Mathew K AnalyticsLearn statsmodels with free notebooks
37 free video lessons that use statsmodels, each with a downloadable Jupyter notebook and, where needed, the dataset. Learn statsmodels by working through real examples.
29 minLesson 5
Python Data Analytics #05: Sales Forecasting for Retail Demand in Python
29 minLesson 10
Python Data Analytics #10: Retail Analytics Capstone — End-to-End Report in Python
16 minLesson 8
A/B Testing & Experiment Design That Works | Statistics #8
13 minLesson 10
Multiple Comparisons & P-Value Corrections | Statistics #10
13 minLesson 12
Multiple Regression & Model Diagnostics | Statistics #12
15 minLesson 13
Categorical Data Analysis & Chi-Square Tests | Statistics #13
15 minLesson 15
Statistics Capstone: A Full Real-World Analysis | Statistics #15
25 minLesson 1
Linear Regression from Scratch in Python | ML Algorithms #1
28 minLesson 35
Correlation and Key Driver Analysis in Market Research
20 minLesson 38
Net Promoter Score Analysis in Python for Market Research
25 minLesson 48
Seasonal Demand Forecasting Training with Python for Retail E-commerce Analytics
24 minLesson 9
Master Bayes Theorem: Real-Life Examples & Step-by-Step Probability Explained
12 minLesson 15
Hypothesis Testing Explained: Concepts, Errors, and How to Interpret P-Values in Python
17 minLesson 19
Understanding Monte Carlo Simulations in Python for Statistical Modeling and Analysis
13 minLesson 22
Understanding Covariance and Correlation: Pearson and Spearman Explained
11 minLesson 24
Understanding Multiple Linear Regression with Python’s Statsmodels Library
12 minLesson 25
Understanding Regression Diagnostics: Residuals and Key Assumptions Explained
24 minLesson 33
Understanding Stationarity, ACF, PACF, and ARIMA Fundamentals in Time Series Analysis
15 minLesson 35
Bayesian Estimation Explained: Using SciPy and PyMC for Practical Inference in Python
12 minLesson 40
Comprehensive Time Series Forecasting Project: From Data Preparation to Deployment
14 minLesson 6
Master Data Cleaning and Preparation with Pandas in Python for Effective Bible Study Analysis
13 minLesson 18
Understanding Heatmaps and Correlation Matrices with Seaborn for Data Analysis
13 minLesson 30
Creating Interactive Choropleth Maps with Plotly for Python Geospatial Visualization
14 minLesson 31
3 - Interactive Maps with Folium
14 minLesson 19
Understanding Stationarity and the Augmented Dickey-Fuller Test in Time Series Analysis
13 minLesson 20
Understanding Autocorrelation and Partial Autocorrelation in Time Series Analysis
10 minLesson 21
Seasonal Decomposition in Python: Techniques for Time Series Analysis and Interpretation
15 minLesson 22
Understanding Autoregressive, Moving Average, and ARMA Models for Time Series Forecasting
17 minLesson 24
Seasonal ARIMA and SARIMAX in Python: A Guide to Time Series Forecasting
12 minLesson 25
Understanding Exponential Smoothing and Holt-Winters Forecasting Models in Python
14 minLesson 26
Understanding Model Diagnostics and Residual Analysis for Time Series Forecasting in Python
15 minLesson 32
Walk-Forward Validation in Python: A Clear Guide for Time Series Model Evaluation
10 minLesson 42
Using Multilayer Perceptrons for Time Series Forecasting in Christian Analytics
24 minLesson 21
Time Series Decomposition Techniques for Accurate Demand Forecasting in Supply Chain
31 minLesson 22
Moving Average and Exponential Smoothing Models in Supply Chain Analytics
23 minLesson 23
ARIMA and SARIMA for Demand Forecasting in Supply Chains
21 minLesson 31