Statistics For Decision Making
Statistical Decision Making is a set of quantitative methods for reaching optimal decisions. It is regarded as the cognitive process resulting in the selection of a belief or a course of action among several alternative possibilities. In this course we will learn about various models in decision making, its error estimation and the cost of the errors.
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Statistics For Decision Making
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Includes
  • 217 knowledge based questions
  • Lifetime access
About the Course

In this course, you will learn about Bayes Theorem and decision making using Bayes Theorem, designing and customizing the Bayesian theorem to work with more than 2 features and cost estimation for errors.

Course Objectives

Upon successful completion of the course, the learner will be able to

  • Master the various concepts in Statistical Decision Making.

  • Learn how Statistical Decision Making plays an important role in prediction and decision making in AI and ML algorithms.

Course Content
Bayes Theorem and Bayesian Decision Making

In this topic, you will learn about how conditional probability is used to derive Bayes Theorem and decision making using Bayes Theorem.

  • 2 Hrs
  • 72 Problems
Multiple Features and Multivariate Statistics

In this topic, you will learn about designing and customizing the Bayesian theorem to work with more than 2 features.

  • 1 Hrs 30 Mins
  • 59 Problems
Decision Regions and Decision Boundaries, Multi-Dimensional Decision Boundaries

In this topic, you will learn about how to create decision region classification by deriving Decision Boundaries and multidimensional Decision Boundaries.

  • 15 Mins
  • 15 Problems
Cost of Errors and Estimation of Errors, Regression

In this topic, you will learn about how to calculate the cost of error and how to do an estimation of errors.

  • 1 Hrs
  • 41 Problems
Applications of Statistical Modelling in ML

In this topic, you will learn about the application of Statistical Decision Making in the field of AI and ML.

  • 1 Hrs
  • 30 Problems
You will Learn through our Scientifically Designed & Proven 5 Step Practice Oriented Learning Process
iLearn
In this session, you will find video lectures and other resources to learn the concepts.
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In this session, you will start designing and creating your own programs.
iExplore
In this session, you will find interesting set of activities which will make you explore more on the specific topic.
iAssess
In this session, you will have activities to self assess your knowledge and skills on the specific topic.
iAnalyse
In this session, you will find varieties of exercises to improve your code analysis, testing and debugging skills.
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Harihara Budra P, XII std

Harihara Budra P, XII std
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