In this activity, students will explore the Law of Large Numbers. By examining unfair models, they will expand their understanding of probability. They predict the weighting of an unfair model by analyzing experimental data and distributions. They will also formulate and test a hypothesis on the fairness of models.

In this activity, students can use the Probability Simulation application to roll a fair die and explore the Law of Large Numbers. They will conduct probability experiments that involve tossing a fair die, graph the results, compare the experimental probability to its theoretical probability and see how the Law of Large Numbers affects the results.

Samples and ProbabilityType of Unit: ConceptualPrior KnowledgeStudents should be able to:Understand the concept of a ratio.Write ratios as percents.Describe data using measures of center.Display and interpret data in dot plots, histograms, and box plots.Lesson FlowStudents begin to think about probability by considering the relative likelihood of familiar events on the continuum between impossible and certain. Students begin to formalize this understanding of probability. They are introduced to the concept of probability as a measure of likelihood, and how to calculate probability of equally likely events using a ratio. The terms (impossible, certain, etc.) are given numerical values. Next, students compare expected results to actual results by calculating the probability of an event and conducting an experiment. Students explore the probability of outcomes that are not equally likely. They collect data to estimate the experimental probabilities. They use ratio and proportion to predict results for a large number of trials. Students learn about compound events. They use tree diagrams, tables, and systematic lists as tools to find the sample space. They determine the theoretical probability of first independent, and then dependent events. In Lesson 10 students identify a question to investigate for a unit project and submit a proposal. They then complete a Self Check. In Lesson 11, students review the results of the Self Check, solve a related problem, and take a Quiz.Students are introduced to the concept of sampling as a method of determining characteristics of a population. They consider how a sample can be random or biased, and think about methods for randomly sampling a population to ensure that it is representative. In Lesson 13, students collect and analyze data for their unit project. Students begin to apply their knowledge of statistics learned in sixth grade. They determine the typical class score from a sample of the population, and reason about the representativeness of the sample. Then, students begin to develop intuition about appropriate sample size by conducting an experiment. They compare different sample sizes, and decide whether increasing the sample size improves the results. In Lesson 16 and Lesson 17, students compare two data sets using any tools they wish. Students will be reminded of Mean Average Deviation (MAD), which will be a useful tool in this situation. Students complete another Self Check, review the results of their Self Check, and solve additional problems. The unit ends with three days for students to work on Gallery problems, possibly using one of the days to complete their project or get help on their project if needed, two days for students to present their unit projects to the class, and one day for the End of Unit Assessment.

Students will compare expected results to actual results by first calculating the probability of an event, then conducting an experiment to generate data. They will use an interactive to simulate a familiar event—rolling a number cube. Students will also be introduced to terminology.Key ConceptsThis lesson takes an informal look at the Law of Large Numbers through comparing experimental results to expected results.There is variability in actual results.Probability terminology is introduced:theoretical probability: the ratio of favorable outcomes to the total number of possible equally-likely outcomes, often simply called probabilityexpected results: the results based on theoretical probabilityexperimental probability: the ratio of favorable outcomes to the total number of trials in an experimentactual results: the results based on experimental probabilityoutcome: a single possible resultsample space: the set of all possible outcomesexperiment: a controlled, repeated process, such as repeatedly tossing a cointrial: each repetition in an experiment, such as one coin tossevent: a set of outcomes to which a probability is assignedGoals and Learning ObjectivesPredict results using ratio and proportion.Compare expected results to actual results.Understand that the actual results get closer to the expected results as the number of trials increase.

Use simulation on the TI-83 graphing calculator to teach students about the distribution of sample proportions, distribution of sample means, the Central Limit Theorem, normal probability plots, and the Law of Large Numbers. Pick and choose topics from within this lengthy activity. Instructions include step-by-step calculator keystrokes as well as calculator screenprints.

This lesson explains how the Law of Large Numbers works in probability and how it can be used to find predictable patterns in data. Includes downloadable study guide with exercises - guide also covers other topics. [6:24]

In this activity, students use simulation to justify the concept of the Law of Large Numbers. They understand that as the sample size increases, the relative frequency of which an event occurs approaches the probability of that event happening. Students investigate the binomial and geometric probability functions, and determine the mean and standard deviation.

This 9-minute video lesson provides an introduction to the law of large numbers. [Statistics playlist: Lesson 27 of 85]

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This is a resource for many topics in probability and statistics. Click on the topic of your choice for an explanation. The sites you will be linked to are quite extensive. A degree of higher-level math is necessary for understanding some of these sites.