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MATH 336. Data Analysis and Probability for K-8 Teachers

Credits: 3
Department: Mathematics
Description: Data collection and organization; measures of central tendency and variance; inferences and convincing arguments; subjective, theoretical, experimental, and conditional probability; simulation; counting principles; mathematical expectation. Techniques, technology, and current trends in the teaching and learning of data analysis and probability.
Prerequisites: MATH 112, MATH 171, MATH 330
Semester Offered: DEMAND
Grading Method: ABCDF

Student Learning Outcomes

1. Organize and summarize data in order to read and interpret graphs.
2. Describe data numerically using measures of center, position, spread, and equations.
3. Compute and interpret probabilities using empirical and theoretical methods.
4. Apply rules of probability to discrete and continuous distributions.
5. Produce data through sampling and experiments.
6. Apply rules of statistical inference to draw conclusions about populations.

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