Assume the z test statistic equals 0.99, find the the p-value if Ha:p> 0.50

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Find table in the back of your statistics text labeled something like "areas under normal distribution" to find the proportion/probability related to the Z score.

Are you sure that you have no typos? Usually it is printed as follows;

Ha: p ≤ .05

To find the p-value given a z test statistic of 0.99 and the alternative hypothesis Ha: p > 0.50, you need to determine the area to the right of the test statistic on the standard normal distribution.

1. Start by finding the cumulative probability associated with the z test statistic of 0.99 using a standard normal distribution table or a statistical calculator.

2. Since the alternative hypothesis is p > 0.50, you want to find the probability of observing a z value greater than 0.99.

3. Look for the z value closest to 0.99 in the standard normal distribution table. In this case, you can use the closest z value above and find its corresponding cumulative probability.

4. This cumulative probability is the p-value. It represents the probability of observing a sample proportion greater than 0.50, assuming the null hypothesis is true.

Please note that without additional information about the sample size or specific calculations, it is not possible to provide the exact p-value.

To find the p-value given the z-test statistic and the alternative hypothesis, follow these steps:

Step 1: Determine the type of test
In this case, the alternative hypothesis is Ha: p > 0.50, which implies a right-tailed test.

Step 2: Find the significance level (α)
The significance level (α) is the acceptable level of Type I error. It is defined prior to conducting the test and typically set to 0.05 or 0.01. Let's assume a significance level of α = 0.05.

Step 3: Find the critical value
To find the critical value for a right-tailed test, we need to find the z-score that corresponds to the given significance level. For a significance level of α = 0.05, the critical value can be found using a standard normal distribution table or a statistical software. In this case, the critical value is approximately 1.645.

Step 4: Calculate the p-value
The p-value is the probability of obtaining a test statistic as extreme as, or more extreme than, the observed value assuming the null hypothesis is true.

In a right-tailed test, the p-value is the area to the right of the observed z-test statistic.

To calculate the p-value, we need to find the cumulative probability associated with the z-test statistic. In this case, the z-test statistic is 0.99.

Using a standard normal distribution table or a statistical software, find the cumulative probability (area) to the right of z = 0.99. Let's assume that the cumulative probability is 0.1635.

Step 5: Interpret the result
Since the p-value obtained (0.1635) is greater than the significance level (0.05), we fail to reject the null hypothesis.

In conclusion, the p-value for the given z-test statistic (0.99) and the alternative hypothesis (Ha: p > 0.50) is approximately 0.1635.