5. In formulating hypotheses for a statistical test of significance, the null hypothesis is often: A) a statement of "no effect" or "no difference." B) the probability of observing the data you actually obtained. C) a statement that the data are all 0. D) 0.05.
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Step 1: The null hypothesis in a statistical test of significance is often a statement of "no effect" or "no difference" between samples. Show more…
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Sarvesh S.
4. A result was said to be statistically significant at the 5% level. This means: a. the null hypothesis is probably wrong b. the result would be unexpected if the null hypothesis were true c. the null hypothesis is probably true d. none of the above.
Christopher D.
Which of the following is a reason to use statistics to evaluate data? a. It enables you to prove that your hypothesis is correct. b. It enables you to exclude data that do not fit your hypothesis. c. It makes it possible to exclude the null hypothesis. d. It enables you to predict experimental results. e. It accounts for variation in scientific measurements.
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