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Probability and Statistics (Algebra 2 - Unit 11) | Math Lion

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Math Lion
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Grade Levels
9th - 12th, Homeschool
Standards
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Pages
28+ 100 Slides
$10.00
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Description

Documents are editable!!!

This unit includes PowerPoint presentations, coordinated guided notes with answers, a mid-unit quiz, and unit test covering Probability and Statistics Functions. The PowerPoint includes warm ups (do-now or bell ringer), key concepts, and examples for students to follow.

10 lessons included! The lessons are 30 - 45 minutes each.

11.1: PERMUTATIONS AND COMBINATIONS

11.2: PROBABILITY

11.3: PROBABILITY OF MULTIPLE EVENTS

11.4: CONDITIONAL PROBABILITY

11.5: PROBABILITY MODELS

11.6: ANALYZING DATA

11.7: STANDARD DEVIATION

11.8: SAMPLES AND SURVEYS

11.9: BINOMIAL DISTRIBUTION

11.10: NORMAL DISTRIBUTION

Unit Essential Questions:

• What is the difference between a permutation and a combination?

• What is the difference between experimental and theoretic probability?

• How are measures of central tendency

Total Pages
28+ 100 Slides
Answer Key
Included
Teaching Duration
3 Weeks
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Standards

to see state-specific standards (only available in the US).
Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve.
Understand statistics as a process for making inferences about population parameters based on a random sample from that population.
Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation. For example, a model says a spinning coin falls heads up with probability 0.5. Would a result of 5 tails in a row cause you to question the model?
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.

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