For all three alternatives, the null hypothesis is o: = o.

Null hypothesis: μ = 72  Alternative hypothesis: μ ≠72

What is the null hypothesis (implied or explicitly stated)?

Since the p-value of 0.004 is so small, the null hypothesis provides a very poor explanation of the data. We find good evidence that the population proportion of left-handed students in the College of Art and Architecture exceeds 0.10.

The standard deviation of  , if the null hypotheses is true (i.e., when o = 0.5) is:

What is the null hypothesis (implied or explicitly stated)?

So when testing, if we get the expected result (B = 1), we reject the Null Hypothesis, because in every case where B=1, the value of NOT A B is False (0). This still does not prove the Research Hypothesis, since the fact that B = 1 does not prove that A = 1; A could still be 0. However, rejection of the Null Hypothesis makes it for the Research Hypothesis to be True.

1. Setting up two competing hypotheses - Each hypothesis test includes two hypothesis about the population. One is the null hypothesis, notated as Ho, which is a statement of a particular parameter value. This hypothesis is assumed to be true until there is evidence to suggest otherwise. The second hypothesis is called the alternative, or research, hypothesis, notated as Ha. The alternative hypothesis is a statement of a range of alternative values in which the parameter may fall. One must also check that any assumptions (conditions) needed to run the test have been satisfied e.g. normality of data, independence, and number of success and failure outcomes.


The null hypothesis in each case would be:

Step Two: Collect and summarize the data so that a test statistic can be calculated. A test statistic is a summary of the data that measures the difference between what is seen in the data and what would be expected if the null hypothesis were true. It is typically standardized so that a p-value can be obtained from a reference distribution like the normal curve.

Step 1: State Null and Alternative Hypotheses.

This is the goal of the negative proof – to show that the opposite of the research hypothesis produces a contradiction and is therefore an invalid argument. So, if B = 1, then the Null Hypothesis cannot be Valid (H0 is rejected), therefore

How do we decide whether to reject the null hypothesis?

407) suggested that “an investigator would be misled less frequently and would be more likely to obtain the information he seeks were he to formulate his experimental problems in terms of the estimation of population parameters, with the establishment of confidence intervals about the estimated values, rather than in terms of a null hypothesis against all possible alternatives.”Many other critics have echoed that advice, to which we also subscribe, especially when the outcome measure is well defined.

(1999).One cheer for null hypothesis significance testing.

For NOT A B there is only ONE condition that does not produce a contradiction: the condition where A is NOT related to B (shaded row). The Null Hypothesis is therefore a statement that there is NO relationship between A and B.

Null and Alternative Hypothesis | Real Statistics Using …

If, however, we do not get the expected result (B = 0), we fail to reject the Null Hypothesis. This still does not reject the Research Hypothesis - it is possible that either A = 0 (we didn't actually create the test condition we intended), or A = 1 and the relationship A B truly does not exist (an actual software defect has been found!). Remember, the existence of the relationship A B was our original premise, and it could be False!