An understanding of potential customers is an essential piece of a good business model. Statistical analysis can help you understand who is interested in a potential product or service. Fred and Carrie have surveyed Portland residents regarding their laundry habits and desired services and would like you to run the numbers for them. Review the information they have collected, contained in the resource titled “Portland Laundry Statistical Data.”
Then, compile a two-to-three page report with the following components:
1. Analysis of Data
Analyze the raw data that they have collected. Using Google Sheets, create two scatter plots:
- one comparing the number of pounds of laundry a household does per week with the likelihood that they would use the service.
- another comparing a customer’s distance from Drip & Dry with the likelihood of them using the service.
Use the Project resources to learn how to find the line of best fit, also known as a trend line, which approximates the data on the scatterplot and the R-squared values to help explain how close the data is to the trend line. Explain whether or not there are meaningful correlations within the variables for each scatterplot (pounds of laundry vs. likelihood to use the service and distance vs. likelihood to use the service.)