Deck 8: Introducing Inferential Statistics

Question 1

One of the keys to successful operation of the central limit theorem is that the sample size must be ___________________.

A) less than 20
B) greater than 30
C) greater than 40
D) greater than 50

Answer 1

B

Question 2

When examining the significance of the relationship between two variables, what test should you use?

A) t-test for dependent means
B) t-test for independent means
C) t-test for the correlation coefficient
D) analysis of variance

Answer 2

C

Question 3

What is rejecting the null hypothesis when it is true?

A) Type I error
B) correct
C) Type II error
D) variance

Answer 3

A

Question 4

To compare findings from many different studies that use the same dependent variable, what technique is used?

A) MANOVA
B) factor analysis
C) t-test
D) meta-analysis

Question 5

The level of significance is similar to which of the following?

A) a Type I error
B) a Type II error
C) a bell curve
D) the null hypothesis

Question 6

When a researcher draws conclusions about a population based on the results of a test on a sample, he or she is most likely using which of the following?

A) inductive statistics
B) deductive statistics
C) descriptive statistics
D) inferential statistics

Question 7

Which of the following states that regardless of the shape of the population, the means of all the samples selected will be normally distributed?

A) Type I Error
B) Type II Error
C) central limit theorem
D) factor analysis

Question 8

When examining whether group differences occur on more than one dependent variable, what should be used?

A) factor analysis
B) MANOVA
C) t-test for independent means
D) t-test for dependent means

Question 9

What is the correct order of steps in testing a hypothesis?

A) statement of null hypothesis, setting level of risk, selection of test statistic
B) statement of null hypothesis, computation of test statistic, selection of test statistic
C) selection of test statistic, comparison of obtained value to critical value, computation of test statistic
D) selection of test statistic, computation of test statistic, statement of null hypothesis

Question 10

Which of the following has the largest potential to decrease the accuracy of an inference made to a population based on a sample?

A) variance
B) a heterogeneous sample
C) a homogeneous sample
D) sampling error

Question 11

What does a level of significance of .05 mean?

A) there is a .5% chance of Type I error
B) there is a 5% chance of Type I error
C) there is a .05% chance of Type I error
D) there is a 50% chance of Type I error

Question 12

What is the statistical test for examining the significant difference between two means from two unrelated groups?

A) t-test for dependent means
B) MANOVA
C) t-test for independent means
D) factor analysis

Question 13

What does the central limit theorem enable researchers to do?

A) compare means from two independent samples
B) generalize the results from a sample to a population without knowing the exact nature of the population's distribution
C) compute the significance of a relationship between two variables
D) reduce the possibility that chance accounts for variability in the variable of interest

Question 14

How can Type II errors be reduced?

A) decreasing sample size
B) homogeneous population
C) increasing sample size
D) heterogeneous population

Question 15

If Helen mistakenly accepts her null hypothesis when it should be rejected, what has occurred?

A) Type I error
B) Type II error
C) researcher bias
D) none of the above

Question 16

When investigating a relationship between two variables, what is the most acceptable initial explanation of the relationship?

A) the treatment
B) chance
C) researcher bias
D) defined factors

Question 17

What is the crucial element in making an accurate inference?

A) obtaining a representative sample of the population
B) obtaining a representative population of the sample
C) being well versed in multivariate statistical procedures
D) doing a good literature review

Question 18

If the two groups you are comparing are related to each other, what test should you use?

A) factor analysis
B) MANOVA
C) t-test for independent means
D) t-test for dependent means

Question 19

What technique reduces the number of variables in a construct?

A) effect size
B) MANOVA
C) factor analysis
D) t-test

Question 20

Which of the following statements is true?

A) Significance is better than meaningfulness.
B) Meaningfulness is better than significance.
C) Both significance and meaningfulness are equal in value.
D) Neither significance nor meaningfulness is important in a study.

Question 21

What is the standard metric used in most meta-analytic studies called?

A) standard deviation
B) effect size
C) sampling mean
D) standard error

Question 22

The minimum or maximum value that one would expect the test statistic to yield if the null hypothesis is true is an example of which of the following?

A) critical value
B) F value
C) t-test score
D) sampling mean

Question 23

The first step for conducting a meta-analysis is ____________.

A) decide on an appropriate statistical software package
B) develop a system to code the various dimensions of the study
C) collect as many studies as possible or at least a representative group)
D) determine the most appropriate type of descriptive or correlational technique to examine the outcomes of the studies as a whole

Question 24

If Professor Columbo is interested in the general trend of research findings regarding infant visual attention and childhood intelligence, what technique would be most amenable to his inquiry?

A) Analysis of Variance ANOVA)
B) Meta-analysis
C) Multiple Analysis of Variance MANOVA)
D) Factor analysis

Question 25

The critical value decreases when_______________________________.

A) the sample size increases
B) the sample size decreases
C) the sample is heterogeneous
D) the sample is homogeneous

Question 26

Why would you do a meta-analytic study?

Question 27

What is the difference between descriptive and inferential statistics?

Question 28

What can you conclude if the obtained value of a test statistic exceeds the critical value?

A) The null hypothesis cannot be rejected.
B) You made an error when calculating the test statistic.
C) The null hypothesis can be rejected.
D) Your obtained value is not statistically significant.

Question 29

The critical value is__________________________________.

A) the value found after calculating a test statistic
B) the value needed to determine a valid study
C) the value needed to determine a reliable study
D) the value needed to reject the null hypothesis

Question 30

Which of the following statements regarding statistical significance is FALSE?

A) The level of statistical significance and Type I error are the same thing.
B) Statistical significance is the degree of risk you are willing to take that you will reject a null when it is actually true.
C) When your results are found to be statistically significant, you can conclude that they will have a meaningful effect in the clinic.
D) The researcher can determine the level of statistical significance.

Question 31

What is the difference between statistical significance and meaningfulness? Which is more important?

Question 32

In order to determine the critical value, which two pieces of information are needed?

A) mean and sample size
B) degrees of freedom and level of significance
C) mean and standard deviation
D) degrees of freedom and variance

Question 33

What assumption forms the basis for inference?

A) A researcher can select a sample that is similar to the population from which it came.
B) Null hypotheses can be proven to be false.
C) A researcher can select the level at which he/she is willing to risk Type I error.
D) The central limit theorem is false.

Question 34

Explain what t₁₂₀ = 2.00, p < .05 means.

Question 35

If Dr. Robinson rejects the null hypothesis after observing a test statistic which exceeds the critical value at the .05 level, there is_____________________________________________.

A) a 95% chance that the null hypothesis is actually true
B) a 5% chance that the null hypothesis is actually true
C) a 5% chance that the null hypothesis is actually false
D) no chance that the null hypothesis is actually true

Question 36

What are the steps involved in testing a hypothesis?

Question 37

What factors decrease the likelihood of making a Type II error?