Lectures related to Data Analysis Techniques: Amplitude Shift Keying and Graphical Methods

Statistics: Exploratory Data Analysis

Introduces statistics basics, including data analysis and probability theory, emphasizing central tendency, dispersion, and distribution shapes.

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.

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.

Data Science Visualization with Pandas

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Introduction to Data Science

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Statistical Analysis: Boxplot and Normal Distribution

Introduces statistical analysis concepts like boxplot and normal distribution using real data examples.

Probability and Statistics: Basics and Applications

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

Probability and Statistics

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.

Designing Learning Experiences: CS411 Class Project

Introduces the CS411 Class Project, where students design and test a lesson using learning theories.

Probabilities and Statistics: Key Theorems and Applications

Discusses key statistical concepts, including sampling dangers, inequalities, and the Central Limit Theorem, with practical examples and applications.

Data Visualization: Excel Charts

Covers the basics of creating and customizing charts in Excel.

Reservoirs and Dams: Hydraulic Construction and Sizing

Explores sizing reservoirs and dams using cumulative flow curves and tank dimensioning for dry and rainy periods.

Continuous Random Variables

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

Vectors of Random Variables: Empirical Distributions

Discusses vectors of random variables and empirical distributions, including their properties and significance in statistics.

Confidence Intervals and Hypothesis Testing

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

Quantum Uncertainty: Measurement and Probability

Delves into quantum uncertainty in measurements and probabilities, contrasting classical and quantum predictions.

Probability Distributions: Central Limit Theorem and Applications

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Turbulence: Numerical Flow Simulation

Explores turbulence characteristics, simulation methods, and modeling challenges, providing guidelines for choosing and validating turbulence models.

Elements of Statistics: Probability and Random Variables

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.