Understanding Statistics & Experimental Design

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Related lectures (30)

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Red Influence: Attractiveness, Desirability, and Status

Explores the effects of red on attractiveness, desirability, and status, emphasizing statistical analysis and the challenges of replication and publication bias.

Statistics & Experimental Design

Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.

Confidence Intervals and Hypothesis Testing

Explores confidence intervals, hypothesis testing, and decision-making using test statistics and p-values.

Hypothesis Testing and Confidence Intervals: An Overview

Covers hypothesis testing, confidence intervals, and their applications in statistics.

Understanding Statistics & Experimental Design

Covers statistics, experimental design, errors, distributions, implications of sample size, and null results.

Hypothesis Testing and Confidence Intervals: Key Concepts

Provides an overview of hypothesis testing and confidence intervals in statistics, including practical examples and key concepts.

Understanding Statistics & Experimental Design

Provides an overview of basic probability theory, ANOVA, t-tests, central limit theorem, metrics, confidence intervals, and non-parametric tests.

Statistical Hypothesis Testing: Unilateral and Bilateral Pairs

Explores unilateral and bilateral pairs in statistical hypothesis testing, covering critical values, test statistics, and p-values.

Understanding Statistics & Experimental Design

Covers basic probability theory, signal detection theory, statistics, and meta-statistics, explaining effect sizes, power, and hypothesis testing.

Probability Distributions in Environmental Studies

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.