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An analysis of variance comparing three treatment conditions produces dftotal = 24. For this ANOVA, what is the value of dfbetween?

2

In analysis of variance, what is measured by the MS values? a. sample variance b. population variance c. the average distance from one mean to another d. the total variability for the set of N scores

A. MS is sort of equivalent to estimate of population variance (S2), yes, but its actually measuring the sample variance

In an analysis of variance, MStotal = MSbetween + MSwithin. True or False

False

In a contingency table, when all the expected frequencies equal the observed frequencies the calculated x2 statistic equals zero. T or F

T

The sum of expected frequencies in chi square must equal N. T or F

T

The sum of the differences between observed and expected frequencies must be zero: T or F

T E-O = 0 bc Etotal = O total

In ANOVA, MS provides a measure of...

variance

5. The chi-square goodness of fit is _________ a one-tailed test with the rejection region in the right tail. A. Always B. Sometimes C. Never

A

An analysis of variance is conducted to determine whether the____differ more than you would expect if the null hypothesis were true A. means of the samples B. variances of the samples C. means of the populations D. variances of the populations

A

which of the following is not one of the assumptions of correlation? A. each variable should vary equally, regardless of the value of the other variable B. data must be randomly selected C. underlying pop fro both variables are normally dist D. homogeneity of variance between the two variables

A D is for ANOVA, corr has a specific one for that

A chi-square test involves a set of counts called "expected counts." What are the expected counts? a. Hypothetical counts that would occur of the alternative hypothesis were true. b. Hypothetical counts that would occur if the null hypothesis were true. c. The actual counts that did occur in the observed data. d. The long-run counts that would be expected if the observed counts are representative.

B

21 If F = 1, the result is statistically significant____. If F=5 the result is statistically significant_____. a) Always, always b) Sometimes, sometimes c) Never, sometimes

C

A research study compares three treatments with n = 5 in each treatment. If the SS values for the three treatments are 25, 20, and 15, then the analysis of variance would produce SSwithin equal to __________. a. 12 b. 20 c. 60 d. cannot be determined from the information given

C

Given a 3 × 4 chi square, how many df are there? (a) 12 (b) 11 (c) 9 (d) 6

D

The table of cells for a chi-square test for independence is called a: A. summery table B. cross-tabulation C. chi-square distribution D. contingency table

D

When is the Tukey's multiple comparison method used? A. To test for normality. B. To test equal variances. C. To test for equality of a group of population means. D. To test for differences in pairwise means.

D

Which of the following is are consequences of analyzing your data with a nonparametric test? A. confidence intervals may not be calculated B. there is an increase in the probability of making a Type II error C. effect size measures may not be available D. all of the above

D

Which combination of factors will produce the largest F-ratio? i. a large mean differences between groups; ii. small variances within groups iii. large variances within groups; iv. large sample size a. i, ii, and iii b. i, iii, and iv c. ii, iii, and iv d. i and ii only e. i, ii, and iv f. i, ii, iii, and iv

E

In the F-ratio for a repeated-measures ANOVA, what happens to variability caused by the individual differences?

It gets partitioned

what are the two populations in a chi-square test goodness of fit?

pop1: observations pop2: expected in general population

A researcher reports an F-ratio with df= (3, 36) for an ANOVA. How many individual subjects participated in the experiment?

40

The sources of variability that contribute to the within-treatments SS are/is?: I. Difference due to Treatment II. Individual Differences III. Differences due to Experimental Error A. I B. II C. III and II D. I,II, and III

C

Why is it important to plot a scattergraph before calculating a correlation coefficient for a large data set? (a) to check whether both variables are normally distributed (b) to find out whether the correlation is positive or negative (c) to ensure the plots are roughly linear (d) to ensure the data are all present

C

If two variables are independent, the cell frequencies will be a. exactly the same b. concentrated in only two of the cells c. less than the expected frequencies d. determined by random chance

D

In the ANOVA test, if the null hypothesis is false, the means of the different sample should be __________ and the standard deviation of the different samples should be __________. a. similar in value, large in value b. close to zero, equal to their respective variances c. very different, lower in value then the means d. very different in value, relatively low in value

