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Covers electron microscope components, vacuum systems, aberrations, detectors, and specimen holders.

Fracture Mechanics: Crack Growth and Weakest Link

Explores fracture mechanics, crack growth, and the weakest link theory, emphasizing the statistical distribution of crack sizes and the significance of the largest crack in material failure.

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Statistical Measures: Mean, Median, and Dispersion Techniques

Discusses statistical measures of central tendency and dispersion, focusing on mean, median, and their implications in data analysis.

Probability and Statistics: Basics and Applications

Covers fundamental concepts of probability and statistics, focusing on data analysis, graphical representation, and practical applications.

Transmission Electron Microscopy: Imaging and Diffraction

Explores the operation of a Transmission Electron Microscope, covering imaging modes and lens effects.

Confidence Intervals and Hypothesis Testing

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

Understanding Statistics & Experimental Design

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

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Normal Distribution: Characteristics and Examples

Covers the characteristics and importance of the normal distribution, including examples and treatment scenarios.

Variance and Covariance: Properties and Examples

Explores variance, covariance, and practical applications in statistics and probability.

Statistical Hypothesis Testing: Unilateral and Bilateral Pairs

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

Estimating Extreme Quantiles

Covers the estimation of extreme quantiles using empirical quantiles and sample data.

Hypothesis Testing in Statistics

Explores hypothesis testing in statistics, focusing on decision-making based on sample data and controlling error probabilities.

Probability & Stochastic Processes

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.

Linear Regression: Estimation and Testing

Explores linear regression estimation, hypothesis testing, and practical applications in statistics.

Probability Theory: Midterm Solutions

Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.

Understanding Statistics & Experimental Design

Explores unequal variances, replication, power, effect size, biases, and their impact on research outcomes.