How are hypotheses valuable even if they are not supported by data?

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How are hypotheses valuable even if they are not supported by data?

If the hypothesis has been proven wrong or falsifiable, it is important because if something is proven wrong, then the opposing hypothesis must be true. Therefore, it leads to determining the correct find.

Did your results support your hypothesis?

What you can say is that your results SUPPORT the original hypothesis. If your original hypothesis didn’t match up with the final results of your experiment, don’t change the hypothesis. Remember, a science fair experiment isn’t a failure simply because does not agree with your hypothesis.

How do you conclude a hypothesis test?

To get the correct wording, you need to recall which hypothesis was the claim. If the claim was the null, then your conclusion is about whether there was sufficient evidence to reject the claim. Remember, we can never prove the null to be true, but failing to reject it is the next best thing.

What can be concluded by failing to reject the null hypothesis?

Failing to reject the null indicates that our sample did not provide sufficient evidence to conclude that the effect exists. However, at the same time, that lack of evidence doesn’t prove that the effect does not exist. Capturing all that information leads to the convoluted wording!

When you reject the null hypothesis is there sufficient evidence?

we reject the null hypothesis of equal means. There is sufficient evidence to warrant rejection of the claim that the three samples come from populations with means that are all equal.

Can you reject the null and alternative hypothesis?

If our statistical analysis shows that the significance level is below the cut-off value we have set (e.g., either 0.05 or 0.01), we reject the null hypothesis and accept the alternative hypothesis. You should note that you cannot accept the null hypothesis, but only find evidence against it.

Which of the following best differentiates a theory from a hypothesis?

Hypotheses must be testable and falsifiable. The best statement, which distinguishes hypotheses from theories in science is “Hypotheses usually are relatively narrow in scope; theories have broad explanatory power.”

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