D

In the ANOVA test, if the null hypothesis is true, then a. SSB should be at least twice as much as dfb b. SSW should be much greater than SSB c. the combined dfb and dfw should be much greater than the SST d. the mean square between and the mean square within should be roughly equal in value

D

In the one-way ANOVA where there are k treatments and n observations, the degrees of freedom for the F-statistic are equal to: a. n and k b. k and n c. n-k and k-1 d. k-1 and n-k

D

One limitation of the ANOVA test is that it requires a. nominal level dependent variables b. ordinal level independent variables c. very small samples d. interval-ratio dependent variables

D

The sources of variability that contribute to the between-treatments SS are/is?: I. Difference due to Treatment II. Individual Differences III. Differences due to Experimental Error A. I B. II C. III and II D. I,II, and III

D

An experiment compares two treatment conditions with a sample of n = 20 in each treatment. If the data are analyzed with ANOVA, the analysis would have dftotal = __________. a. 18 b. 19 c. 38 d. 39

D dftotal= Ntotal-1

A chi-square test of the relationship between personal perception of emotional health and marital status led to rejection of the null hypothesis, indicating that there is a relationship between these two variables. One conclusion that can be drawn is: A. Marriage leads to better emotional health. B. Better emotional health leads to marriage. C. The more emotionally healthy someone is, the more likely they are to be married. D. There are likely to be confounding variables related to both emotional health and marital status.

D the question doesnt state if there's a positive or neg correlation, so C cant be the answer

For the study of any number of groups of participants, the square root of the F statistic is equal to the t-statistic. T or F

F. only for two groups of participants

How can you increase power in an ANOVA test?

Increase number of people (dfw), increase number of groups (dfb). (holding alpha rate constant, real group mean difference constant, etc).

Which of the following is incorrect in relation to ANOVA: A. ANOVA is relatively robust to small numbers of participants B. ANOVA is relatively robust to skewed data C. ANOVA is relatively robust to unequal numers of scores in different conditions D. all of the above

all of the above

A treatment effect refers to differences between scores that are caused by the different treatment conditions. The differences (or variability) produced by treatment effects will contribute to __________. a. the numerator of the F-ratio b. the denominator of the F-ratio c. both the numerator and the denominator of the F-ratio d. Treatment effects do not contribute to the F-ratio because they are removed before the F-ratio is computed

A. MSbetween is variability between treatment conditions MSwithin is variability between scores in each treatment

If there are eight categories or classes in a goodness of fit test how many df are there? (a) 8 (b) 7 (c) 6 (d) cannot tell from the information given

B

In analysis of variance, large values for the sample variances will produce a large value for: a. SSbetween treatments b. SSwithin treatments c. SStotal d. Large sample variances will cause all three SS values to be large

B

In one-way ANOVA, the amount of total variation that is unexplained is measured by the: A. sum of squares for treatments. B. sum of squares for error. C. total sum of squares. D. degrees of freedom.

B

Which of the following are not true concerning parametric and nonparametric tests? A. there is a different distribution for each degree of freedom in t, F, r, and chi-square B. F distribution and chi-square distribution are highly positively skewed at low degrees of freedom and cant be negative C. as df increases, critical values (CV's) become less extreme/smaller D. Parametric tests have more power than nonparametric tests

C

Which of the following statements is false? a. The rejection region of the chi-squared goodness-of-fit test has k-1 degrees of freedom, where k is the number of categories (called cells) b. The rejection region of the chi-squared goodness-of-fit test is 22 ,1k , where k is the number of categories and X2 is the value of the test statistics c. The chi-squared goodness-of-fit test involves two categorical variables d. The chi-squared distribution is skewed to the right

C

which of the following is not normally calculated as part of an analysis of variance? A. SStotal B.SSwithin C. MStotal D. MSwithin

C

The X2 statistic is used to test whether the assumption of normality is reasonable for a given population distribution. The sample consists of 5000 observations and is divided into 6 categories (intervals). The degrees of freedom for the chi-square statistic is A. 3 B. 49999 C. 6 D. 5 E. 4

D.

