Bootstrap Distribution and Confidence Interval for a Population Mean – Apply It 1

  • Create a bootstrap distribution for a sample mean
  • Find and describe a bootstrap percentile confidence interval for a population mean

Recall that we are working with a sample of kWh/100 miles ratings for [latex]10[/latex] electric cars that were randomly selected from the population of all the 2021 models of electric cars sold in the United States, as reported by the EPA. The sample data are shown in the following table.

Observation Car model kWh/100 miles
1 Porsche Taycan 4S Cross Turismo 45
2 Volkswagen ID.4 Pro S 35
3 Hyundai Kona Electric 27
4 Ford Mustang Mach-E RWD 34
5 Tesla Model S Performance 35
6 Tesla Model X Performance 35
7 Nissan Leaf SV/SL 32
8 Tesla Model S Plaid 33
9 Volkswagen ID.4 Pro 34
10 BMW i3s
To calculate a bootstrap confidence interval, let’s use the statistical tool: https://istats.shinyapps.io/Boot1samp/. 

Step 1: For the “Enter Data” option, choose “Your Own.”
Step 2: Type the values from the sample into the “Enter Observations” box. Separate the data values by spaces or commas.
Step 3: Recall the values for the sample are: 45, 35, 27, 34, 35, 35, 32, 33, 34, and 30.
Step 4: For the “Statistic of Interest” option, select “Mean.”
Step 5: On the left-hand side of the display, under “Select how many bootstrap samples you want to generate,” click on “1,000.” Then, click on “Draw Bootstrap Sample(s).”
Step 6: You should see the bootstrap distribution in the lower part of the right-hand side of the display.