Lectures related to Evolution of Press: Challenges and Transformations

Covers the reliability of observational and experimental studies, participant selection, data bias, and result accuracy.

Explores the impact of bias in machine learning models and strategies to mitigate risks.

Covers ethical considerations in NLP, focusing on bias, toxicity, and misinformation.

Covers criteria for estimating parameters, emphasizing the importance of consistency, bias, variance, and efficiency of estimators.

Explores Signal Detection Theory and its impact on decision-making processes in statistics and experimental design.

Introduces supervised learning with k-NN and decision trees, covering techniques, examples, and ensemble methods.

Discusses the multidimensional nature of teaching evaluations and offers tips for formulating effective questions.