Highlights
Task
R Studio1. You are an analytics professional working for an e-commerce firm selling athletic shoes on the internet. The company collects data on products and customers to investigate the properties of shoes that sell the best and the demographics of customers who purchase the products. For each shoe model, you have data on profitability (“profitable” or “not profitable”), number of reviews, median review, price, brand (“Nike”, “Under Armor”,“Adidas”, or“Other”), production cost, outsole cost, endorsement cost, length of laces, number of eyelets, and profit per shoe (in dollars).
Suppose you want to investigate whether there is a difference in profitable and unprofitable models based on the number of reviews provided by users of the website. What is a visualization you can use to determine if there is a difference?
2. Suppose you want to investigate the relationship between the number of reviews, the price, and whether a model is profitable or unprofitable (yes/no). What is a visualization you can use?
3. Consider a histogram of the outsole cost for each shoe.
A. What is an approximate value for the range (the maximum minus the minimum value) for the average coupon value?
B. Is the distribution skewed? If so, which way?
C. The outsole cost, along with several other predictors, is going to be used in a predictive model to predict whether a shoe model will be profitable. Would you recommend a transformation of this variable for downstream analysis? If so, what transformation?
4. In an effort to understand the historical sales of shoe models, you perform a cluster analysis using k-means to determine how models group together. Below is a plot on the first two principal components. The plotting character indicates the assignment for 4 clusters. Answer the following questions based on the output below.
How many principal components are needed to explain at least 90% of the variation in the original dataset?
Which variables are most responsible for variation on PC 1?
Which variables are most responsible for variation on PC 2?
Based on the PCA plot and loadings, provide a description of the clusters:
circles
squares
triangles
pluses
5. Your team begins a project to evaluate online reviews of shoes provided by customers. Data are scraped from various websites and include the date and time of each review, shoe model, the product identification number, shoe description, price, rating (on a 5-point scale), product family, the website (e.g., target.com, amazon.com), the review text, and several other fields.
The database administrator asks how you would like data to be delivered to the analytics team for the analysis. What are some considerations that you can communicate that would help your team load the data into an analytics software such as R?
10. Consider a month's worth of data on the date/time of reviews, shoe model, and review rating. Describe four fields that you can create from the transaction data below to summarize the data by shoe model.
Time Model Review Rating
2021-01-21 10:00 AM Adidas Grand Court 4
2021-01-21 10:04 AM Allbirds Merino Wool 5
2021-01-21 11:05 AM UnderArmor Curry 9 2
2021-01-21 11:39 AM Adidas Grand Court 3
2021-01-21 01:09 PM UnderArmor Curry 9 3
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