Which of the following statements is TRUE? 0.01 means there is a 1% chance that we fail to reject the null hypothesis when the alternative hypothesis is true. - If an effect is substantively significant, then it must also be statistically significant. We reject the null hypothesis when p-value is larger than the significance level. If we want to reduce the probability of a Type II error, the probability of a Type I error will increase.

A researcher expects a treatment to produce an increase in the population mean. The treatment is evaluated using a one tailed hypothesis test, and the test produces z = -1.85. Based on this result, what is the correct statistical decision? O The researcher should reject the null hypothesis with either a = .05 or α = .01. O The researcher should reject the null hypothesis with a = .05 but not with α = .01. O cannot answer without additional information O The researcher should fail to reject Ho with either a = .05 or α = .01.

A hypothesis test on a regression coefficient fails to reject the null hypothesis at the 5% significance level. This means:

“Type I Error Blues,” by David Stein The managers huddled to see if they had won or lost. Did the new process from 2 months before yield data showing a reduction in cost? Or was it merely a matter of chance… Too soon to do the data dance?   So they set about the business of crafting a hypothesis test In order to conclude which process was best. With the null hypothesis meaning “status quo”, no change evident They quickly concluded H0 could not stand, as was their true intent.   Just one month later, they realized their grave mistake! A Type II error would have been so much safer, for goodness sake. Alas, their final huddle was a sad one with HR Director Bob. He told them to go back to training school as each was now in need of a new job.   What was the likely managerial mood and outcome on the days immediately following the (erroneous) conclusion to reject this null hypothesis? What would have been the likely managerial mood and outcome on the days immediately following an…

Evaluate the significance of the p-value. You can think of the p-value as the probability that the null hypothesis is true. A value greater than 0.05 indicates that in more than 1 in 20 (or more than 5%) repetitions of an experiment of the same size, the observed deviation from predicted valuescould have been obtained by chance, even if the null hypothesis is actually true; the data are therefore not significant for rejecting the null hypothesis. Statisticians have arbitrarily selected the 0.05 p-value as the boundarybetween rejecting or not rejecting the null hypothesis. A p-value of less than 0.05 means that you can consider the deviation to be significant, and you can reject the null hypothesis.

Pearson’s correlation is the only statistical test that can measure the relationship between two variables. a. True b. False   A strong correlation indicates there is a cause-and-effect relationship between two variables. a. True b. False   Within a hypothesis test, estimated standard error provides a measurement of which of the following: a. The typical amount of sampling error expected when the null hypothesis is true b. The typical mean expected when the null hypothesis is true c. The typical amount of sampling error expected when the null hypothesis is false d.The typical mean expected when the null hypothesis is false

Which one of the following statements is incorrect:   A. A type I error consists of rejecting the null hypothesis when it is true B. A type II error consists of accepting the null hypothesis when it is false C. You can control simultaneously both the Type I and Type II error probabilities when the sample size is fixed D. Hypothesis testing and confidence intervals are related concepts

An researcher has decided to use significant level α = 0.01 for her experiment. What is the consequence? Group of answer choices The probability of a Type II error is small. There is a small chance of rejecting the null hypothesis when it is true. The probability of a Type I error is large. If the null hypothesis is false, the experimenter will easily be able to reject it.

The following data are from a completely randomized design. In the following calculations, use a = 0.05. Treatment Treatment Treatment 2 3 64 82 69 47 71 53 54 87 60 35 64 46 50 76 57 2 148.67 108.67 96.67