Track 08

Motivation to do Track 08

This learning path is designed to develop the following skills:

What is the context to employ a test of hypothesis?
What are the steps to employ a test of hypothesis?
How the first step is related to a one-side or two-side test?
How the sample size is related to the selection of the distribution?
How to determine the critical values and rejection region?
How to compute the statistical test with Zobs?
Make a decision using the Zobs and if it is inside or not in the rejection region. Accept or not null hypothesis Ho.
How to employ p-value and extract different types of errors?

The journey map of Track 08

Badges

CLT Simulator

P-value

Normal Distrib,

Student T Distrib,

Inverse Distrib.

Test of Hypothesis

HS6 and Weight

Inspect LVL 3

1. Concepts & Definitions

1.1. Defining statistical test of hypothesis

1.2. Numerical example of test of hypothesis for mean

1.3. Code for test of hypothesis for mean

1.4. Code for right tailed test of hypothesis for mean

1.5. Code for left tailed test of hypothesis for mean

1.6. Code for small sample hypothesis for mean

1.7. P-Value and test of hypothesis

1.8. Statistical power and power analysis

1.9. Shapiro Wilk for normality test

2. Problem & Solution

2.1. Shapiro Wilk to verify CLT Simulator

2.2. Shapiro Wilk for HS6 code weight samples

2.3. Test of hypothesis for weight of HS6 code

1. Concepts & Definitions

2. Problem & Solution

Defining Statistical Test of Hypothesis

Code for Right tailed test of hypothesis for mean

P-Value and Test of Hypothesis

Shapiro Wilk to verify CLT Simulator

Numerical Example of test of Hypothesis for mean

Code for Left tailed test of hypothesis for mean

Statistical Power and Power Analysis

Shapiro Wilk for HS6 code weight samples

Code for test of hypothesis for mean

Code for small sample of hypothesis for mean

Shapiro Wilk for normality test

Test of hypothesis for weight of HS6 code

This learning path is designed to develop the following skills:

Test of hypothesis
Adherence test for fitting curves in particular normal distribution for the log weight per unit, and the Shapiro–Wilk test.
Explain in more detail the following topics: how to define hypothesis tests and their relationship to adherence tests,

the relationship between hypothesis testing and p-value, and more general questions about curve fitting.

Check Shapiro–Wilk test for more than one country: if the curve fits are the same for the same products, using the

concept of mirror statistics to define selected products, and countries as candidates for inspection smart, that is, refining

the question of smart selection is addressed in Track 06.

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