Statistical Methods for Decision Making
Boost your knowledge through this Statistical Methods for Decision Making course and embark on your Data Science career. Grasp the concepts of sampling, distribution hypothesis testing, error types, and ANOVA techniques for free.
4.44
Intermediate
3.0 Hrs
62.4K+
Ratings
Level
Learning hours
Learners
Skills you’ll Learn
About this course
The Statistical Methods for Decision Making course aims to give you the knowledge to understand sampling, normal distributions, hypothesis testing, and its different types, type 1 and type 2 errors, chi-square testing, and ANOVA. The course will fix the concepts in your mind through demonstrated examples and solved samples for the aforesaid concepts. You will have to take up the quiz/assessment at the end of the course to test your skills and evaluate your gains to secure the certificate. Upon completing this free, self-paced, intermediate's guide to Statistical Methods for Decision Making, you can embark on your Data Science and Business Analytics career with a professional Post Graduate certificate and learn various concepts with millions of aspirants worldwide!
Read More
Course Outline
Sampling
You will learn and understand edge detection and sharpening in the sampling technique of Computer Vision with example to represent an image in this section.
Normal Distribution
This section explains the central theorem and then later looks at how samples and data are distributed. We shall also look at how supervised learning classifies the data later in this section, after which we will understand future predictions for EV sales.
Hypothesis Testing
We shall understand how to assume characteristics of a population and later understand Null and Alternative hypotheses concepts in this section.
Type 1 and Type 2 errors
This section discusses errors rejecting and not rejecting null hypotheses at the right instances. We shall look into the causes of why the actions are not performed right and also understand how to bring them back in the flow.
Types of hypothesis tests
We shall understand single/dual/multiple samples, one/two-tailed, and mean-variance, or proportion tests in this section. This section picks up multiple examples stating null and alternative hypotheses to understand the concept better.
Trusted by 1 Crore+ Learners globally
