Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Statistics for behavioral sciences > exam 3 > Flashcards

exam 3 Flashcards

1
Q

What is the main advantage that ANOVA testing has compared with t testing?

A

It can be used to compare two or more treatments

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

ANOVA is to be used in a research study using two therapy groups. For each group, scores will be taken before the therapy, right after the therapy, and one year after the therapy. How many different sample means will there be?

A

6

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Which of the following most accurately describes the F-ratio in ANOVA testing?

A

The F-ratio is the ratio of the variance between sample means and the variance expected with no treatment effect.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

A researcher is conducting an ANOVA test to measure the influence of the time of day on reaction time. Participants are given a reaction test at three different periods throughout the day: 7 a.m., noon, and 5 p.m. In this design, there are _______ factor(s) and ______ level(s).

A

1, 3

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

In an ANOVA study on the impact that various forms of cellphone use have on driving speed, a researcher concludes that there are no systematic treatment effects. What was the F-ratio closest to?

A

An F-ratio near 1 indicates that the differences between treatments (numerator) are random and unsystematic, just like the differences in the denominator. With an F-ratio near 1, we conclude that there is no evidence to suggest that the treatment has any effect.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

If the variance between treatments increases and the variance within treatments decreases, what will happen to the F-ratios and the likelihood of rejecting the null hypothesis in an ANOVA test?

A

The F-ratio and the likelihood of rejecting the null hypothesis will increase.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

In an analysis of variance, the primary effect of large mean differences within each sample is to increase the value for

A

the variance within treatments

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

An analysis of variance is used to evaluate the mean differences for a research study comparing 4 treatment conditions and 7 scores in each sample. How many total degrees of freedom are there?

A

27

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

eta squared (long elephant n)

A

ss between/ ss total

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Under what conditions might a post hoc test be performed following ANOVA?

A

it’s done after we reject the null hypothesis. If they’re 2 treatments, we know which is effective, so 3 or more.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Which of the following will increase the likelihood of rejecting the null hypothesis using ANOVA?

A

A decrease of SSwithin
b. An increase in the sample sizes

Because SSwithin occurs in the denominator of F, a decrease in SSwithin will cause an increase in F, which will increase the likelihood of rejecting the null hypothesis. An increase in sample sizes will also increase the likelihood of rejecting the null hypothesis.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

When a research study involves more than one factor, what is it called?

A

A factorial design

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

In a two-factored ANOVA, how many F-ratios are calculated?

A

3

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

If a researcher is studying the reaction time of males and females at 6:00 a.m. and at 6:00 p.m. using a two-factor, independent-measures ANOVA, which two mean differences make up the two main effects?

A

gender and time of day

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

In a two-factor, independent-measures ANOVA, an interaction between factors occurs when?

A

a. When the effect of one factor depends on the different levels of a second factor.
b. When the mean differences between individual treatment conditions are different from what would be predicted from the overall main effects of the factors.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

An interaction in a two-factor, independent-measured ANOVA can be seen from the graph of the two factors when _________________.

A

they are not parallel, and or they intersect.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

In a two-factor, independent-measures ANOVA, if SS between treatments = 67, SSA = 12, and SSB = 15, what is SSA×B?

A

40

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

In a two-factor, independent-measures ANOVA, with each factor having the same number of levels, if dfA×B = 4, how many levels does each factor have?

A

3

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

What happens in the first stage of a two-factor ANOVA?

A

The total variability is divided into “between-treatments” and “within-treatments.”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

In a two-factor, independent-measures ANOVA, when is FA guaranteed to be equal to FB?

A

when MSA = MSB

Because the denominators of FA and FB are equal, the two F-ratios are the same whenever their numerators are equal, i.e. MSA = MSB. SSA = SSB 
only guarantees equal F-ratios when we also have dfA = dfB. See 14.2: An Example of the Two-Factor ANOVA and Effect Size.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Why is testing a simple main effect in a two-factor ANOVA essentially the same thing as a single factor ANOVA?

A

Because we are restricting data to the first row of the data matrix.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

What information can we obtain from a simple main effect analysis in a two-factor ANOVA?

A

a. An evaluation of the effects of one factor

b. An evaluation of one factor’s interaction with the second factor

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

In a particular independent-measures design, two treatment groups were present, but the researcher noticed a high level of variability within each group, which led to a t-statistic that was too low. Upon further investigation, the researcher noticed that there were consistent individual differences, in that male scores were consistently higher than the female scores in both treatment groups. What can be done to salvage this study?

A

The researcher can use the same data, create a second factor of gender, split the treatment groups into two subgroups, and perform a two-factor ANOVA.

24
Q

A two-factor study has 3 levels of Factor A and 4 levels of Factor B. Because the ANOVA produces a significant interaction, the researcher decides to evaluate the simple mean effect of Factor A for each level of Factor B. How many F-ratios will this require?

A

4

25
Q

A researcher runs an independent-measures design for two treatment groups. The variability within each group is high, so the researcher splits each group by the participant variable of gender and attempts to run a factorial design ANOVA. The variability within each group is still high. What can the researcher conclude?

A

Gender was not an individual difference in the original treatment groups.

26
Q

A researcher introduces a second factor due to individual differences to create a factorial design from an independent-measures design. Why can this help the researcher draw conclusions about the data set?

A

It can reduce the variability within the treatment groups.

27
Q

Which of the following is measured and described by a correlation?

A

A correlation measures and describes three things: the direction of a relationship, the form of a relationship, and the strength of a relationship.

28
Q

The relationship between age and height in trees is most likely a _____________ correlation.

A

positive

In a positive correlation, the two variables tend in the same direction. In this case, as age increase, height tends to increase as well.

