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Statistics Foundation Course cover
Data Analysis and Research

Statistics Foundation Course

1 students
Last updated Jul 2026

Course Overview

About This Course

Welcome to this course on Discovering Statistics! Statistics is the foundation of all other statistical disciplines. It helps us to understand the world around us. It is the first step towards understanding the world. A statistician must be able to calculate basic statistics. He can use these statistics to analyze and interpret data. He can also use them to make decisions. This is a comprehensive five in one course in statistics covering the following: Manual calculation of basic and advanced statistics in a state by step manner along with a conceptual explanation Demonstration of calculation using Excel to boost your confidence like how managers do statistics Demonstration of calculation using IBM SPSS Statistics to boost your confidence like how Researchers do statistics Demonstration of calculation using R-Package to boost your confidence like how Researchers and Data Scientists do statistics Demonstration of calculation using Python to boost your confidence like how Programmers and Data Scientists do statistics Pedagogy: The course will be delivered in an easy-to-understand and self-explanatory manner. The course will provide you with the skills to learn the concepts of statistics. The course will help you to master the use of statistical software and to understand the concepts of statistics. The course will start with the basics of statistics. It will explain how to calculate the most important statistics manually. Then, it will show how to calculate them using four software i.e., Excel, SPSS, R, and Python. Finally, it will give a detailed conceptual explanation of statistics.



Requirements
Familiarity with basic research process will be helpful but not essential.
A keen desire to master Statistics
A laptop with internet connection
Familiarity with basic computer and operating system

Learning Outcomes

Learn Univariate and Multivariate Statistics from Scratch with Manual Calculation

Demonstration of calculation using IBM SPSS Statistics to boost your confidence like how Researchers do statistics

Demonstration of calculation using Python to boost your confidence like how Programmers and Data Scientists do statistics

Manual calculation of basic and advanced statistics in a state by step manner along with a conceptual explanation

Demonstration of calculation using R-Package to boost your confidence like how Researchers and Data Scientists do statistics

