Z-test

Formal sciences
Statistics
Statistical inference
Statistical hypothesis testing

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Related lectures (31)

Page 3 of 4

Statistical Hypothesis Testing & Error Types

Covers statistical hypothesis testing and error types in neural signals processing.

Bayesian Statistics: Hypothesis Testing and Estimation

Covers hypothesis testing, p-values, significance levels, and Bayesian estimation.

Linear and Ridge Regression

Covers linear and ridge regression, overfitting, hyperparameters, and test sets.

Hypothesis Testing and Confidence Intervals: Key Concepts

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

Analysis of Variance (ANOVA)

Covers Analysis of Variance (ANOVA) for assessing categorical variable effects on quantitative outcomes.

Property Estimation and Exponential Family

Covers test statistics, threshold values, and lower bounds for estimating properties.

Randomization tests: Understanding Experimental Results

Explores randomization tests as an alternative to t-tests for experimental analysis, using fake data to assess treatment effectiveness.

Review Session: Module 1

Introduces inferential statistics, covering sampling, central tendency, dispersion, histograms, z-scores, and the normal distribution.

Do ImageNet Classifiers Generalize?

Examines the generalization of ImageNet classifiers, safety-critical applications, overfitting, and the reliability of machine learning models.

Hypothesis Testing in Statistics

Delves into hypothesis testing, covering test statistics, critical regions, power functions, p-values, multiple testing, and non-parametric statistics.