Healthcare Statistics with SPSS
Learn to analyze healthcare data using SPSS, covering data creation, import, visualization, descriptive statistics, file manipulation, and parametric testing.
Machine Learning
Explore machine learning models through hands-on tutorials in Python and Julia, covering clustering, regression, neural networks, and more. Practical examples with code provided.
Modern Linear Algebra Using Python Instead of a Textbook
Explore linear algebra concepts through hands-on Python programming, covering matrix operations, decompositions, and applications in machine learning and data analysis.
Julia
Learn Julia programming for data analysis, statistics, and linear algebra. Covers databases, plotting, environments, and advanced mathematical concepts with practical tutorials.
R Tutorials
Learn essential R skills for data analysis, visualization, and machine learning, covering statistics, deep learning, Plotly, and real-world applications like COVID-19 data extraction.
Binary Logistic Regression
Learn to perform and interpret binary logistic regression, including multivariate analysis and interactions, through a series of three concise video tutorials.
Ordinal Logistic Regression
Learn to analyze ordered categorical data using ordinal logistic regression, covering introduction, multiple regression, and the proportional odds assumption.
Multinomial Logistic Regression
Explore multinomial logistic regression, covering introduction and multiple regression concepts for analyzing categorical outcomes with more than two levels.
Introduction to Poisson Regression Models for Count Data
Learn to analyze count data using Poisson regression models, including diagnostics, goodness of fit statistics, and residual analysis techniques.
Working with StatCrunch
Learn to use StatCrunch for data analysis: importing, visualizing, and analyzing data with various statistical methods. Master creating charts, performing tests, and exporting results efficiently.
Excel Skills
Enhance data analysis skills with time-series plots, matrix-to-vector conversion, vlookup, histograms, text data import, and correlation techniques in Excel.
ECLR-R for Econometrics
Learn essential econometric techniques using R, from data import and analysis to advanced modeling like ARIMA, GARCH, and difference-in-differences, with practical examples and hands-on exercises.
Statistics
Learn fundamental probability concepts, distributions, and statistical methods through clear explanations and practical examples.
Edexcel S2
Comprehensive video series covering Edexcel A-Level S2 topics, including probability distributions, random variables, and hypothesis testing for exam preparation.
Convolution
Explore convolution through intuitive descriptions, equations, and worked examples of typical functions, covering various applications and related concepts.
Biostatistics
Explore advanced biostatistics techniques, from ANOVA to experimental design, enhancing your ability to analyze scientific data and interpret research papers effectively.
Stats Examples
Comprehensive statistical training covering key concepts, probability, distributions, hypothesis testing, and advanced analyses with step-by-step examples and practical applications.
The Statistical Process
Explore key statistical concepts including data types, sampling methods, survey design, inference, significance, and measures of central tendency and spread.
Hypothesis Testing and P-Values
Learn key concepts in statistical inference, including p-values, hypothesis testing, t-tests, and ANOVA. Develop skills to choose appropriate tests and interpret results for data-driven decision making.
Basics of Probability
Explore fundamental concepts of probability, including random variables, distributions, and Bayes' Theorem, to model uncertainty and make informed decisions.
Probability Distributions, Including Normal
Explore random variables and probability distributions, including binomial, Poisson, and normal, with practical examples and Excel illustrations for real-life modeling.