1.What does a significant test statistic tell us?

1. There is an important effect.
2. That the test statistic is larger than we would expect if there were no effect in the population.
3. The hull hypothesis is false.
4. All of the above.

2.What is the relationship between sample size and the standard error of the mean? (Hint: The law of

large numbers applies here: the larger the sample is, the better it will reflect that particular population.)

1. The standard error decreases as the sample size decreases.
2. The standard error is unaffected by the sample size.
3. The standard error increases as the sample size increases.
4. The standard error decreases as the sample size increases.

3.What symbol is used to represent the standard error of the mean?

4.Which of the following statements is true?

1. The standard error is calculated solely from sample attributes.
2. The standard deviation is calculated only from sample attributes.
3. The standard error is a measure of central tendency.
4. All of the above.

5.There are basically two types of statistics - descriptive and inferential. Which of the following sentences

are true about descriptive statistics? (Hint: The answer is in the namedescriptivestatistics).

1. Descriptive statistics enable you to make decisions about your data, for example, is one group mean significantly different from the population mean?
2. Descriptive statistics describe the data.
3. Descriptive statistics enable you to draw inferences about your data, for example does one variable predict another variable?
4. All of the above.

1.Which of the following transformations is most useful for correcting skewed data?

1. Tangent transformation
2. Arcsine transformation
3. Cosine transformation
4. Log transformation

2.The assumption of homogeneity of variance is met when:

1. The variances in different groups are significantly different.
2. The variances in different groups are approximately equal.
3. The variance across groups is proportional to the means of those groups.
4. The variance is the same as the interquartile range.

3.Imagine you conduct a t-test using IBM SPSS and the output reveals that Levene's test for equality of variance is significant. What should you do? (Hint: Levene's test tests the assumption that variances in

different groups are approximately equal.)

1. Interpret the figures in the row labelled 'equal variances assumed'.
2. Conduct a Kruskal-Wallis test instead.
3. Interpret the figures in the row labelled 'equal variances not assumed'.
4. Collect more data.

1.'Children can learn a second language faster before the age of 7'. Is this statement:

1. A non-scientific statement
2. A one-tailed hypothesis
3. A two-tailed hypothesis
4. A null hypothesis

2.If my experimental hypothesis were 'Eating cheese before bed affects the number of nightmares you have', what would the null hypothesis be?

1. Eating cheese before bed gives you more nightmares.
2. Eating cheese before bed gives you fewer nightmares.
3. Eating cheese is linearly related to the number of nightmares you have.
4. The number of nightmares you have is not affected by eating cheese before bed.

3.If my null hypothesis is 'Dutch people do not differ from English people in height', what is my alternative hypothesis?

1. All of the statements are plausible alternative hypotheses.
2. Dutch people are taller than English people.
3. English people are taller than Dutch people.
4. Dutch people differ in height from English people.

4.Of what ispthe probability if the null hypothesis were true? (Hint: NHST relies on fitting a 'model' to the data and then evaluating the probability of this 'model' given the assumption that no effect exists.)

1. pis the probability that the results are due to chance, the probability that the null hypothesis (H0) is true.
2. pis the probability of observing a test statistic at least as big as the one we have if there were no effect in the population (i.e., the null hypothesis were true).
3. pis the probability that the results are not due to chance, the probability that the null hypothesis (H0) is false.
4. pis the probability that the results would be replicated if the experiment was conducted a second time.

5.A Type I error occurs when: (Hint: When we use test statistics to tell us about the true state of the world, we're trying to see whether there is an effect in our population.)

1. We conclude that there is not an effect in the population when in fact there is.
2. We conclude that the test statistic is significant when in fact it is not.
3. The data we have typed into SPSS is different from the data collected.
4. We conclude that there is an effect in the population when in fact there is not.