Statistics: Central Limit Theorem and Hypothesis Testing

Focused View

Shubham Kalra

6:51:28

6 View

1 - Continuous Probability Distributions Uniform and Normal Distribution

1 - Introduction.mp4

03:38

2 - Introduction.pdf

2 - Introduction Written Notes.html

3 - Uniform Distribution.mp4

09:39

4 - Uniform Distribution Written Notes.html

4 - Uniform-Distribution.pdf

5 - Area as a measure of probability.mp4

05:40

6 - Normal Distribution.mp4

01:24

7 - Characteristics of Normal Distribution.mp4

09:17

8 - Standard Normal Distributions.mp4

02:28

9 - How to calculate probability using Cumulative Probability table.mp4

06:13

10 - 2 important rules to remember.mp4

02:45

11 - 3 types of probability calculation.mp4

09:10

12 - How to compute z values when probability value is given.mp4

03:25

13 - A different type of table to compute probability.mp4

06:46

14 - How to calculate probability for any normal distribution.mp4

10:42

15 - Application of Normal Distribution.mp4

16:28

16 - Revisiting the application.mp4

15:32

17 - Normal Distribution Some Real Life Examples.html

18 - Normal Distribution using Microsoft Excel.mp4

07:52

19 - Practice Question 1.mp4

11:19

20 - Practice Question 2.mp4

05:46

21 - Practice Question 3.mp4

17:41

22 - Practice Question 4.mp4

07:49

23 - Practice Question 5.mp4

07:11

24 - Practice Question 6.mp4

05:38

25 - Practice Question 7.mp4

04:36

26 - Practice Question 8.mp4

12:54

27 - Practice Question 9.mp4

06:22

28 - Share your experience.html

2 - Sampling and Sampling Distributions

29 - Introduction to the Section.html

30 - The Sampling Problem.mp4

04:33

31 - Simple Random Sample Finite Population.mp4

09:59

32 - Simple Random Sample Infinite Population.mp4

03:20

33 - How to calculate the point estimators of population parameters.mp4

05:52

34 - Sampling Distribution.mp4

08:59

35 - Properties of Sampling Distribution.mp4

06:38

36 - Central Limit Theorem Explained.mp4

05:58

37 - Why large samples are considered to be better predictors of population parameter.mp4

12:48

38 - Share your experience.html

3 - Hypothesis Testing

39 - Basics of Hypothesis Testing.mp4

10:53

40 - Null and Alternate hypothesis.mp4

06:10

41 - Burden of proof.html

42 - Type of test and Rejection Region.mp4

11:33

43 - Types of Errors.mp4

02:41

44 - Type 1 Error.mp4

05:23

45 - Type 2 Error.mp4

02:51

46 - Example 1 Critical Value Method.mp4

15:40

47 - Example Z Score Method.mp4

06:01

48 - Example 2 Critical Value Method.mp4

08:55

49 - Example 3 Critical Value Method.mp4

08:49

50 - Introduction to pvalue.mp4

06:53

51 - Example 1 pvalue method.mp4

09:06

52 - Example 2 pvalue method.mp4

07:41

53 - Example 3 pvalue method.mp4

12:01

54 - Practice Question 1.mp4

11:13

55 - Practice Question 2.mp4

05:26

56 - Practice Question 3.mp4

14:06

57 - Practice Question 4.mp4

08:33

58 - Practice Question 5.mp4

09:11

59 - Share your experience.html

4 - Bonus Section

60 - Bonus Lecture.html

Description

Get a thorough understanding of the most important concepts in Statistics - Central Limit Theorem and Hypothesis Testing

What You'll Learn?

Understand Normal & Standard Normal Distribution and feel much more confident in solving the questions
Build a good intuitive understanding of Central Limit Theorem - One of the most important concepts in Statistics
Understand the basics and essence of Hypothesis Testing
Solve exam style questions in a step by step manner with much more confidence

Who is this for?

Students who are new to statistics

Students who are struggling with statistics

Students who want a refresher of important statistics concepts in a simple and detailed manner

What You Need to Know?

Basics of Statistics (Random Variable, Probability Distributions etc.)

Knowledge of MS Excel (Preferred, not necessary)

More details

Description
This course is theÂ keyÂ to build an excellent understanding of Inferential Statistics. It has students (from overÂ 100Â countries) and here is what some of them have to say:
"Well explained sir, every concept is clear as water and the way you explain is very easy to understand the concept. Worth buying this course" ~ K Roshnishree
"The explanations are quite intuitive and the best part is that the course includes practice problems which helps in building the concepts" ~ Swati Sahu
"The detail level coverage of the basic topics is amazing"Â Â ~ Rehana Shake
"This instructor is doing a fine job explaining the statisticsÂ concepts"Â Â ~ Frank Herrera
"Very clear examples, thank you sir!"Â Â ~ Gitartha Pathak

Course Description:Â
This course is designed for students who are struggling with Statistics or who areÂ complete beginners in statistics.
How is this course structured?Â
Section 1 and 2: These 2 sectionsÂ coverÂ the concepts thatÂ are crucial to understand the basics of hypothesis testing - Normal Distribution, Standard Normal Distribution, Â Sampling, Sampling Distribution andÂ Central Limit Theorem. (Before you start hypothesis testing, make sure you are absolutely clear with these concepts)
Section 3: This section caters to theÂ basics of hypothesis testing withÂ three methodsÂ - Critical Value Method, Z-Score Method and p-value method.
My approach is hands on:Â Â Concepts, examples and solved problems addressing all the concepts covered in the lectures.
Note : Only Hypothesis Testing in Case of Single Population Mean is covered
Who this course is for:
Students who are new to statistics
Students who are struggling with statistics
Students who want a refresher of important statistics concepts in a simple and detailed manner

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Academic Writing

Shubham Kalra

Instructor's Courses

Author of four e-books on Amazon (two for Statistics and two for Econometrics). I have 3500+ hours of teaching experience in the field of Microeconomics, Statistics and Econometrics. I became an online tutor in 2015 and have been teaching full time since then. I have worked with students who were complete beginners, as well as those who were facing challenges in mastering advanced topics.I completely understand the initial struggle in decoding the concepts and formulas. I am adept in breaking down difficult concepts with the use of simple examples. I don't encourage memorisation and simply recalling the formulas, instead, I focus on the 'why' and 'how'.I understand that every student has a different way of understanding things. Some students understand the concepts when explained through analogies, others when shown mathematical foundation behind them. I modify my teaching methodology depending on what the student is comfortable with.I have worked with students from 90+ universities. Here are some of the courses I have catered to:6012B0453Y : Econometrics (Amsterdam School of Economics)EC226: Econometrics (University of Warwick)EC203: Applied Econometrics (University of Warwick)MG205: Econometrics - Theory and Applications (LSE)EC3301: Statistics and Econometrics (University of St Andrews)ECON W3412: Introduction to Econometrics (Columbia University)BEE2031: Econometrics (University of Exeter)Econometrics: University of BirminghamBEE2006: Statistics and Econometrics (University of Exeter)EC3303 : Statistics and Econometrics (University of St. Andrews)EC304: Empirical Economic Analysis II (Boston University)FR2202: Financial Econometrics (Cass Business School)EC220: Introduction to Econometrics (LSE)EC221: Introduction to Econometrics (LSE)5SSMN932: Introduction to Econometrics (King’s College London)5QQMN938 : Intermediate Econometrics (King’s College London)5SSPP213: Econometrics (King’s College London)BEE1023 : Introduction to Econometrics (University of Exeter)6012B0212: Econometrics (Amsterdam School of Economics)

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