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Statistical Analysis: Boxplot and Normal Distribution

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

ANOVA and Factorial Experiments

Explores ANOVA, factorial experiments, and model evaluation techniques.

Descriptive Statistics: Hypothesis Testing

Introduces descriptive statistics, hypothesis testing, p-values, and confidence intervals, emphasizing their importance in data analysis.

Matlab: 3D Surface Plotting

Covers logical arrays, 3D surface plotting, parametric curves, interpolation, and fitting in Matlab.

Logistic Regression: Interpretation & Feature Engineering

Covers logistic regression, probabilistic interpretation, and feature engineering techniques.

Linear Regression Testing

Explores least squares in linear regression, hypothesis testing, outliers, and model assumptions.

Types of Variables and Multinomial Distribution

Introduces types of variables, multinomial distribution, data characteristics, shapes of densities, correlation, and data visualization methods.

Linear Regression: Statistical Inference and Regularization

Covers the probabilistic model for linear regression and the importance of regularization techniques.

Exploratory Statistics: Data Analysis Fundamentals

Covers the basics of exploratory statistics, including variables, quantiles, central tendency, dispersion, outliers, and robustness.

Robust Regression: Methods and Applications

Explores robust and resistant methods in linear models, emphasizing the importance of handling extreme observations and the implications of robustness in regression models.