February 28, 2012

This activity allows students to practice taking simple random samples, stratified random samples, systematic random samples, and cluster random samples in an archaeological setting. Additionally, students compare the performance of simple random sampling and stratified random sampling within the context of a specific archaeological problem.

- Mathematics > General
- Mathematics > Applied Mathematics
- Mathematics > Data Analysis & Probability
- Mathematics > Problem Solving
- Mathematics > Statistics
- Education > General

- Grade 9
- Grade 10
- Grade 11
- Grade 12

Represent data with plots on the real number line (dot plots, histograms, and box plots).

Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.

Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

Understand statistics as a process for making inferences about population parameters based on a random sample from that population.

Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.

Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through the use of simulation models for random sampling.

Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant.

Represent data with plots on the real number line (dot plots, histograms, and box plots).

Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.

Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

Understand statistics as a process for making inferences about population parameters based on a random sample from that population.

Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.

Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through the use of simulation models for random sampling.

Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant.