Coursera – Bayesian Statistics Specialization

Coursera - Bayesian Statistics Mixture Models/04_applications-of-mixture-models/02_clustering/01_mixture-models-for-clustering.mp4

Coursera - Bayesian Statistics Mixture Models/01_basic-concepts-on-mixture-models/03_definition-of-mixture-models/01_basic-definitions.mp4

Coursera - Bayesian Statistics Capstone Project/03_bayesian-location-mixture-of-ar-p-model/01_week-3/02_full-conditional-distributions-of-model-parameters.mp4

Coursera - Bayesian Statistics Mixture Models/02_maximum-likelihood-estimation-for-mixture-models/01_the-em-algorithm-for-mixture-models/01_em-for-general-mixtures.mp4

Coursera - Bayesian Statistics Mixture Models/04_applications-of-mixture-models/03_classification/01_mixture-models-and-naive-bayes-classifiers.mp4

Coursera - Bayesian Statistics Time Series Analysis/02_week-2-the-ar-p-process/01_the-general-ar-p-process/01_definition-and-state-space-representation.mp4

Coursera - Bayesian Statistics Time Series Analysis/03_week-3-normal-dynamic-linear-models-part-i/02_bayesian-inference-in-the-ndlm-part-i/01_filtering.mp4

Coursera - Bayesian Statistics Time Series Analysis/02_week-2-the-ar-p-process/01_the-general-ar-p-process/02_examples.mp4

Coursera - Bayesian Statistics Time Series Analysis/04_week-4-normal-dynamic-linear-models-part-ii/01_seasonal-ndlms/01_fourier-representation.mp4

Coursera - Bayesian Statistics Mixture Models/01_basic-concepts-on-mixture-models/04_likelihood-function-for-mixture-models/05_parameter-identifiability.mp4

Coursera - Bayesian Statistics Capstone Project/01_bayesian-conjugate-analysis-for-autogressive-time-series-models/01_week-1/04_model-formulation.mp4

Coursera - Bayesian Statistics Mixture Models/04_applications-of-mixture-models/01_density-estimation/01_density-estimation-using-mixture-models.mp4

Coursera - Bayesian Statistics Mixture Models/01_basic-concepts-on-mixture-models/04_likelihood-function-for-mixture-models/04_the-likelihood-function.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/03_priors-and-models-for-discrete-data/03_bernoulli-binomial-data/05_data-analysis-example-in-excel.mp4

Coursera - Bayesian Statistics Techniques and Models/02_markov-chain-monte-carlo-mcmc/02_4-metropolis-hastings/02_demonstration.mp4

Coursera - Bayesian Statistics Time Series Analysis/04_week-4-normal-dynamic-linear-models-part-ii/03_case-studies/01_eeg-data.mp4

Coursera - Bayesian Statistics Time Series Analysis/04_week-4-normal-dynamic-linear-models-part-ii/03_case-studies/02_google-trends.mp4

Coursera - Bayesian Statistics Techniques and Models/03_common-statistical-models/03_8-anova/01_introduction-to-anova.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/02_statistical-inference/03_bayesian-inference/05_lesson-5-4-posterior-intervals.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/03_priors-and-models-for-discrete-data/04_poisson-data/01_lesson-8-1-poisson-data.mp4

Coursera - Bayesian Statistics Techniques and Models/01_statistical-modeling-and-monte-carlo-estimation/03_2-bayesian-modeling/03_posterior-derivation.mp4

Coursera - Bayesian Statistics Techniques and Models/02_markov-chain-monte-carlo-mcmc/02_4-metropolis-hastings/01_algorithm.mp4

Coursera - Bayesian Statistics Mixture Models/05_practical-considerations/01_computational-considerations-for-mixture-models/01_numerical-stability.mp4

Coursera - Bayesian Statistics Techniques and Models/01_statistical-modeling-and-monte-carlo-estimation/03_2-bayesian-modeling/01_components-of-bayesian-models.mp4

