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Lecture
Understanding Statistics & Experimental Design
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Related lectures (28)
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Statistics & Experimental Design
Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.
Sampling Theory: Statistics for Mathematicians
Covers the theory of sampling, focusing on statistics for mathematicians.
Normal Distribution: Characteristics and Examples
Covers the characteristics and importance of the normal distribution, including examples and treatment scenarios.
Understanding Statistics & Experimental Design
Explores unequal variances, replication, power, effect size, biases, and their impact on research outcomes.
Normal Distribution: Characteristics and Z-scores
Explores normal distribution characteristics, Z-scores, probability in inferential statistics, sample effects, and binomial distribution approximation.
Elements of Statistics: Probability and Random Variables
Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.
Probability Distributions in Environmental Studies
Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.
Elements of Statistics: Probability, Distributions, and Estimation
Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.
Probability and Statistics
Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
Probability and Statistics
Covers probability distributions, moments, and continuous random variables.
