Hypothesis Testing (Advance) Introduction
- Do you make claims of your products or service?
- Do you know if your claims are true and valid?
- Do you have high rejections because your customer doesn't accept your claims?
- Do you have high warranty costs due to less-than-promised claims?
- Do your want to reduce your risks of claims?
Hypothesis Testing is an important statistical technique. Hypothesis Testing (Advance) is used to formulate a hypothesis and test the truth of that hypothesis. This technique is used to form an assumption about a population parameter. A sample from the population is then obtained to ascertain a value of the assumed parameter. The validity of the assumption is then tested at a given confidence level. This course has a practical hands-on approach in understanding Hypothesis Testing for manufacturing or service. This course enables the delegates to recognize the importance and role of implementing, interpreting and use of Hypothesis Testing.
Benefits Of Attending The Hypothesis Testing (Advance) Training
The Hypothesis Testing (Advance) Training enables the delegates to:
- Understand the importance of hypothesis testing.
- Distinguish the different types of hypothesis testing.
- Conduct suitable hypothesis testing.
- Interpret the hypothesis testing.
- Make decisions from hypothesis testing.
Who Should Attend The Hypothesis Testing (Advance) Training ?
Hypothesis Testing (Advance) will be most appropriate for those involved in Marketing, Finance, Sales, Manufacturing, Production and Service. Teams are encouraged to attend for maximum benefit.
Brief Hypothesis Testing (Advance) Training Outline
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Day 1 (AM) |
Why Hypothesis Testing?
- Hypotheses
- Types of error
- Example of SPC chart
Concepts
- Binomial
- Poisson
- Normal
- Chi-squared
- 1-Sided
- 2-Sided
- a Error
- b Error
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Day 1 (PM) |
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Introduction to Hypothesis Testing
- z-test
- t – Test
- t – Test 2 Sample
- t – Test Paired
- One Sample Proportion
- Two Sample Proportions
- Anova 1 Factor
- Anova 2 Factor
- Chi Square – Goodness of Fit
- Chi Square – Test Of Independence
- One Sample Variance
- Two Sample Variance
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Day 2 (AM) |
Conducting Hypothesis Testing
- Collect data
- Formulate null hypothesis
- Identify a test statistic
- Identify the significance level
- Establish the reject criteria
- Compute the test statistic
- Compare the test statistic against the reject criteria
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Day 2 (PM) |
Report the Hypothesis Testing
- Draw suitable graphs
- Present the data
- Present the conclusion
Course conclusion
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