How do I respond to this?

The p-Value that we compute during a Hypothesis Test tells us the probability of observing what we saw in the Sample, assuming that our Null Hypothesis is True. To decide on the Hypothesis Test, you will compare the p-Value to the Level of Significance (alpha), as the former must be less than alpha to Reject the Ho. The smaller the p-Value, the more significant the results of the test. The smaller the p-Value, the more likely you should be to Reject the Null Hypothesis and accept the Research/Alternative Hypothesis.

You can use a table, chart, or computer software to convert a test statistic (like Z) into a p-value for further analysis. Whichever method you use will compute the probability of seeing a Z score in the test.

Since we have defined the Level of Significance and p-value in terms of the risk of rejecting the Ho when it is true, the lower the value, the less chance of rejecting Ho (and accepting the Ha) in error, the p-Value that we compute during a Hypothesis Test tells us the probability that we would observe what we saw in the Sample, assuming that our Null Hypothesis is True. To decide on the Hypothesis Test, you will compare the p-Value to the Level of Significance (alpha), as the former must be less than alpha to Reject the Ho. The smaller the p-Value, the more significant the results of the test. The smaller the p-Value, the more likely you should be to Reject the Null Hypothesis and accept the Research/Alternative Hypothesis.

You can use a table, chart, or computer software to convert a test statistic (like Z) into a p-value for further analysis. Whichever method you use will compute the probability of seeing a Z score in the test.

Since we have defined the Level of Significance and p-value in terms of the risk of rejecting the Ho when it is true, the lower the value, the less chance of rejecting Ho (and accepting the Ha) in error.