'Reject ho' diaporamas de présentation

Chapter 13 Comparing Groups: Analysis of Variance Methods

1.01k views • 82 slides

ESTIMATION AND TEST OF HYPOTHESES: One- sample, two- sample

ESTIMATION AND TEST OF HYPOTHESES: One- sample, two- sample. Introduction to hypothesis Testing:

821 views • 60 slides

ESTIMATION AND TEST OF HYPOTHESES: One- sample, two- sample

ESTIMATION AND TEST OF HYPOTHESES: One- sample, two- sample. Introduction to hypothesis Testing:

738 views • 60 slides

Stats 2020 Tutorial

Stats 2020 Tutorial. Chi-Square Goodness of Fit. f o. p e. f e. Steps. What we know: n = 300, ? = .05 and... The observed number (f o ) and percentage of drivers in each category:. Steps (cont.).

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IEEM 552 - Human-Computer Systems

IEEM 552 - Human-Computer Systems. Dr. Vincent Duffy - IEEM Week 7 - Hazards in HCI March 16, 1999 http://www-ieem.ust.hk/dfaculty/duffy/552 email: vduffy@uxmail.ust.hk. 1. For today. 1. Further discussion/review of the summary of results you submitted

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Sample Size Estimation

Sample Size Estimation. Dr. Tuan V. Nguyen Garvan Institute of Medical Research Sydney, Australia. The classical hypothesis testing. Define a null hypothesis (H0) and a null hypothesis (H1) Collect data (D) Estimate p-value = P(D | H0)

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Multiple Regression Analysis: Inference

Multiple Regression Analysis: Inference. Assumptions of the Classical Linear Model (CLM). Given the Gauss-Markov assumptions, OLS is BLUE. Beyond the Gauss-Markov assumptions, we need another assumption to conduct tests of hypotheses (inference).

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EPI-820 Evidence-Based Medicine

EPI-820 Evidence-Based Medicine. LECTURE 7: CLINICAL STATISTICAL INFERENCE Mat Reeves BVSc, PhD. Objectives. Understand the theoretical underpinnings and the flaws associated with the current approach to clinical statistical testing (the frequentist approach).

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Prof. Saibal Chattopadhyay IIM Calcutta

IIMC Long Duration Executive Education Executive Programme in Business Management Statistics for Managerial Decisions Advanced Statistical Inference. Prof. Saibal Chattopadhyay IIM Calcutta. A Brief Review. Uncertainty and Randomness: Theory of Probability

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If we live with a deep sense of gratitude, our life will be greatly embellished.

If we live with a deep sense of gratitude, our life will be greatly embellished. Hypothesis Test I: Z tests. Logic of hypothesis test Rejection region and p-value Test for one proportion Test for two proportions. Example: New Drug.

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Hypothesis Test II: t tests

Hypothesis Test II: t tests. Test for one population mean Test for the difference of two population means. Hypothesis Tests for Population Parameters. Population proportion Population mean Difference between two population means. 5 Steps in Hypothesis Tests.

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Exam Feb 28: sets 1,2

Exam Feb 28: sets 1,2. Set 2 due today. (1)multiple regression. (a) forecast = 85 -.05(180) + .76(10) -.10(120) +2(1) = 74

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Introduction to Inference

Introduction to Inference. Statistical Hypotheses. Statistical Hypotheses are statements about population parameters. Hypotheses are not necessarily true. Examples of Hypotheses. mean weight of adult males is greater than 160 pounds

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Summary of t-Test for Testing a Single Population Mean ( m )

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Where we are going : a graphic: Hypothesis Testing.

Where we are going : a graphic: Hypothesis Testing. Samples. 1 2 Paired 2 or more. Ho: / CI. Ho: / CI. Ho: / CI. Means Variances Proportions Categories Slopes. Ho: / CI. Ho: / CI. Ho: / CI. Ho: / CI. Ho: / CI. Ho:. Ho:. Ho: / CI.

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Chi-Square Test

Chi-Square Test. Mon, Apr 19 th , 2004. Chi-Square ( ? 2 ). Are 2 categorical variables related (correlated) or independent of each other? Compares # in categories that would be expected by chance (E) to # in categories actually observed (O)

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Statistics

Statistics. Chapter 7 Review. A car maker claims that its new sub-compact car gets better than 49 miles per gallon on the highway. Determine whether the hypothesis test is left-tailed, right-tailed, or two-tailed. Left-tailed Right-tailed Two-tailed.

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Related Samples t-test

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COMPARING TWO POPULATIONS

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ONE SAMPLE t-TEST FOR THE MEAN OF THE NORMAL DISTRIBUTION

ONE SAMPLE t-TEST FOR THE MEAN OF THE NORMAL DISTRIBUTION. Let sample from N( ? , ? ) , ? and ? unknown , estimate ? using s. Let significance level = ? .

426 views • 6 slides