29
Q

Which of the following values represents a perfect correlation?

A

1 and -1.00

30
Q

The population of a bacteria colony is measured at 3:00, 3:15, and 3:30. The corresponding population values are 40, 80, and 160. Explain why this does or does not have a linear correlation.

A

This does not have a linear form because the population does not increase by the same amount every fifteen minutes.

31
Q

A set of n = 25 pairs of X and Y values has a Pearson correlation of r = 0.24. If each of the X values were multiplied by –3, and each Y value is increased by 2, then what is the correlation for the resulting data?

A

–0.24

When a set of scores is multiplied by a negative constant, the Pearson correlation is only changed by flipping the sign. When a set of scores is increased by the same amount, the Pearson correlation is not changed at all.

32
Q

Which of the following is an application of correlations

A

Prediction
Validity
Reliability
Theory Verification

33
Q

Which of the following are accurate considerations of correlations?

A

The value of a correlation can be affected greatly by the range of scores represented in the data. Further, one or two extreme data points can have a dramatic effect on the value of a correlation (outliners). High SS scores do not dramatically decrease the effectiveness of a correlation.

34
Q

hypothesis for correlation

A

Ho: p = 0
H1: p not equal to 0

one tailed Ho: P less than or equal to 0
H1: P is greater than 1

35
Q

What can be used to conduct the hypothesis test for the Pearson correlation?

A

Either a t statistic or an F-ratio can be used to conduct the hypothesis test for the Person correlation.

36
Q

What is the difference between the Pearson correlation and the Spearman correlation?

A

When the Pearson correlation formula is used with data from an ordinal scale (ranks), the result is called the Spearman correlation.

37
Q

In preparation for a Spearman correlation, what are the ranks for the following data set?
(335689)

A

1.5, 1.5, 3, 4, 5, 6

38
Q

Which of the following situations is an example of a dichotomous variable and would therefore suggest the possible use of a point-biserial correlation.

A

Whether a computer is running the latest version of an operating system or an earlier version

A variable with only two values is called a dichotomous variable or a binomial variable. The only variable in these choices with exactly two values is whether or not a computer is running the latest version of an operating system.

39
Q

Which situation would be appropriate for obtaining a phi-coefficient with a Pearson test?

A

Comparing gender with whether or not someone has a PhD

In order to use a phi-coefficient, both X and Y have to be dichotomous. When comparing gender with whether or not someone has a PhD, there are two outcomes for each: male/female, and yes/no. All other options have more than two choices in at least one of the factors.

40
Q

Which of the following is not one of the purposes of a line of regression?

A

A line of regression is a visual representation of the relationship between two variables. It serves to identify the central tendency of this relationship and can be used to predict missing values for each of the variable. It does little to display variability for each variable.

41
Q

If the Pearson correlation between X and Y is negative, what is the slope of the regression line?

A

Negative

42
Q

If the Pearson correlation between X and Y is r = –1, how many (X, Y) pairs do you need to compute the regression line?

A

If r = –1, then the correlation is perfect. This means that all of the ordered pairs will fall on the regression line. To determine the line, we only need two of the available points.

43
Q

For the following data set, find the Y-intercept of the standardized regression line.

A

For a standardized regression line, the Y-intercept is always 0.

44
Q

When a linear regression is obtained for X, Y and residuals are computed for Y, what is the sum of these residuals?

A

For a linear regression, the sum of the residuals is always 0.

45
Q

If the Pearson correlation between 11 pairs of X and Y is r = 0.5, and SSY = 36, find the standard error of estimate.

A

1.732

46
Q

Testing the significance of a regression equation is equivalent to testing the significance of the _________________.

A

Pearson correlation

47
Q

Which of the following could represent a multiple regression equation?

A

Y = 2X1 + 3X2

A multiple regression equation is one in which Y is related to two different variables, X1 and X2.

48
Q

The multiple regression equation between Y and two independent variables, X1 and X2, is Y = 1.54X1 + 3.51X2 + 1.17. Predict the Y value if X1 = 5 and X2 = 8.

A

If X1 = 5 and X2 = 8, then Y = (1.54)(5) + (3.51)(8) + 1.17 = 36.95.

49
Q

A multiple regression equation with two predictor variables produces R = 0.8. What portion of the variability for the Y scores is predicted by the equation?

A

64%

50
Q

A multiple regression equation

A

Multiple regression provides an alternative procedure for using a partial correlation. Specifically, the regression analysis evaluates the contribution of each predictor variable after the influence of the other predictor has been considered. Thus, you can determine whether each predictor variable contributes to the relationship by itself or simply duplicates the contribution already made by another variable.

51
Q

Data from a recent study suggests that 61% of the population that buys a certain product is female. In a sample of n = 200 people that purchased this product, 136 were female. What is the expected frequency of male purchasers in this sample?

A

78

52
Q

What does the chi-square test for independence evaluate?

A

The chi-square test for independence uses the frequency data from a sample to evaluate the relationship between two variables in the population. Each individual in the sample is classified on both of the two variables, creating a two-dimensional frequency distribution matrix.

53
Q

Which of the following tests has a fundamental purpose of evaluating the significance of the relationship between two variables?

A

I. Chi-square
III. Tests of mean difference
IV. ANOVA

54
Q

Which statistic does the Median Test for Independent Samples rely on?

A

In a median test for independent samples, the data for a particular variable is grouped into two categories: “Above the Median” and “Below the Median”. A matrix is created, and a chi-square statistic is calculated.

55
Q

point-biserial correlation

A

A correlation between two variables where one of the variables is dichotomous (boy vs girl)

Statistics for behavioral sciences (3 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions