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Introduction to Probability - STAT 201

Covers sample spaces, counting, conditional probability, independence, random variables, distributions, expectation, and basic statistical applications.

Study Tools

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Study guides

7

2 Counting Techniques

Learn how to count finite outcomes systematically and use addition, multiplication, permutations, combinations, and equally likely probability models to solve counting problems.
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4 Random Variables and Probability Distributions

A structured guide to modeling uncertainty with random variables, probability distributions, distribution functions, expected value, variability, and common discrete and continuous models.
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7 Basic Statistical Applications

A structured introduction to probability, descriptive statistics, random variables, sampling, simulation, and responsible interpretation of statistical results.
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1 Probability Foundations and Sample Spaces

A structured introduction to probability that develops sample spaces, events, probability rules, counting methods, dependence, and reliable problem-solving techniques.
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3 Conditional Probability and Independence

A progressive guide to conditional probability, multiplication, partitions, Bayes’ theorem, and the distinctions among different forms of independence.
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6 Common Probability Models

A structured guide to identifying, applying, and comparing common discrete and continuous probability models, including their assumptions, formulas, and key measures of center and spread.
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5 Expectation and Variability

A progressive guide to expectation, variance, standard deviation, covariance, and sums of random variables, with formulas, examples, applications, and common errors to avoid.
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Quizzes

7

1 Probability Foundations and Sample Spaces

A medium-difficulty quiz on probability experiments, sample spaces, events, probability rules, dependence, counting, and empirical probability. The questions emphasize applying definitions and selecting appropriate methods.
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3 Conditional Probability and Independence

A medium-difficulty quiz on conditional probability, multiplication rules, partitions, total probability, Bayes’ theorem, and independence. Questions progress from foundational understanding to more demanding application.
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6 Common Probability Models

A 14-question quiz on selecting, interpreting, and applying common probability models, including discrete and continuous distributions, Bernoulli-based models, sampling models, event-count models, waiting-time models, normal approximations, and expectation and variance.
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5 Expectation and Variability

A medium-difficulty quiz on expectation, variance, standard deviation, covariance, sums of random variables, and sample statistics. Questions progress from foundational interpretation to applied calculation and explanation.
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4 Random Variables and Probability Distributions

A medium-difficulty quiz on random variables, probability distributions, probability functions, common discrete and continuous models, and expectation and variability. The questions emphasize interpreting definitions, checking assumptions, and applying formulas.
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7 Basic Statistical Applications

A 14-question assessment on probability, data summaries, distributions, sampling, and simulation. The questions progress from foundational recognition to medium-difficulty application and explanation.
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2 Counting Techniques

A medium-difficulty quiz on addition and multiplication principles, factorials, permutations, combinations, and finite probability. The questions progress from foundational recognition to applied counting and probability problems.
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Flashcards

7

1 Probability Foundations and Sample Spaces

A focused set of flashcards covering experiments, sample spaces, events, probability rules, dependence, counting, and empirical probability.
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2 Counting Techniques

Review the addition and multiplication principles, factorials, permutations, combinations, and their use in equally likely finite-probability problems.
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7 Basic Statistical Applications

A focused review of probability, data summaries, distributions, sampling, simulation, and sound statistical interpretation.
Flashcards · Updated

4 Random Variables and Probability Distributions

Study the definitions, probability functions, common distributions, summary measures, and modeling assumptions used for random variables and probability distributions.
Flashcards · Updated

3 Conditional Probability and Independence

A focused review of conditional probability, multiplication and total-probability rules, Bayes’ theorem, independence, and related event relationships.
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6 Common Probability Models

A focused review of discrete and continuous probability models, their assumptions, probability formulas, key parameters, and appropriate applications.
Flashcards · Updated

5 Expectation and Variability

Review expectation, variance, standard deviation, covariance, sums of random variables, and their sample counterparts.
Flashcards · Updated