What you'll learn

Fundamental of Statistics
Type of Mesurement
Calculation of Descriptive Statistics- Central Tendency and Dispersion
Descriptionting of Graph-Box Description, Scatter Description, Pie Chart, Histogram & Bar Graph
Random Variable, Probability Distribution,Binomial Distribution and Normal Distribution
Sampling Distribution & Central Limit Theorem (CLT)
Hypothesis Formulation
Concept of Critical Value Method and Alpha Level
Concept of P-Value and Alpha Level
Type of Hypothesis Error
Hypothesis Testing using Excel & XLStat

Requirements

No Requirement.
Willingness to Learn & Practice

Description

Specially Designed Course for DS, ML & AI

Statistics is the foundational course for the topics in Data Science,Machine learning & Artificial Intelligence.And it is design specially for students interested in Analytics.All the concept & logic is explained lucidly which is back by example & practice question.This course will cover following topics-

a) Introduction to Statistics - Branches of Statistics & Measurements

b) Descriptive Statistics- Central Tendency, Dispersion and Graphs

c) Inferential Statistics - Normal Distribution, Standard Normal Distribution , Sampling Distribution and Central Limit Theorem (CLT)

d) Hypothesis Testing- Hypothesis Formulation, Critical Value Method , P-Value Method, Alpha Level &T-distribution

After completing the course, you will able to do following things-

a) Data Analysis of datasets by using Excel to find any patterns or trends.

b) Using of CLT concept to calculate unknown population mean.

b) Hypothesis testing of claims or assumptions which is use heavily in data driven companies.

c) Concept of P-value and Alpha Value which is very important in analytics.

Who this course is for:

Students who want to built career in Data Science, Artificial Intelligence and Machine Learning
Business Analyst
Business Executive
Any individual who has interest in numbers
Any individual who is interested in Research

Citación :

rapidgator_net:
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nitroflare_com:
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uploadgig_com:
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