Overview
Examples: 1. True, 2. False, and so on to include 20 item numbers with True OR False answers.
Chapter 5
1. A ?-score of ? = −0.25 indicates a location that is slightly below the mean.
2. A population distribution of scores has ? = 80 and ? = 6. In this distribution a ?-score of ? = +2.00 identifies an
X-value that is twelve points above the mean.
3. A positive ?-score always corresponds to a score greater than the mean.
4. For a sample with ? = 40 and ? = 12, a ?-score of ? = −0.50 corresponds to a score of ? = 46.
5. A population with ? = 100 and a ? = 20 is transformed into ?-scores. The resulting distribution of ?-scores will have
a mean of zero.
Chapter 6
6. For a normal distribution the score that separates the highest 10% from the rest of the scores is called the 90
th
percentile.
7. For a normal distribution, the probability of selecting a score less than the mean is 50%.
8. For a normal distribution, a ?-score value of ? = −0.84 separates the lowest 20% of the distribution from the highest
80%.
9. For a normal distribution, the proportion in the tail beyond ? = −2.00 is ? = −0.0228.
10. For a normal distribution, the proportion in the tail beyond ? = +1.00 is exactly the same as the proportion in the tail
beyond ? = −1.00.
Chapter 7
11. The mean of the distribution of sample means is called the expected value of M.
12. The standard deviation of the distribution of sample means is called the standard error of M.
13. As sample size increases, the expected value of M stays constant.
14. As sample size increases, the standard error of M decreases.
15. If random samples, each with ? = 4 scores, are selected from a normal population with ? = 80 and ? = 10, then the
distribution of sample means will have a standard error of 5.
Chapter 8
16. A hypothesis test is an inferential technique that uses the data from a sample to draw inferences about the population.
17. A sample of ? = 25 individuals is selected from a population with ? = 80 and a treatment is administered to the
sample. If the treatment has no effect, then the sample mean should be close to 80 and should lead you to fail to reject the
null hypothesis.
18. The critical region consists of extreme sample values that are very unlikely to occur if the null hypothesis is true.
19. If the obtained sample value is in the critical region, then we conclude that the data provide support for the null
hypothesis.
20. In a research report, the term statistically significant is used to indicate that the null hypothesis was rejected.