Curriculum

10 Sections • 108 Lectures
Live Class Option
Defining Statistics
5:46
Statistics Defined as a Summary Feature of Sample
1:15
History of Statistics
2:02
Evolutions and Revolutions in Statistics
5:48
Types of Statistics: Descriptive vs. Inferential
5:02
Types of Statistics: Parametric vs. Non-Parametric Statistics
4:22
What We Mean by Sample and Population?
8:22
What We Mean by Statistics and Parameter?
3:57
Understanding Data, Dataset, Values, Observations, Variables
3:54
Understanding Data, Observations, Values, Cases through Covid Data
3:13
Understanding Data, Dataset, Observations, Variables and Values: ESS Example
3:36
Introduction to Scales of Measurement
3:22
What are Nominal Scales?
1:22
What are Ordinal Scales?
2:43
What are Interval Scales?
3:29
Are Likert Scales Ordinal or Interval Scales?
2:31
What are Ratio Scales?
3:28
Summing Up Scales of Measurement
4:00
What is a Frequency Distribution?
1:42
Understanding Frequency Distribution Through a Problem: Favourite Eating Option
2:20
Creating a Frequency Distribution in Excel
17:04
Creating Frequency Distribution in SPSS
12:32
How to Clear R Console _Useful R Commands
0:52
Getting Familiar with R Environment
10:52
Assignment Operators in R
6:09
Creating Numeric and String Vectors in R
10:00
Importing Excel File in R using File import wizard
6:22
Importing Excel File using Setwd and read.csv commands
6:02
How to Seek help and search in R?
1:38
Counting in R Table Function
11:40
Understanding Geometric Progression and Learning to Create it
6:34
Understanding Formula and Manual Calculation of Geometric Mean
13:33
GM exercise Calculate GM using GEOMEAN nth Root and Antilog formula
14:35
Calculating Geometric Mean Using SPSS
4:00
How to calculate Log of a number using log Table
7:23
Harmonic Mean Definition and Formula
8:41
Properties of Harmonic Mean
3:10
Calculation of Harmonic Mean: Manual Calculation with Excel and SPSS Demo
11:34
Calculation of Arithmetic Mean for Grouped Data
14:20
Calculation of Arithmetic Mean for Grouped Data Using SPSS
11:45
Median Calculation for Discrete and Continuous Data
16:28
Mode Calculation for Grouped Data
4:44
Weighted Mean
10:35
What are positional averages Quartiles Percentiles Deciles?
5:33
Understanding Quartiles
6:40
Understanding Formula of Quartiles for Grouped and Ungrouped Data
15:06
Calculation of Quartiles_Understading formula
3:37
Calculation of Quartiles for Even Ungrouped Series
5:36
Calculation of Quartiles for Odd Ungrouped Series
8:23
Quartile Calculation for Class Interval Data
12:24
Calculation of Quartiles in Excel
2:08
Calculation of Quartiles in SPSS
1:52
Merits and Demerits of Quartiles
8:56
Understanding Deciles
3:15
Understanding Formula for Deciles
2:27
Calculation of Deciles for Ungrouped Data
5:18
Decile Calculation for Continuous Data
5:27
Decile Calculation in SPSS
3:42
Percentiles Definition and Formula
6:12
Percentile Calculation of Discrete Data
4:55
Percentile Calculation by Anderson et al. Method
7:26
Percentile Calculation by Inclusion vs. Exclusion Method
7:08
Formula for Percentiles for Continuous Data
7:10
Understanding Measures of Dispersion
7:28
Types of Measures of Dispersion: Absolute Vs. Relative
4:05
Analytical Strategy for Measures of Dispersion
4:17
Understanding Range, its Usage and Calculation
3:27
Calculation of Range and Coefficient of Range for Individual Series
6:59
Calculation of Range for Discrete Series
3:02
Calculation of Range for Continuous Series
2:36
Calculation of Range in Excel and SPSS
4:37
Merits and Demerits of range
4:41
Quartile Deviation Definition and Manual Calculation with Excel and SPSS Demo
8:27
Merits and Demerits of Quartile Deviation
6:39
Understanding the Concept and Formula of Mean Deviation
5:53
Calculation of Mean Deviation for Individual Series
Calculation of Mean Deviation for Discrete and Continuous Series
8:29
Standard Deviation: Understanding Sample and Population Standard Deviation
6:58
Variance and Coefficient of Variation: Definition and Formula
7:09
Calculation of Sample Standard Deviation for Ungrouped Data
11:37
Calculation of Sample Standard Deviation for Ungrouped Data in Excel
2:17
Calculation of Sample Standard Deviation for Ungrouped Data Using SPSS
2:32
Manual Calculation of Population Std Dev for Ungrouped Data
7:06
Calculation of Population Standard Deviation Using Excel
0:52
Calculation of Population Standard Deviation Using SPSS
5:20
What is a Statistical Distribution?
11:56
Understanding Symmetric and Asymmetric Distributions
6:02
Normal Distribution: Explanation and Properties
7:52
What is Skewness_Understanding Positive and Negative Skewness
7:20
Properties of Skewness
4:04
Measures of Skewness
4:26
Pearson's Coefficient of Skewness
7:15
Bowley's Coefficient of Skewness
4:40
Kelly's Formula of Skewness
3:53
Downloading and Installing R and R Studio
6:36
Downloading and Installing PyCharm
7:35
Download install Anaconda
5:55
Getting Familiar with Juypter Notebook Interface
3:00
Getting familiar with Jupyter Notebook Interface: Part 2
2:18
Running Basic Python Functions in Jupyter Notebook
1:40
Understanding the concept of logs and exponents_With Graphical Demo of
8:48
Understanding Calculation of Log
3:59
Types of Log and Their Calculation_ Explanation of Common Natural Binar
3:40
Rules for Width of CI
9:10
Math_ Types of Numbers
11:22
Types of CI Continuous Discrete
5:52
TIPS _ How to Activate data Analysis Tool Pack in Excel
1:20
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An experienced and passionate instructor, [Name] is dedicated to fostering a dynamic and engaging learning environment where students feel motivated to grow both academically and personally. With a strong foundation in their subject area, they bring clarity, structure, and enthusiasm to every lesson, ensuring complex concepts are made accessible and relevant. Their teaching approach blends theoretical knowledge with practical application, encouraging students to think critically and develop problem-solving skills. Known for their supportive and approachable demeanor, [Name] builds meaningful connections with students, understanding that each learner has unique strengths and challenges. They are committed to creating an inclusive classroom atmosphere where curiosity is encouraged, questions are welcomed, and every student feels valued. By adapting teaching methods to suit diverse learning styles, they help students gain confidence and achieve their full potential. Beyond the classroom, [Name] is deeply invested in continuous learning and professional development, staying updated with the latest educational practices and advancements in their field. They often contribute to curriculum development, mentorship programs, and extracurricular activities, reinforcing their role as not just an instructor, but a mentor and guide. Their ultimate goal is to inspire lifelong learning and empower students to succeed in an ever-evolving world.

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