Once a test statistic has been calculated, we calculate the P-value by using what we know about the distribution of the test statistic. For the test of proportions that meets the sample conditions (highlighted in Question 3), we use the standard normal curve to calculate the P-value. We considering P-value equal to the area under curve corresponding to the observation and observations more extreme (assuming Ho is true). Specifically, we use the DCMP tool to calculate the area that represents the P-value = probability of seeing that observation or observations more extreme, assuming Ho is true. Suppose you get an observation that has a test statistic of z = -1.2. Suppose your alternate hypothesis is HA: p < the null value. This means that the P-value will be how "likely" it is that we observed the sample data that resulted in a test statistic of z = -1.2 or lower/smaller