Final answer:
To calculate the p-value for a hypothesis test of a single population proportion, you need to define your null and alternative hypotheses, enter your sample data into statistical software, generate a randomization distribution, and determine the p-value.
Step-by-step explanation:
To use Statkey or other technology to find the p-value for a hypothesis test of a single population proportion, you would follow these steps:
- Define the null hypothesis (H0) and alternative hypothesis (Ha). In this case, the null hypothesis is H0: p = 0.7, and the alternative hypothesis is Ha: p < 0.7.
- Enter the sample data into the software. The sample proportion (Üp) is 0.625, and the sample size (n) is 200.
- Generate a randomization distribution for the single proportion. The software like Statkey will simulate many samples under the null hypothesis and compute a proportion for each one.
- Determine the p-value, which is the probability of observing a sample proportion at least as extreme as the one observed, assuming the null hypothesis is true. The lower the p-value, the stronger the evidence against the null hypothesis.
In this scenario, once you have entered the data into the software, it would calculate the p-value, which you would then compare with your alpha level (α) to decide whether to reject or fail to reject the null hypothesis.