sample data should be normally distributed.
We could conduct a survey and calculate the sample mean and the sample standard deviation. The sample mean is the point estimate for the population mean. The sample standard deviation is the point estimate for the population standard deviation (OpenStax)
I would get my manager to understand statistics by creating data visualizations to help them present data more straightforwardly for the manager to comprehend. Data may be represented graphically in various ways, including bar charts, bubble clouds, box-and-whisker plots, and graphs, to mention just a few examples of these representations. When using statistics and data, make sure your data is correct so you may make assumptions based on facts. The null hypothesis is random, whereas the alternative hypothesis includes non-random observations.
Holmes, Alexander and Illowsky, Barbara and Dean, Susan (2018), Introductory Business Statistics, OpenStax, Rice University.
Respond to Peer post 3 in 150-200 words
This particular task can be approached by doing survey in which the customers can answer their preference. From these surveys, data can be gathered and organized. The “enough” sample size can be computed by knowing the total customers you have for a week, and from there gather and compute your sample size.(Ex. 5000 customers per week, and you hand out/verbally ask questions of 1000 of them, so your sample size is 1/5 of your weekly customers) Also, in choosing the those who’ll take the survey, it should be random. Questions (and assumptions) such as what brand would they prefer, what type/style of clothing, or if they even like the new brand that is being considered to be added on the store can be added to the survey. More data means a more concrete conclusion can be drawn. When presenting the results to your manager, include graphs and tables as visual for him/her to easily interpret the result. A pie chart can be really helpful to present the number of customer who prefer a new brand. Bar graphs can represent what brand or type the customers would prefer in which the higher the bar, the more likely the customer will choose it. Visuals will always help explain the statistics in such a manner that you do not offend anyone or explain the data condescendingly.

Topic: Assume you are working in the marketing department of Walmart. The compan
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