If 9p = 162 then p = 162/9 = 18.
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Normally you would find the critical value when given the p value and the test statistic.
A p-value is the probability of obtaining a test statistic as extreme or more extreme than the one actually obtained if the null hypothesis were true. If this p-value is less than the level of significance (usually set by the experimenter as .05 or .01), we reject the null hypothesis. Otherwise, we retain the null hypothesis. Therefore, a p-value of 0.66 tell us not to reject the null hypothesis.
The p-value is the probability of any event or the level of significance for any statistical test. The z-score is a transformation applied to a Random Variable with any Normal distribution to the Standard Normal distribution.
If the probability of an event occurring is p, then 1-p represents the probability of the same event not occurring. The value of p must lie between 0 and 1.
p value are used when comparing the likelihood of a stated [null] hypothesis being true against a stated alternative. It is a measure of the probability with which an observation which is at least as extreme as that observed will occur even though the null hypothesis is true.