Ppt hypothesis testing
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This document discusses the fundamentals of hypothesis testing. It introduces important terms like population, sample, statistical inference, parameters, and statistics. It explains that hypothesis testing is a form of statistical inference used to generalize from a sample to a population. The document outlines the steps for hypothesis testing, including formulating the null and alternative hypotheses, selecting an appropriate test, determining critical values, and deciding whether to reject or not reject the null hypothesis. It provides examples and discusses type I and type II errors.
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Ppt hypothesis testing
- 1. FUNDAMENTALS OF HYPOTHESIS TESTING - BY MONIDEEPA MULLICK M.COM(ACCOUNTING & FINANCE), PGDM(BUSINESS ANALYTICS)
- 2. Introducing with some important terms • Population all possible values • Sample a portion of the population • Statistical inference generalizing from a sample to a population with calculated degree of certainty • Two forms of statistical inference – Hypothesis testing – Estimation • Parameter a characteristic of population, e.g., population mean µ • Statistic calculated from data in the sample, e.g., sample mean ( )x
- 4. DEFINITION
- 5. Steps for Hypothesis Testing Draw Marketing Research Conclusion Formulate H0 and H1 Select Appropriate Test Choose Level of Significance Determine Prob Assoc with Test Stat Determine Critical Value of Test Stat TSCR Determine if TSCR falls into (Non) Rejection Region Compare with Level of Significance, Reject/Do not Reject H0 Calculate Test Statistic TSCAL
- 7. EXAMPLE: 1
- 8. EXAMPLE: 2
- 9. EXAMPLE: 3
- 10. TYPE I AND TYPE II ERROR
- 11. LETS UNDERSTAND WITH AN INTERESTING EXAMPLE TYPE I AND TYPE II ERROR
- 12. CONCLUSION LETS SEE HOW ARE HYPOTHESIS DRAWN IN OTHER STATISTICAL TOOLS