Hypothesis testing

Hypothesis testing

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DT #4 – Hypothesis Testing

The topic is in the Assignments area.

See examples on p. 323 – 324 and 325 – 326. Page 326 shows the computed value of z in the “do not reject Ho” and page 329 describes the calculated z-value with the associated p-value.

I want to be sure each student understands two of the three ways to get to REJECT the null hypothesis. The two methods are actually the same test. You can use the critical value (z, t, F, chi squared, etc) to define the line between acceptance/rejection areas or you can use the alpha to define the rejection area (as a percentage).

If the sample gives enough evidence then you GET to reject the null hypothesis. (Which lends support to your research statement in the alternative hypothesis)

You calculate the test statistic (or use the p-value) to see if you GET to reject the null hypothesis.

1. If the test statistic is outside the acceptance area (in the rejection area) you GET to reject the null hypothesis. . (p. 324) OR

2. If the p-value is inside (less than alpha) the rejection area you GET to reject the null hypothesis. (p. 329)

If you think in terms of the areas on the bell shaped curve as shown on pages 321, 323,324, 326, 328, 329, 334, 335, 337, 340 , and 341 then it is more clearly the same test. The test statistic and p-value are from the sample’s data, they are compared to the critical value and/or alpha (management decision, Step 2).

Page 328 illustrates the two tailed and one tailed usage of this concept.
***If you would like a copy of these pages listed please feel free to call or message me at any time. I am able to scan and send them.

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