Unit 8: Data Sets, Distributions, and Sampling
Students explore key statistical concepts including dot plots, histograms, measures of center and variability, sampling, and probability.
Worksheets
Every sheet has an answer key. Free to print, no login.
What this unit covers
A Dot Plots and Histograms ยท 3 lessons
Goals
- Describe a distribution represented by a dot plot, including informal observations about its center and spread.
- Interpret a histogram to answer statistical questions about a data set.
Lessons
- Representing Data
- Using Dot Plots to Answer Statistical Questions
- Interpreting Histograms
B Measures of Center and Variability ยท 4 lessons
Goals
- Calculate and interpret the mean and mean absolute deviation (MAD) of a data set.
- Calculate and interpret the median and interquartile range (IQR) of a data set.
Lessons
- The Mean
- Variability and MAD
- The Median
- Box Plots and Interquartile Range
C Sampling ยท 5 lessons
Goals
- Describe methods to obtain a random sample from a population, and explain why it is representative of the population.
- Explain why samples are necessary and describe a sample and population for a given statistical question.
- Use the mean of a random sample to make inferences about the population.
Lessons
- Larger Populations
- What Makes a Good Sample?
- Sampling in a Fair Way
- Estimating Population Measures of Center
- More about Sampling Variability (Optional)
D Probability ยท 5 lessons
Goals
- Describe a multi-step experiment that could be used to simulate a compound event in a real-world situation, and justify that it represents the situation.
- Interpret or create a list, table, or tree diagram that represents the sample space of a compound event, and use the sample space to write the probability for an event.
- Use the results from a repeated experiment to estimate the probability of an event, and justify the estimate.
- Use the sample space to determine the probability of an event, and express it as a fraction, decimal, or percentage.
Lessons
- What Are Probabilities?
- Estimating Probabilities through Repeated Experiments
- Keeping Track of All Possible Outcomes
- Multi-step Experiments
- Designing Simulations