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The  Introduction to Data Analysis: Inferential Statistics – Part 2 course covers the advanced parts of statistics and teaches you how to take data and use it to make reasonable and useful conclusions. You will learn the right statistical tools for analysing data. The reasons for studying statistics, sampling procedures, Hypothesis testing, basic use of ANOVA, chi-square test, Correlation, multiple regression will be discussed thoroughly in the course.

Upon completion, you will gain a strong command over statistics and know how to use R software for data analysis.


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.


Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

  • Add the certificate to your CV or resume and brighten up your career
  • Show it to prove your success


Course Credit:  The University of Texas

Course Curriculum

Module 00: Introduction to Data (Optional Review)
The Need for Statistics 00:04:00
Variables: What they are and what they tell us 00:05:00
Introduction to RStudio 00:06:00
Functions and Objects 00:04:00
Vectors 00:05:00
Indexing 00:03:00
Importing a Data Frame 00:06:00
Indexing Data Frames 00:09:00
Module 01: Sampling
The Sampling Distribution 00:08:00
The Confidence Interval 00:06:00
Optional Review – Univariate Descriptive Statistics 00:03:00
Sampling Distributions 00:07:00
Module 02: Hypothesis Testing (One Group Means)
Hypothesis Testing 00:07:00
Alpha Levels, Critical Values, and P-Values 00:08:00
The T-Distribution 00:10:00
Single Sample T-Test 00:08:00
One or Two Tails 00:05:00
One-Sample t Tests 00:05:00
Module 03: Hypothesis Testing (Two Group Means)
Independent Samples t-test 00:07:00
Paired Samples t-test 00:10:00
Paired t Tests 00:05:00
Independent t Test 00:04:00
Module 04: Hypothesis Testing (Categorical Data)
Chi-Square Goodness-of-fit, Part One 00:09:00
Chi-Square Goodness-of-fit, Part Two 00:04:00
Chi-Square Test-of-Independence 00:10:00
Optional Review – Table Proportions 00:06:00
Optional Review – Grouped Bar Charts 00:05:00
Chi-Squared Goodness of Fit Test 00:05:00
Chi-Squared Test of Independence 00:03:00
Module 05: Hypothesis Testing (More Than Two Group Means)
One-Way ANOVA 00:12:00
Two-Way ANOVA 00:10:00
Optional Review – Visualizing Univariate Data 00:08:00
Optional Review – Histograms by Groups 00:08:00
Boxplots 00:05:00
ANOVA 00:06:00
Module 06: Correlation and Regression
Regression Inference 00:11:00
Multiple Regression 00:00:00
Regression Diagnostics 00:04:00
Optional Review – Scatterplots 00:08:00
Optional Review – Correlation 00:04:00
Correlation Testing 00:05:00
Regression Diagnostic Plots 00:06:00
Simple Regression 00:06:00
Multiple Regression 00:06:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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