Question 1

Statistics that assess the reliability of your findings are called _____ statistics.
A) descriptive
B) inferential
C) evaluative
D) reliability

Accepted Answer

Inferential statistics are used to assess the reliability of findings by making inferences about a population based on a sample.

Question 2

The distribution of a statistic that one would get by taking every possible sample of n scores from a population is the _____ of the mean.
A) sampling distribution
B) frequency distribution
C) skewed distribution
D) None of the answers is correct.

Accepted Answer

The sampling distribution of the mean is the distribution of sample means over repeated sampling from the same population.

Question 3

An estimate of the amount of variability in sample means expected across a series of samples is provided by the:
A) standard deviation of the mean.
B) standard error of the mean.
C) standardized variability around the mean.
D) error variance.

Accepted Answer

The standard error of the mean is an estimate of the amount of variability in sample means expected across a series of samples. It is calculated by dividing the standard deviation of the population by the square root of the sample size.

Question 4

If you want the average of 10 scores to equal 100, you can choose any numbers you want for 9 of the scores, but the 10^th score will have to be whatever number will make the average of the scores equal 100. Thus, the _____ are 9. A) dependent variables B) degrees of variability C) degrees of freedom D) independent variables

Accepted Answer

Degrees of freedom refer to the number of values in a calculation that are free to vary. In this case, you can choose any values for 9 scores, but the 10th score is determined by the requirement that the average equals 100, leaving 9 degrees of freedom.

Question 5

The main difference between parametric and nonparametric statistics is that a parametric statistic:
A) makes no assumptions about the population distribution underlying a sample distribution.
B) assumes that the underlying population distribution is skewed and makes allowances for the skewness.
C) cannot be used with dependent measures scaled on ratio and interval scales.
D) estimates the value of a population parameter from the characteristics of a sample.

Accepted Answer

Parametric statistics involve estimating population parameters based on sample data, assuming the data follows a specific distribution, typically normal.

Question 6

The _____ allows one to examine the relationship between experimentally manipulated variables while statistically controlling another variable that may be correlated with them.
A) analysis of covariance
B) Mann-Whitney U test
C) t test for independent samples
D) z test for proportions

Accepted Answer

Analysis of covariance (ANCOVA) is used to examine the relationship between variables while controlling for the effects of other variables.

Question 7

Means of samples drawn randomly from a single population differ only because of:
A) the central limit theorem.
B) poorly designed independent variables.
C) sampling error.
D) None of the answers is correct.

Accepted Answer

Means of samples drawn randomly from a single population differ due to sampling error, which is the natural variation that occurs by chance when a sample is taken from a population.

Question 8

The hypothesis that sample means are drawn from the same population is referred to as the _____ hypothesis.
A) alternative
B) equivalence
C) sampling error
D) null

Accepted Answer

The null hypothesis posits that there is no significant difference between specified populations, suggesting that any observed difference is due to sampling or experimental error.

Question 9

The hypothesis that sample means are drawn from different populations is called the _____ hypothesis.
A) alternative
B) nonequivalence
C) null
D) differential means

Accepted Answer

The alternative hypothesis suggests that there is a difference between populations, meaning the sample means are drawn from different populations.

Question 10

A statistically significant difference between sample means leads us to:
A) accept that the observed differences between sample means were not due to chance.
B) conclude that the means represent a single underlying population.
C) accept that the observed differences were due mainly to chance fluctuations in the data.
D) None of the answers is correct.

Accepted Answer

A statistically significant difference suggests that the observed differences between sample means are unlikely to be due to chance, indicating a real effect or difference.

Question 11

Which of the following is a Type I statistical error?
A) Saying that an independent variable had no effect when in fact it did
B) Saying that an independent variable had an effect when in fact it did not
C) Saying that an independent variable had a weak effect when in fact it had a strong effect
D) Identifying one independent variable as affecting the dependent variable when in fact a different independent variable had the effect

Accepted Answer

A Type I error occurs when a true null hypothesis is incorrectly rejected, meaning we conclude there is an effect when there is none.

Question 12

A statistical test led Dr. Jones to incorrectly decide that his independent variable had no effect when in fact it did. Dr. Jones committed a(n):
A) Type I error.
B) Type II error.
C) Type III error.
D) alpha error.

Accepted Answer

A Type II error occurs when a statistical test fails to reject the null hypothesis when it is actually false. In this case, Dr. Jones' test led him to conclude that his independent variable had no effect when in fact it did, which is a Type II error.

Question 13

By setting a criterion probability for rejecting the null hypothesis, one can set the rate at which one will commit Type I errors. This criterion that is the probability of making a Type I error is known as the _____.
A) alpha level
B) beta level
C) effect size
D) F ratio

Accepted Answer

The alpha level is the criterion probability set by the researcher for rejecting the null hypothesis, and it represents the probability of committing a Type I error.

Question 14

In the context of inferential statistics, which of the following statements is true of the alpha level?
A) The minimum acceptable alpha traditionally has been set at .01.
B) The alpha value determines the probability of making a Type II error.
C) The particular level of alpha one adopts is called the effect size.
D) The probability of making a Type I error is less when the value of alpha is small.

Accepted Answer

The alpha level is the threshold for statistical significance, and it represents the probability of making a Type I error (rejecting a true null hypothesis). A smaller alpha level reduces the probability of making a Type I error.

Question 15

A one-tailed test is used:
A) in any situation where finding statistical significance is important.
B) when you want to minimize the possibility of making a Type II error.
C) if you are interested only in whether the obtained value of the statistic falls in one tail of the sampling distribution for that statistic.
D) if you are interested in bidirectional differences between means (for example, the experimental group mean is either higher or lower than the control group mean).

Accepted Answer

A one-tailed test is used when the research hypothesis predicts the direction of the effect, meaning the interest is only in one direction of the distribution.

Question 16

At a given significance level, a one-tailed test:
A) is less likely to detect real differences between means than is a two-tailed test.
B) has a higher critical value than does a two-tailed test.
C) is less accurate than a two-tailed test.
D) is more likely to detect real differences between means than is a two-tailed test, given that the correct tail was selected for the test.

Accepted Answer

A one-tailed test is more powerful than a two-tailed test in detecting a real difference in the specified direction because it allocates all the significance level to one tail, making it more likely to reject the null hypothesis if the effect is in the predicted direction.

Question 17

According to the text, a two-tailed test should be used:
A) unless there is a compelling a priori reason not to.
B) if you are sure that the difference between your means is sufficiently large to ensure statistical significance.
C) when you are interested in controlling Type II errors but less interested in controlling Type I errors.
D) None of the answers is correct.

Accepted Answer

A two-tailed test is typically used unless there is a specific reason to use a one-tailed test, as it tests for the possibility of an effect in two directions, providing a more conservative approach.

Question 18

Which of the following is not one of the assumptions that underlie parametric inferential tests?
A) The scores have been sampled randomly from a population.
B) The sampling distribution of the mean is normal.
C) The sample sizes are large.
D) The within-groups variances are homogeneous.

Accepted Answer

Parametric tests do not necessarily require large sample sizes; they assume normality and homogeneity of variance, but not a specific sample size.

Question 19

Serious violations of one or more of the assumptions underlying parametric inferential tests:
A) have little effect on the validity of a statistic.
B) will lead one to commit a Type I error either more or less often than the stated alpha probability.
C) affect Type I error rates but not Type II error rates.
D) affect Type II error rates but not Type I error rates.

Accepted Answer

Serious violations of assumptions can affect the Type I error rate, causing it to deviate from the nominal alpha level, leading to either an increased or decreased likelihood of committing a Type I error.

Question 20

The _____ is used when there is data from two groups of participants who were assigned at random to the two groups.
A) analysis of variance (ANOVA)
B) t test for independent samples
C) Bayesian approach
D) t test for correlated samples

Accepted Answer

The t-test for independent samples is used when there is data from two groups of participants who were assigned at random to the two groups.

Quiz 14: Using Inferential Statistics

Statistics that assess the reliability of your findings are called _____ statistics.

The distribution of a statistic that one would get by taking every possible sample of n scores from a population is the _____ of the mean.

An estimate of the amount of variability in sample means expected across a series of samples is provided by the:

If you want the average of 10 scores to equal 100, you can choose any numbers you want for 9 of the scores, but the 10^th score will have to be whatever number will make the average of the scores equal 100. Thus, the _____ are 9.

The main difference between parametric and nonparametric statistics is that a parametric statistic:

The _____ allows one to examine the relationship between experimentally manipulated variables while statistically controlling another variable that may be correlated with them.

Means of samples drawn randomly from a single population differ only because of:

The hypothesis that sample means are drawn from the same population is referred to as the _____ hypothesis.

The hypothesis that sample means are drawn from different populations is called the _____ hypothesis.

A statistically significant difference between sample means leads us to:

Which of the following is a Type I statistical error?

A statistical test led Dr. Jones to incorrectly decide that his independent variable had no effect when in fact it did. Dr. Jones committed a(n) :

By setting a criterion probability for rejecting the null hypothesis, one can set the rate at which one will commit Type I errors. This criterion that is the probability of making a Type I error is known as the _____.

In the context of inferential statistics, which of the following statements is true of the alpha level?

A one-tailed test is used:

At a given significance level, a one-tailed test:

According to the text, a two-tailed test should be used:

Which of the following is not one of the assumptions that underlie parametric inferential tests?

Serious violations of one or more of the assumptions underlying parametric inferential tests:

The _____ is used when there is data from two groups of participants who were assigned at random to the two groups.