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# Measuring Hypothesis Test

Discuss Measuring Hypothesis Test within the Marketing Research ( MR ) forums, part of the PUBLISH / UPLOAD PROJECT OR DOWNLOAD REFERENCE PROJECT category; Measuring the power of a Hypothesis Test The measure of how well the test is working is called the power ...

 Measuring Hypothesis Test
Abhijeet S

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Measuring Hypothesis Test - September 7th, 2010

Measuring the power of a Hypothesis Test

• The measure of how well the test is working is called the power of the test.

• Type I error occurs when we reject Ho which is true and a (the significance level of the test) is the probability of making type - I error.

• Once the significance level is fixed, nothing can be done about a.

• Type II error occurs when we accept Ho which is false.

• The probability of type II error is b. The smaller the value of b, the better is the test. Alternately ( 1 - b ) i.e. the probability of rejecting Ho when it is false should be as large as possible.

• Thus (1 - b ) is the measure of the power of the test. If we plot the values of ( 1 - b ) for each value of m f2 for which Ha is true, the resulting curve is known as a power curve.

• You can see from the figure given below that the power is simply ( 1 - b ). In testing of a hypothesis high power is desirable.

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James Cord

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March 1st, 2016

Quote:
 Originally Posted by abhishreshthaa Measuring the power of a Hypothesis Test The measure of how well the test is working is called the power of the test. Type I error occurs when we reject Ho which is true and a (the significance level of the test) is the probability of making type - I error. Once the significance level is fixed, nothing can be done about a. Type II error occurs when we accept Ho which is false. The probability of type II error is b. The smaller the value of b, the better is the test. Alternately ( 1 - b ) i.e. the probability of rejecting Ho when it is false should be as large as possible. Thus (1 - b ) is the measure of the power of the test. If we plot the values of ( 1 - b ) for each value of m f2 for which Ha is true, the resulting curve is known as a power curve. You can see from the figure given below that the power is simply ( 1 - b ). In testing of a hypothesis high power is desirable.
Buddy,

i found some important information Hypothesis Testing Objectives and wanna share it with you and other's. So please download and check it.

I am uploading a document which will give more detailed explanation on the Hypothesis Testing and ANOVA.
Attached Files
 Hypothesis Testing Objectives.pdf (80.5 KB, 0 views) Hypothesis Testing and ANOVA.pdf (625.0 KB, 0 views)

Last edited by kartik; March 2nd, 2016 at 11:36 AM..

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