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Hypothesis Testing of Mean: P-value Method

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Kannon Camera has developed a new camera that it claims can take an average of more than 10 photographs per second. You decide to evaluate the company's claim. In summary, in this problem you are given:

x = 10.5 (This is a x with - above it)
Ï? = .52
n = 16
? = .10

In part 1 of 5, you found that the kind of problem is: a hypothesis test; population mean; with the population sigma known; requiring us to use the standard normal distribution; with a right tail test. In part 2 of 5, you found the null and alternative hypotheses are:

Null Hypothesis: Population Mean â?¤ 10
Alternative Hypothesis: Population Mean > 10

In part 3 of 5 you found the critical value = 1.28, and the test statistic = 3.85. You properly concluded that, because the test statistic is farther out in the tail than the critical value, you could reject the null hypothesis and accept the alternative hypothesis, at alpha = .10.

Finally, in part 4 of 5 you used the test statistic to find the p-value = .0001, and you properly concluded that, because the p-value was less that alpha = .10, you could reject the null hypothesis and accept the alternative hypothesis, at alpha = .10. Moreover, you correctly used the weight of evidence cutoffs to conclude that the p-value = .0001 provided 'extremely strong' evidence for rejecting the null hypothesis and accepting the alternative hypothesis.

The 5th part is to show the set up of MegaStat required to perform the hypothesis test and interpret the essential MegaStat output.

Inputs to the MegaStat Setup Screen Assuming summary input is used, the required data for the Input Range is:

Sample Mean =

Population Standard Deviation =

Sample Size =

Entry for the hypothesized mean =

The appropriate test: t test or z test?

The alternative: Less than, not equal to, greater than?

Explaining and Interpreting the Resulting MegaStat Output

Test statistic type: z or t?

Test statistic value: