The P-value is the probability of getting a test statistic at least as extreme as the one representing the sample data, assuming that .

The P-value is the probability of getting a test statistic at least as extreme as the one representing the sample data, assuming that the null hypothesis is true.

Step-by-step explanation:

The P-value is the probability of getting a test statistic at least as extreme as the one representing the sample data, assuming that the null hypothesis is true.

The p-value is the probability that, if the null hypothesis were true,sampling variation would yield and estimate that is further away from the hypothesised value than our data estimate. The p-value shows us how possible it is to get a result like this if the null hypothesis is true.

Assuming we have a null hypothesis and an alternative hypothesis computed as follows.

If P-value is less than or equal to , we will reject the null hypothesis.

38.5

step-by-step explanation:

lets say, first number = r

second number = 3r+7

total = 49

(r)+(3r+7)= 49

4r+7 = 49

4r = 42

r = 42/4

r= 10.5

3r+7 = 3(10.5)+7 = 38.5

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