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Lecture
Exploratory Statistics: Data Analysis Fundamentals
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Related lectures (26)
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Hypothesis Testing and Confidence Intervals: Key Concepts
Provides an overview of hypothesis testing and confidence intervals in statistics, including practical examples and key concepts.
Hypothesis Testing: Q-Q Plots and Non-Parametric Tests
Covers hypothesis testing, Q-Q plots, and non-parametric tests in statistics.
Data Analysis: Correlation Measures
Covers the basics of data analysis, focusing on statistical concepts and correlation measures.
Sampling strategies
Explores research process, variable types, causality vs correlation, and sampling strategies.
Statistics: Hypothesis Testing & Confidence Intervals
Covers hypothesis testing, confidence intervals, data distributions, and statistical significance in data analysis.
Statistical Inference: Confidence Intervals
Covers the construction of approximate confidence intervals using the central limit theorem for large sample sizes.
Describing Data: Statistics & Uncertainty
Introduces descriptive statistics, uncertainty quantification, and variable relationships, emphasizing the importance of statistical interpretation and critical analysis.
Introduction to Comparison Statistics
Introduces comparison statistics, error rates, hypothesis testing, and real-life examples of treatment effectiveness and weightlifting analysis.
Describing Data: Statistics and Hypothesis Testing
Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.
Statistics & Experimental Design
Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.