Coursera - Bayesian Statistics Capstone Project/02_model-selection-criteria/01_week-2/01_aic-and-bic-in-selecting-the-order-of-ar-process.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/02_statistical-inference/02_frequentist-inference/03_lesson-4-2-likelihood-function-and-maximum-likelihood.mp4

Coursera - Bayesian Statistics Techniques and Models/04_count-data-and-hierarchical-modeling/03_11-hierarchical-modeling/01_correlated-data.mp4

Coursera - Bayesian Statistics Techniques and Models/03_common-statistical-models/03_8-anova/02_one-way-model-using-jags.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/02_statistical-inference/03_bayesian-inference/03_lesson-5-2-inference-example-bayesian.mp4

Coursera - Bayesian Statistics Techniques and Models/01_statistical-modeling-and-monte-carlo-estimation/04_3-monte-carlo-estimation/01_monte-carlo-integration.mp4

Coursera - Bayesian Statistics Techniques and Models/03_common-statistical-models/04_9-logistic-regression/02_jags-model-logistic-regression.mp4

Coursera - Bayesian Statistics Techniques and Models/01_statistical-modeling-and-monte-carlo-estimation/02_1-statistical-modeling/02_modeling-process.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/04_models-for-continuous-data/05_linear-regression/02_linear-regression-in-r.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/04_models-for-continuous-data/05_linear-regression/03_linear-regression-in-excel-analysis-toolpak.mp4

Coursera - Bayesian Statistics Techniques and Models/02_markov-chain-monte-carlo-mcmc/02_4-metropolis-hastings/04_random-walk-example-part-2.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/01_probability-and-bayes-theorem/03_bayes-theorem/02_lesson-2-2-bayes-theorem.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/04_models-for-continuous-data/05_linear-regression/04_linear-regression-in-excel-statplus-by-analystsoft.mp4

Coursera - Bayesian Statistics Techniques and Models/04_count-data-and-hierarchical-modeling/02_10-poisson-regression/02_jags-model-poisson-regression.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/03_priors-and-models-for-discrete-data/03_bernoulli-binomial-data/04_data-analysis-example-in-r.mp4

Coursera - Bayesian Statistics Techniques and Models/01_statistical-modeling-and-monte-carlo-estimation/03_2-bayesian-modeling/04_non-conjugate-models.mp4

Coursera - Bayesian Statistics Techniques and Models/01_statistical-modeling-and-monte-carlo-estimation/03_2-bayesian-modeling/02_model-specification.mp4

Coursera - Bayesian Statistics Capstone Project/01_bayesian-conjugate-analysis-for-autogressive-time-series-models/01_week-1/08_prediction-for-ar-models.mp4

Coursera - Bayesian Statistics Techniques and Models/03_common-statistical-models/02_7-linear-regression/04_model-checking.mp4

Coursera - Bayesian Statistics Techniques and Models/03_common-statistical-models/02_7-linear-regression/01_introduction-to-linear-regression.mp4

Coursera - Bayesian Statistics Mixture Models/01_basic-concepts-on-mixture-models/04_likelihood-function-for-mixture-models/01_hierarchical-representations.mp4

Coursera - Bayesian Statistics From Concept to Data Analysis/01_probability-and-bayes-theorem/02_probability/02_lesson-1-1-classical-and-frequentist-probability.mp4

Coursera - Bayesian Statistics Techniques and Models/01_statistical-modeling-and-monte-carlo-estimation/02_1-statistical-modeling/01_objectives.mp4

Coursera - Bayesian Statistics Techniques and Models/04_count-data-and-hierarchical-modeling/03_11-hierarchical-modeling/06_linear-regression-example.mp4

Coursera - Bayesian Statistics Time Series Analysis/02_week-2-the-ar-p-process/01_the-general-ar-p-process/04_simulating-data-from-an-ar-p.mp4

Coursera - Bayesian Statistics Techniques and Models/02_markov-chain-monte-carlo-mcmc/05_6-assessing-convergence/01_trace-plots-autocorrelation.mp4