What is the comparison distribution of a correlation test? a. the pearson distribution b. the coefficient distribution c. the t-distribution d. a distribution of correlation coefficients based on many samples of size N.

D. a distribution of correlation coefficients based on many samples of size N=how many people in that particular test.

Which of the following is true pearson correlation coefficient? I. as df increase critical values get less extreme II. the correlation distribution is like the F and chi-square distribution III. the coefficient must be larger than the critical value to reject the null. A. I B. II C. III D. I, II, and III E. I and III

E there is no Pearson distribution! but there is table of CV's for different p levels

The shape of the chi-square distribution depends on the size of the sample. T or F

F depends on the number of categories, but not Ntotal.

If the computed value of a chi-square statistic is less than the critical chi-square value, reject the null hypothesis at a predetermined Type I error rate. T or F

F. Fail to reject

ANOVA null and research hypotheses

Ho: u1:u2:u3....u10 (no difference in treatments) Ha: at least one mean is different.

A chi-squared goodness-of-fit test is always conducted as: a. a lower-tail test b. an upper-tail test c. a two-tail test d. All of the above

B

An analysis of variance produces SSwithin treatments = 40 and MSwithin treatments = 10. In this analysis, how many treatment conditions are being compared? A. 4 B. 5 C. 30 D. 50

B

If an analysis of variance is used for the following data, what would be the effect of changing the value of SS2 to 100? Sample Data M1 = 15 M2 = 25 SS1 = 90 SS2 = 70 A. Increase SSwithin and increase the size of the F-ratio. B.Increase SSwithin and decrease the size of the F-ratio. C. decrease SSwithin and decrease the size of the F-ratio. D.decrease SSwithin and increase the size of the F-ratio.

B

As the number of categories in a chi square table increases so does df: (a) true (b) false (c) sometimes (d) depends on N

D. think its A however

for an experiment comparing more than two treatment conditions you should use analysis of variance rather than separate t tests because _____.

] ANOVA has less risk of a Type I error because several means are compared in one test Conducting many t-tests would inflate Type I error

What happens to the critical value for a chi square test if the number of categories is increased?

critical values get larger

In testing a hypothesis using the chi square test, the theoretical frequencies are based on the a. null hypothesis b. alternative hypothesis c. normal distribution d. chi-squared distribution

A

An independent-measures research study compares three treatment conditions using a sample of n = 5 in each treatment. For this study, the three sample means are, M1 = 1, M2 = 2, and M3 = 3. For the ANOVA, what value would be obtained for SSbetween?

10 (calculate grand mean, then do the square difference for all 15 and add them up)

An analysis of variance produces SSbetween = 40 and MSbetween = 10. In this analysis, how many treatment conditions are being compared?

5

Results of an analysis of variances produce SSbetween = 20, SSwithin = 30, and an F-ratio with df = 2, 15. For this analysis, what is the F-ratio?

5

A chi-square test for independence has df=2. What is the total number of categories (cells in the matrix) that were used to classify individuals in the sample?

6

A chi-square test of goodness fit has df=6. What is the total number of categories (cells in the matrix) that were used to classify individuals in the sample?

7

. In the ANOVA test, what assumption must be made with regard to the population variances? a. They are equal. b. They are unequal. c. They are both less than zero. d. They are equal to each other and to zero.

A

1. Correlation relates the relative position of a score in one distribution to a. the relative position of a score in another distribution b. the mean of the z-scores from another distribution c. the total variance of all scores in both distributions d. the standard deviation of the z-scores for both distributions

A

A treatment effect refers to differences between scores that are caused by the different treatment conditions. The differences (or variability) produced by treatment effects will contribute to __________. a. the numerator of the F-ratio b. the denominator of the F-ratio c. both the numerator and the denominator of the F-ratio d. Treatment effects do not contribute to the F-ratio because they are removed before the F-ratio is computed.

