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Statistics is a versatile discipline that has revolutionized the fields of business, engineering, medicine and pure sciences. This course is Part 1 of a 4-part series on Business Statistics, and would be beneficial for the learners who wish to enroll in business programs. The first two courses cover topics in the field of Descriptive Statistics, whereas the next two courses focus on the Inferential Statistics.


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: Indian Institute of Management Bangalore

Course Curriculum

Module: 01
Navigating through edX 00:03:00
2 Data Cleanup 00:06:00
Crunchbase: Descriptive Analysis 00:07:00
Histograms 00:05:00
Data visualisation 00:03:00
Module: 02
Rankings 00:08:00
R Installation 00:06:00
RStudio Basics 00:03:00
Yellowstone 00:04:00
RStudio Panes 00:04:00
Module: 03
Variables 00:02:00
Scripts 00:06:00
Vectors 00:03:00
Data Input 00:03:00
Dataframes 00:03:00
Output 00:03:00
Module: 04
Packages 00:02:00
Reading Data 00:05:00
Basic Plots 00:04:00
Regression Fit 00:06:00
Boxplots 00:02:00
Multivariate Data 00:02:00
Module: 05
Sampling Dataset 00:03:00
Cloud Spreadsheets 00:04:00
Cloud Spreadsheets 00:04:00
Summary 00:02:00
Salary Distribution 00:06:00
Module: 06
Analysis 00:06:00
Aggregating data 00:06:00
Grouped Measures 00:05:00
Driving Questions 00:06:00
pmf and cdf 00:07:00
Module: 07
Expectation 00:02:00
Expectation of a Sum 00:05:00
Law of Expectations 00:09:00
Laws of Variance 00:06:00
Probability and Correlation 00:07:00
Module: 08
Uniform Distribution: Discrete 00:04:00
Uniform Distribution: Continuous 00:03:00
Uniform Distribution: Application 00:04:00
Uniform Distribution: Quality Assurance 00:04:00
Uniform Distribution: Continuous 00:03:00
Uniform Distribution: Application 00:04:00
Uniform Distribution: Quality Assurance 00:02:00
Module: 09
Bernoulli Distribution 00:04:00
Binomial Distribution 00:08:00
Random Sample: Goal Seek 00:04:00
Benford’s Law: Introduction 00:07:00
Logarithms 00:06:00
Poisson Distribution 00:04:00
Poisson Distribution: Excel Functions 00:04:00
Module: 10
Poisson Distribution: Application 00:04:00
Exponential Distribution 00:05:00
Exponential Distribution 00:06:00
Simulation 00:06:00
Predicted vs Observed 00:05:00
Module: 11
Poisson and Exponential 00:05:00
Simulation: Discrete 00:06:00
Simulation: Generic Variables 00:04:00
Monte Carlo 00:06:00
Normal Distribution 00:05:00
Simulation: Emergence of Normality 00:03:00
Stock Returns 00:03:00
Model vs Actual 00:05:00
Module: 12
Independence 00:05:00
Standardisation 00:04:00
Chi-Square Test 00:03:00
Aggregate Returns 00:07:00
Summary Measures 00:04:00
PR: Calculations 00:07:00
Interview with Mrinal Wadhwa 00:18:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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