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 Probability:
- Interpreting probability, including long-run relative frequency interpretation
- 'Law of Large Numbers' concept
- Addition rule, multiplication rule, conditional probability, and independence
- Discrete random variables and their probability distributions, including binomial and geometric
- Simulation of random behavior and probability distributions
- Mean (expected value) and standard deviation of a random variable and linear transformation of a random variable
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Combining independent random variables:
- Notion of independence versus dependence
- Mean and standard deviation for sums and differences of independent random variables
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The Normal distribution:
- Properties of the Normal distribution
- Using tables of the Normal distribution
- The Normal distribution as a model for measurements
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Sampling distributions:
- Sampling distribution of a sample proportion
- Sampling distribution of a sample mean
- Central Limit Theorem
- Sampling distribution of a difference between two independent sample proportions
- Sampling distribution of a difference between two independent sample means
- Simulation of sampling distributions
- t-distribution
- Chi-square distribution
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