Advanced Probability Theory
Kurssi
90 Opiskelijat jo ilmoittautuneet- Gain a comprehensive understanding of additional probability theory topics pertinent to data science and analytics.
- Develop proficiency with both absolutely continuous and discrete random variables.
- Grasp the principles of cumulative distribution functions and probability density functions.
- Explore and characterize the features of random variables and random vectors.
Varusta yrityksesi huipputeknologialla Data ja tekoäly asiantuntemus.
Jaa se sosiaalisessa mediassa ja suoritusarvioinnissasi
On 4 moduulia tässä kurssissa
Statistics and probability theory are fundamental tools in data analysis, decision-making, and scientific research. They provide a systematic and quantitative way to understand and interpret data, make predictions, and draw conclusions based on evidence. Now we will consider all additional topics necessary for Data Science and Data Analytics.- Course OverviewEsikatselu
- Absolutely Continuous and Discrete Random VariablesEsikatselu
- Cumulative Distribution Functions and Probability Density FunctionsEsikatselu
- Characteristics of Random VariablesEsikatselu
- Random VectorsEsikatselu
- Useful Properties of the Gaussian DistributionEsikatselu
- Challenge: Detecting Outliers Using 3-Sigma RuleEsikatselu
- General population. Samples. Population parameters.Esikatselu
- Momentum estimation. Maximum Likelihood EstimationEsikatselu
- Challenge: Estimate Parameters of Chi-square DistributionEsikatselu
- Unbiased EstimationEsikatselu
- Challenge: Checking Bias of An Estimation Using SimulationEsikatselu
- Consistent EstimationEsikatselu
- Efficient EstimationEsikatselu
- Confidence Intervals for Population ParametersEsikatselu
- Challenge: Confidence Interval for Exponential Distribution ParameterEsikatselu
- What is Statistic Hypothesis? Type 1 and Type 2 ErrorsEsikatselu
- What is P-value?Esikatselu
- Comparing Means of Two Different DatasetsEsikatselu
- Challenge: Using CLT to Compare Mean Values of Non-Gaussian DatasetsEsikatselu
- Challenge: Resampling Approach to Compare Mean Values of the DatasetsEsikatselu
- Testing the Hypothesis of Independence of Two Random VariablesEsikatselu
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