STATISTICS HYPOTHESIS TESTING

If a researcher takes a large enough sample, he/she will almost always obtain:

• virtually significant results

• practically significant results

• consequentially significant results

• statistically significant results

The null and alternative hypotheses divide all possibilities into:

• two sets that overlap

• two non-overlapping sets

• two sets that may or may not overlap

• as many sets as necessary to cover all possibilities

Which of the following is true of the null and alternative hypotheses?

• Exactly one hypothesis must be true

• both hypotheses must be true

• It is possible for both hypotheses to be true

• It is possible for neither hypothesis to be true

One-tailed alternatives are phrased in terms of:

• ≠

• < or >

• or =

• ≤ or ≥

The chi-square goodness-of-fit test can be used to test for:

• significance of sample statistics

• difference between population means

• normality

• probability

A type II error occurs when:

• the null hypothesis is incorrectly accepted when it is false

• the null hypothesis is incorrectly rejected when it is true

• the sample mean differs from the population mean

• the test is biased

Of type I and type II error, which is traditionally regarded as more serious?

• Type I

• Type II

• They are equally serious

• Neither is serious

You conduct a hypothesis test and you observe values for the sample mean and sample standard deviation when n = 25 that do not lead to the rejection of . You calculate a p-value of 0.0667. What will happen to the p-value if you observe the same sample mean and standard deviation for a sample > 25?

• Increase

• Decrease

• Stay the same

• May either increase or decrease

The form of the alternative hypothesis can be:

• one-tailed

• two-tailed

• neither one nor two-tailed

• one or two-tailed

A two-tailed test is one where:

• results in only one direction can lead to rejection of the null hypothesis

• negative sample means lead to rejection of the null hypothesis

• results in either of two directions can lead to rejection of the null hypothesis

• no results lead to the rejection of the null hypothesis