Table of Contents
- 1 Why do researchers want to reject the null hypothesis?
- 2 Why does science test the null hypothesis and not directly test the research hypothesis?
- 3 Why do researchers use null hypothesis instead of alternative hypothesis?
- 4 Why do we not accept the alternative hypothesis?
- 5 When the researcher accepts the null hypothesis when should be rejected?
- 6 When do you reject the null hypothesis and go with the alternative?
- 7 How do researchers construct their hypotheses?
Why do researchers want to reject the null hypothesis?
We assume that the null hypothesis is correct until we have enough evidence to suggest otherwise. After you perform a hypothesis test, there are only two possible outcomes. When your p-value is less than or equal to your significance level, you reject the null hypothesis. Your results are statistically significant.
Why does science test the null hypothesis and not directly test the research hypothesis?
The null hypothesis is the one that they do t want to be true, so they may work more strenuously to nullify it. If it can be nullified, the research hypothesis may still not be proven or even correct. – the best the researcher can say is that so far there is no cusd fit rejecting it.
Why do researchers use null hypothesis instead of alternative hypothesis?
The purpose and importance of the null hypothesis and alternative hypothesis are that they provide an approximate description of the phenomena. The purpose is to provide the researcher or an investigator with a relational statement that is directly tested in a research study.
Do researchers want to prove the null hypothesis?
The null hypothesis, H0 is the commonly accepted fact; it is the opposite of the alternate hypothesis. Researchers work to reject, nullify or disprove the null hypothesis.
When a researcher fails to reject a false null hypothesis?
A type II error is also known as a false negative and occurs when a researcher fails to reject a null hypothesis which is really false. Here a researcher concludes there is not a significant effect, when actually there really is.
Why do we not accept the alternative hypothesis?
If the P-value is less than or equal to the significance level, we reject the null hypothesis and accept the alternative hypothesis instead. If the P-value is greater than the significance level, we say we “fail to reject” the null hypothesis.
When the researcher accepts the null hypothesis when should be rejected?
When the null hypothesis is true and you reject it, you make a type I error. The probability of making a type I error is α, which is the level of significance you set for your hypothesis test. An α of 0.05 indicates that you are willing to accept a 5\% chance that you are wrong when you reject the null hypothesis.
When do you reject the null hypothesis and go with the alternative?
When we do find that a relationship (or difference) exists then we reject the null and accept the alternative. If we do not find that a relationship (or difference) exists, we fail to reject the null hypothesis (and go with it).
What happens if data suggests we reject the null?
If data suggests we reject the Null, else we Fail to reject the null in favor of the alternative. The reason behind this concept is that Null hypothesis is the hypothesis, which says there is nothing going on.
Is there such a thing as a positive hypothesis?
The only “positive” statement we may be justified in asserting is that it is likely that the null hypothesis is wrong (i.e., we can reject it), but we can’t say that if the evidence isn’t strong enough to reject, then the null hypothesis has been confirmed.
How do researchers construct their hypotheses?
Typically, the researcher constructs these hypotheses with the expectation (based on the literature and theories in their field of study) that their findings will contradict the null hypothesis, and in turn support the alternative hypothesis. For instance, in our IQ example we may expect to see a difference between arts majors and science majors.