* I just wanted to know if I'm setting up the Ho and Ha correctly.
An herbal supplement is advertised as producing an increase in strength and stamina.
Sample of n=36 adults is obtained and each person is told to take the regulary daily dose of the herb for 30 days.
At the end of the 30days each person is tested on a treadmill task for which average, age adujected score is mu=15.
The people in the sample proudce a mean socre of M=16.9 with SS=1260
* I just wanted to know if I'm setting up the Ho and Ha correctly.
-Are these data sufficient enough to conclude that the herb has a statistically significant effects using a 2 tailed test with an alpha level of .05?
Ho: mu =15
Ha: mu does NOT equal 15
How would I would a set up the Ho and Ha for a ONE-TAILED test?
Would it be like this?
Ho: mu>15
Ha: mu<15
Thanks
For two-tailed test:
Ho: μ = 15
Ha: μ ≠ 15
Since the sample value is greater than μ, for one-tailed test:
Ho: μ = 15
Ha: μ > 15
I hope this helps. Thanks for asking.
Yes, you have correctly set up the null hypothesis (Ho) and alternative hypothesis (Ha) for a two-tailed test:
Ho: mu = 15
Ha: mu does not equal 15
This means that under the null hypothesis, there is no significant difference in the mean score of the treadmill task for individuals taking the herbal supplement compared to the population mean score of 15. The alternative hypothesis suggests that there is a significant difference in the mean score.
If you want to set up the hypotheses for a one-tailed test, you need to specify the direction of the difference you are looking for. Based on your question, it seems like you want to check if the herbal supplement leads to a decrease in the mean score. In that case, the hypotheses would be:
Ho: mu >= 15
Ha: mu < 15
These hypotheses state that under the null hypothesis, the mean score is greater than or equal to 15, while the alternative hypothesis suggests that the mean score is less than 15.
To determine which type of test (two-tailed or one-tailed) to use and to evaluate if the herb has a statistically significant effect, further statistical analysis needs to be conducted using the sample statistics.