1 Use the Sampler plugin to create the following tables and give them the specified names. (Re-open Sampler before creating each table to avoid getting one massive hierarchical table!)

  • 10 animals randomly selected without replacement ⇒ tiny-sample

  • 20 animals randomly selected without replacement ⇒ small-sample

  • 40 animals randomly selected without replacement ⇒ medium-sample

  • 80 animals randomly selected without replacement ⇒ large-sample

2 Make a bar chart of the species in the tiny-sample.

  • What animals are in the sample?

  • Create a new, random, tiny-sample, and use it to make a bar-chart. What animals are in the sample?

  • Make another tiny sample and bar chart of species. Based on these samples, how many species do you think are at the shelter?

  • Which species do you think there are the most of at the shelter?

3 What did you learn from taking multiple samples that you wouldn’t have known if you’d only taken a single sample?

4 Now use small-sample to make a bar chart of the species.

  • What animals are in the sample?

  • Create a new random sample and make another bar chart of species in the small sample. What animals are in the sample?

5 Now that you’ve seen the small sample, how has your sense of the distribution of the species changed?

6 Now use the medium sample to make a bar chart of the species. If there are about 400 animals at the shelter, how many of each species would you predict there to be?

7 Now use the large to make a bar chart of the species. If there’s anything you’d like to change about your prediction now that you’ve seen the large sample, record it here.

8 Let’s see how accurate your prediction is…​ When you’re ready, make a bar chart of Animals Table 2.

  • Which predictions were closest?

  • Which predictions were off?

  • Were there any surprises?

9 In the real world, we usually don’t have access to a whole dataset to check predictions against! How could we test…​

  • Every giraffe on the planet?

  • Everyone who has ever come in contact with a covid-positive person?

  • Every person who identifies as queer?

What strategies can we use to make sure that predictions from samples are as close to accurate as possible?

These materials were developed partly through support of the National Science Foundation, (awards 1042210, 1535276, 1648684, 1738598, 2031479, and 1501927). CCbadge Bootstrap by the Bootstrap Community is licensed under a Creative Commons 4.0 Unported License. This license does not grant permission to run training or professional development. Offering training or professional development with materials substantially derived from Bootstrap must be approved in writing by a Bootstrap Director. Permissions beyond the scope of this license, such as to run training, may be available by contacting contact@BootstrapWorld.org.