Learn Hypothesis Testing
1: Learn Hypothesis Testing
Master Hypothesis Testing for Data-Driven Decision Making - Lean Six Sigma Certification Course
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This course is part of our Lean Six Sigma Green Belt program, which consists of four courses designed to prepare you for the International Association of Six Sigma Certification (IASSC) Green Belt exam. We recommend you take all four courses in the program to be fully prepared for the exam.
Hypothesis testing allows you to make decisions about problems based upon statistically significant data. Depending on the nature of the hypothesis and data available, different tests should be applied.
In this course, you will learn about 20 different statistical tests. You will understand when to use each test, and when not to use them. You will also identify the level of risk associated with different statistics, and how best to work with them.
The training features plenty of opportunities to practice with examples, exercises, and quizzes to test your knowledge. By the end of the course, you will have learned how to apply these hypothesis tests in your business processes.
The course is designed from the standpoint of making sound business decisions, not deriving proofs behind the formulas or statistics. You won't need to do any advanced math, as popular programs like Excel and Minitab will do that for you. While the computer crunches the numbers, you will learn how to read and interpret the test results to understand the messages in your data.
Learn Hypothesis Testing | Udemy
Highlights:
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34 practical tutorials with videos, reference guides, exercises, and quizzes.
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Designed to prepare you in part for the IASSC Green Belt exam. To prepare in full, you should also take the Lean Six Sigma Principles, Statistical Process Control, and Measurement Systems Analysis courses part of our four-course Lean Six Sigma Green Belt program.
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Understand the concepts of hypotheses in problem-solving.
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Identify the hypothesis testing process, and best practices that should be applied.
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Learn key decision factors for selecting which hypothesis test to use.
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Apply statistical analysis principles such as inferential statistics.
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Learn how to read residual graphs and conduct regression analysis.
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Conduct statistical hypothesis tests including T Tests, F Tests, ANOVA, and more.
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Aligned to the IASSC Lean Six Sigma Green Belt Body of Knowledge.
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The only method to earn an IASSC certification is to successfully sit for and pass an official IASSC certification™ exam, which can be taken through IASSC. We do not provide access to IASSC Certification exams.
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Earn 3 PDUs or contact hours toward your Project Management education for certification with PMI.
What you'll learn
Designed to prepare you in part for the IASSC Green Belt exam. To prepare in full, you should also take the Lean Six Sigma Principles, Statistical Process Contr
Understand the concepts of hypotheses in problem-solving.
Identify the hypothesis testing process, and best practices that should be applied.
Learn key decision factors for selecting which hypothesis test to use.
Apply statistical analysis principles such as inferential statistics.
Learn how to read residual graphs and conduct regression analysis.
Conduct statistical hypothesis tests including T Tests, F Tests, ANOVA, and more.
Aligned to the IASSC Lean Six Sigma Green Belt Body of Knowledge.
Learn Hypothesis Testing | Udemy
Requirements
There are no prerequisites for this course
Who this course is for:
This course is perfect for Lean Six Sigma Green Belt aspirants aiming to ace the IASSC Green Belt exam. Learn the ins and outs of hypothesis testing, including identifying when to use specific statistical tests, risk assessment, and best practices in decision-making. With hands-on exercises, quizzes, and practical tutorials, you'll master inferential statistics, regression analysis, residual graph reading, and more. Take this course to sharpen your problem-solving skills and make data-driven business decisions.
- Step 1: Specify the Null Hypothesis. ...
- Step 2: Specify the Alternative Hypothesis. ...
- Step 3: Set the Significance Level (a) ...
- Step 4: Calculate the Test Statistic and Corresponding P-Value. ...
- Step 5: Drawing a Conclusion.
Learn Hypothesis Testing | Udemy
- Identify Population and Sample.
- State the Hypotheses in terms of population parameters.
- State Assumptions and Check Conditions.
- Calculate the Test Statistic.
- Calculate the P-value.
- State the Conclusion.
Step 1: State the null and alternative hypothesis. Step 2: Determine the level of significance. Step 3: Compute the test statistic. Step 4: Make a decision; 2.
Hypothesis testing is the process used to evaluate the strength of evidence from the sample and provides a framework for making determinations related to the population, ie, it provides a method for understanding how reliably one can extrapolate observed findings in a sample under study to the larger population from ...
The p-value is calculated using the sampling distribution of the test statistic under the null hypothesis, the sample data, and the type of test being done (lower-tailed test, upper-tailed test, or two-sided test). The p-value for: a lower-tailed test is specified by: p-value = P(TS ts | H 0 is true) = cdf(ts)
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GoSkills: Lean Six Sigma
