Discrete Random Variable Course
This course equips you to handle discrete random variables for count data analysis. You will construct empirical pmfs, fit and validate Binomial, Poisson, and Negative Binomial distributions using MLE and moments methods, perform goodness-of-fit tests like chi-square and rootograms, assess overdispersion, quantify uncertainty, and transform probabilistic results into actionable business recommendations with real-world applications.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain expertise in discrete random variables through this targeted course, progressing from data gathering and empirical pmfs to selecting, fitting, and validating Binomial, Poisson, and Negative Binomial models. Compute essential probabilities, analyse count data, evaluate model fit, measure uncertainty, and convey practical insights to stakeholders with business-focused examples.
Elevify advantages
Develop skills
- Model count data by fitting Binomial, Poisson, and Negative Binomial distributions efficiently.
- Estimate parameters using MLE and method of moments on actual count datasets.
- Construct empirical pmfs through sampling, count summarisation, and data visualisation.
- Validate models with chi-square tests, rootograms, and checks for overdispersion.
- Convert probabilities into business decisions, such as addressing churn and zero-purchase risks.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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