1. Using Bootstrapping to Teach Statistical Concepts
Tom Bowler
Minitab Inc.

2. Bootstrapping is a resampling method where repeated samples are taken (with replacement) from a column of data, to estimate the sampling distribution of a statistic of interest.
Resampling methods have grown in popularity in academia to help students understand statistical concepts.
Bootstrapping can help teach confidence intervals, sampling distributions, and the central limit theorem.

3. Today we’ll be using…

4. Lumber Mill example Wood beams have a target length of 100 cm
If the average length exceeds 101.5, the mill wastes material and loses money
If the average length falls below 98.5,
customers complain

5. Lumber Mill example
What’s the mean & median length of the population? BeamLength.MTW from
Manager randomly selects 50 beams and measures their length

6. Bootstrap concept (1-sample mean)
Collect a random sample of size n
Draw n observations from that sample (randomly, with replacement) to create a bootstrap sample
Calculate the mean for the bootstrap sample
Repeat steps 2-3 many times to build a bootstrap distribution
Use percentiles of the bootstrap distribution to obtain a confidence interval

7. Lid Torque example
An assembly line uses two machines to seal jars with a twist-off lid
To ensure consistency for customers opening the jars, an engineer wants both machines to apply the same amount of torque
She measures the torque needed to twist off the caps of 68 jars (CapTorque.MTW)

8. Want to try Express 1. 5 for free. Visit minitab
Want to try Express 1.5 for free? Visit minitab.com/express

9. If you already have Minitab Express… “Check for Updates”

10. Want to try Express 1. 5 for free. Visit minitab
Want to try Express 1.5 for free? Visit minitab.com/express