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Data management is a part of computing activities that have a great contribution to its operations. Data analysts are responsible to learn probability to be able to produce data analysis which is used by businesses and organizations.

You are provided in this [course_title] with the principles and methodologies of the data analysis. With these lessons, you are encouraged to implement environmental applications that help in programming the computer to utilize its potential.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


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Course Credit: MIT

Course Curriculum

Module 01
L-1 Course Introduction 00:01:00
L-2 Descriptive Statistics 00:05:00
L-3 Probablility 00:15:00
L-4 Joint Probability, Independence, Repeated Trials 00:05:00
L-5 Combinatorial Methods for Deriving Probabilities part 1 00:05:00
L-5 Combinatorial Methods for Deriving Probabilities part 2 00:10:00
L-6 Conditional Probability and Baye’s Theorem 00:10:00
L-7 Random Variables and Probability Distributions 00:05:00
L-8 Expectation, Functions of a Random Variable 00:10:00
L-9 Some Common Probability Distributions 00:05:00
L-10 Multivariate Probability 00:10:00
Module 02
L-11 Populations and Samples 00:10:00
L-12 Estimation 00:05:00
L-13 Confidence Intervals 00:15:00
L-14 Testing Hypotheses about a Single Population 00:10:00
L-15 Testing Hypotheses about Two Populations 00:15:00
L-16 Small Sample Statistics 00:10:00
L-17 Analysis of Variance 00:10:00
L-18 Multifactor Analysis of Variance 00:10:00
L-19 Linear Regression 00:10:00
L-20 Analyzing Regression Results 00:10:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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