Power of a Hypothesis test. H 0 True H 0 False Reject Fail to reject Type I Correct Type II Power   Suppose H 0 is true – what if we decide to fail.

Slides:



Advertisements
Similar presentations
Understanding Power By Jessica Jorge.
Advertisements

Power of a test. power The power of a test (against a specific alternative value) Is a tests ability to detect a false hypothesis Is the probability that.
Power of a test. power The power of a test (against a specific alternative value) Is the probability that the test will reject the null hypothesis when.
 When we perform a hypothesis test, we make a decision to either Reject the Null Hypothesis or Fail to Reject the Null Hypothesis.  There is always the.
Statistics 101 Class 8. Overview Hypothesis Testing Hypothesis Testing Stating the Research Question Stating the Research Question –Null Hypothesis –Alternative.
Ch. 21 Practice.
+ Chapter 10 Section 10.4 Part 2 – Inference as Decision.
AP Statistics – Chapter 9 Test Review
Hypothesis Testing Steps of a Statistical Significance Test. 1. Assumptions Type of data, form of population, method of sampling, sample size.
Hypothesis Testing: Type II Error and Power.
Power of a test. power The power of a test (against a specific alternative value) Is the probability that the test will reject the null hypothesis when.
Chapter 9 Hypothesis Testing.
Power of a Test Notes: P 183 and on your own paper.
Hypothesis Testing.
Section 10.2: Errors in Hypothesis Testing. Test Procedure – the method we use to determine whether H 0 should be rejected. Type 1 Error: the error of.
The Probability of a Type II Error and the Power of the Test
1 Power and Sample Size in Testing One Mean. 2 Type I & Type II Error Type I Error: reject the null hypothesis when it is true. The probability of a Type.
Elementary Statistical Methods André L. Souza, Ph.D. The University of Alabama Lecture 22 Statistical Power.
A Brief Introduction to Power Tyrone Li ‘12 and Ariana White ‘12 Buckingham Browne & Nichols School Cambridge, MA.
1 Lecture note 4 Hypothesis Testing Significant Difference ©
1 STATISTICAL HYPOTHESIS Two-sided hypothesis: H 0 :  = 50H 1 :   only here H 0 is valid all other possibilities are H 1 One-sided hypothesis:
Hypothesis Testing – A Primer. Null and Alternative Hypotheses in Inferential Statistics Null hypothesis: The default position that there is no relationship.
Errors in Hypothesis Tests. When you perform a hypothesis test you make a decision: When you make one of these decisions, there is a possibility that.
1 9 Tests of Hypotheses for a Single Sample. © John Wiley & Sons, Inc. Applied Statistics and Probability for Engineers, by Montgomery and Runger. 9-1.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Statistics for Business and Economics 8 th Edition Chapter 9 Hypothesis Testing: Single.
Errors in Hypothesis Tests. When you perform a hypothesis test you make a decision: When you make one of these decisions, there is a possibility that.
Chapter 9: Power I can make really good decisions. Chapter 9: Power Target Goal: I can make really good decisions. 9.1d h.w: pg 548: 23, 25.
Ex St 801 Statistical Methods Inference about a Single Population Mean.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Unit 5: Hypothesis Testing.
Goals… Define what is meant by a Type I error. Define what is meant by a Type II error. Define what is meant by the power of a test. Identify the relationship.
Introduction to Hypothesis Testing
Inference as Design Target Goal: I can calculate and interpret a type I and type II error. 9.1c h.w: pg 547: 15, 19, 21.
Type I and Type II Errors. For type I and type II errors, we must know the null and alternate hypotheses. H 0 : µ = 40 The mean of the population is 40.
Major Steps. 1.State the hypotheses.  Be sure to state both the null hypothesis and the alternative hypothesis, and identify which is the claim. H0H0.
Power of a test. power The power of a test (against a specific alternative value) Is In practice, we carry out the test in hope of showing that the null.
Hypothesis Testing Steps for the Rejection Region Method State H 1 and State H 0 State the Test Statistic and its sampling distribution (normal or t) Determine.
Chapter 9: Hypothesis Tests for One Population Mean 9.2 Terms, Errors, and Hypotheses.
Chapter 10 Lesson 10.2 Hypotheses and Test Procedures 10.2: Errors in Hypothesis Testing.
Tests of hypothesis Statistical hypothesis definition: A statistical hypothesis is an assertion or conjecture on or more population.
Warm Up Check your understanding p. 563
Section Testing a Proportion
Power of a test.
Example: Propellant Burn Rate
Power of a test.
Power of a test.
Hypothesis Testing: Hypotheses
MATH 2311 Section 8.2.
CONCEPTS OF HYPOTHESIS TESTING
A Closer Look at Testing
Chapter Review Problems
P-value Approach for Test Conclusion
Chapter 9 Hypothesis Testing
AP Statistics: Chapter 21
Statistical inference
Chapter 9: Hypothesis Tests Based on a Single Sample
Power of a Test.
P-VALUE.
More About Tests Notes from
Power of a test.
Power of a test.
Chapter 7: Statistical Issues in Research planning and Evaluation
Power of a Hypothesis Test
Power of a test.
Chapter 9: Testing a Claim
Power of a test.
The POWER of a hypothesis test
Power Problems.
Inference as Decision Section 10.4.
Power and Error What is it?.
Statistical Power.
Presentation transcript:

Power of a Hypothesis test

H 0 True H 0 False Reject Fail to reject Type I Correct Type II Power   Suppose H 0 is true – what if we decide to fail to reject it? Suppose H 0 is false – what if we decide to reject it? Suppose H 0 is true – what if we decide to reject it? Suppose H 0 is false – what if we decide to fail to reject it? We correctly reject a false H 0 !

power The power of a test (against a specific alternative value) Is the probability that the test will reject the null hypothesis when the alternative is true In practice, we carry out the test in hope of showing that the null hypothesis is false, so high power is important.

A researcher selects a random sample of size 49 from a population with standard deviation  = 35 in order to test at the 1% significance level the hypothesis: H 0 :  = 680 H a :  > 680 What is the probability of committing a Type I error?  =.01

H 0 :  = 680 H a :  > 680 For what values of the sample mean would you reject the null hypothesis? Invnorm(.99,680,5) =691.63

Normalcdf(-10^99,691.63,700,5) =.0471 Power = =.9529 Go to 2 nd VARS, enter normalcdf Lower: -100,000 Upper: Mean: 700 Standard deviation: 5

H 0 :  = 680 H a :  > 680 If H 0 is rejected, suppose that  a is 695. What is the probability of committing a Type II error? What is the power of the test? Normalcdf(-10^99,691.63,695,5) =.2502 Power = =.7498

Reject H 0 Fail to Reject H 0 Power = 1 -  00  aa 

What happens to , , & power when the sample size is increased? Reject H 0 Fail to Reject H 0 00  aa 

Facts: The researcher is free to determine the value of . The experimenter cannot control , since it is dependent on the alternate value. The ideal situation is to have  as small as possible and power close to 1. (Power >.8)  powerAs  increases, power increases. (But also the chance of a type I error has increased!) sample sizeBest way to increase power, without increasing , is to increase the sample size

A water quality control board reports that water is unsafe for drinking if the mean nitrate concentration exceeds 30 ppm. Water specimens are taken from a well. Identify the decision: a) You decide that the water is not safe to drink when in fact it is safe. Type I Error

A water quality control board reports that water is unsafe for drinking if the mean nitrate concentration exceeds 30 ppm. Water specimens are taken from a well. Identify the decision: b) You decide that the water is not safe to drink when in fact it is not safe. Correct – Power!!