Test Android StudyStack App
Please help StudyStack get a grant! Vote here.
or...
Reset Password Free Sign Up

Free flashcards for serious fun studying. Create your own or use sets shared by other students and teachers.


incorrect cards (0)
correct cards (0)
remaining cards (0)
Save
0:01
To flip the current card, click it or press the Spacebar key.  To move the current card to one of the three colored boxes, click on the box.  You may also press the UP ARROW key to move the card to the Correct box, the DOWN ARROW key to move the card to the Incorrect box, or the RIGHT ARROW key to move the card to the Remaining box.  You may also click on the card displayed in any of the three boxes to bring that card back to the center.

Pass complete!

Correct box contains:
Time elapsed:
Retries:
restart all cards



Embed Code - If you would like this activity on your web page, copy the script below and paste it into your web page.

  Normal Size     Small Size show me how

Statistics Def.

Definitions for Hypothesis Testing

Part1Part2
Hypothesis Test pertaining to one population for testing a claim about some parameter of the population.
Null Hypothesis a statement that the value of a population parameteris equal to some value.
Alternative Hypothesis a statement that the population parameter has a value that somehow differs from the value in the null hypothesis.
Test Statistic a value that is computed from a sample data.
Traditional Method invloves critical values and critical regions.
P-value Method involves the calculation of a P-value.
Critical Region a set of values of the test statistic that causes us to reject the null hypothesis.
Significance Level the probability that the test statistic will fall in the critical region when the null hypothesis is actually true.
Critical Value the value that separates the critical region from the non-critical region.
Two-Tailed if the sign is H1is not = to.
Right-Tailed if the sign is H1>.
Left-Tailed if the sign is H1<.
P-Value the probability of getting a value of the test statistic that is at least as extreme as the one representing the sample data, assuming the null hypothesis is true.
Type I Error if the null hypothesis is true, but we reject it.
Type II Error if the null hypothesis is false, but we fail to reject it.
Created by: isaxo on 2005-06-19



bad sites Copyright ©2001-2014  StudyStack LLC   All rights reserved.