A

How is a chi-square table used in hypothesis testing? A. a computed chi-square statistic form the table is compared to a critical value of chi-square B. the table provides estimates of power for differential significance levels and effect sizes C. the table provides estimates of effect size for different levels of power and significance D. a p value for a computed chi-square statistic is compared to the appropriate level for a specific degrees of freedom

A

If the distribution of the scores of one variable (Y) changes across the categories of another variable (X), the variables a. are associated to some extent b. are related in a way that is statistically significant c. have a cause and effect relationship d. are perfectly associated

A

In an ANOVA, which of the following is most likely to produce a large value for the F-ratio? a. large mean differences and small sample variances b. large mean differences and large sample variances c. small mean differences and small sample variances d. small mean differences and large sample variances

A

In an analysis of variance, large mean differences from one sample to another will produce a large value for: a. SSbetween treatments b. SSwithin treatments c. SStotal d. Large sample variances will cause all three SS values to be large

A

In the ANOVA test, what assumption must be made about the shape of the population distribution? a. The population distribution is normal in shape. b. The test is non-parametric, no assumption need be made about the population. c. Population distribution is a bivariate table. d. The test is parametric, population distribution is assumed to not be normal.

A

In the F-ratio for a repeated-measures ANOVA, what happens to variability caused by individual differences? a. is automatically eliminated from the numerator but must be computed and subtracted out of the denominator b. is automatically eliminated from the denominator but must be computed and subtracted out of the numerator c. is automatically eliminated from both the numerator and the denominator d. must be computed and subtracted out of the numerator and the denominator

A

In the notation for ANOVA, what is referred to by the letters n and N? a. n is the number of scores in each treatment and N is the number of scores in the entire study. b. N is the number of scores in each treatment and n is the number of scores in the entire study. c. n is the number of scores in each treatment but N is not used in the notation for ANOVA. d. N is the number of scores in the entire study but n is not used in the notation for ANOVA.

A

The ANOVA test uses means and standard deviations to compare the amount of variation ____ with the amount of variation ____. a. within categories, between categories b. above categories, below categories c. within sample means, between sample means d. within sample standard deviations, between sample standard deviations

A

The denominator of the pearson corr coefficient formula corrects for two things, which are: A. variability and sample size B. sample size and underestimation of error C. increased risk of Type I errors and order effects D. alternate causal variables and outliers

A

The value of a correlation is reported by a researcher to be r = −0.5. Which of the following statements is correct? a. The x-variable explains 25% of the variability in the y-variable. b. The x-variable explains −25% of the variability in the y-variable. c. The x-variable explains 50% of the variability in the y-variable. d. The x-variable explains −50% of the variability in the y-variable.

A

To determine the critical values in the chi-squared distribution table, you need to know the: A. degrees of freedom. B. sample size. C. probability of Type II error. D. All of these choices are true.

A

Which one of the following best expresses what an analysis of variance is about? A. a comparison of two different ways of estimating population variances B/ a comparison of of the estimates of the true values of 3 or more pop means C. a comparison of of of the estimates of the true values of 3 or more pop variances D. a comparison of 3 or more estimates of the true value of a single population mean

A

If we reject the null hypothesis in a test using analysis of variance, we are concluding that a. the populations from which our samples come are different b. the variable are independent c. the population variances are the same d. the sample means are significantly different

A. not D because in hypothesis testing you are making conclusions about the population

The analysis of variance is a procedure that allows statisticians to compare two or more population a. means b. proportions c. variances d. standard deviations

A. ANOVA is done to compare population means through sample means. The F ratio is of two kinds of pop estimate variances through sample variances

The analysis of variance is a procedure that allows statisticians to compare two or more population: A. means. B. proportions. C. variances. D. standard deviations

A. ANOVA compares more than 2 sample means USING a ratio of population variances

ANOVA assumes that the data to be analysed: A. has a normal dis B. data is interval C. variances in the groups are similar D. all of the above

All of the above

The factor that affects the significance of a correlation most is: (a) whether both variables are interval (b) the p value (c) df (d) all of the above

C

The test statistic of the single-factor ANOVA equals: A. sum of squares for treatments / sum of squares for error. B. sum of squares for error / sum of squares for treatments. C. mean square for treatments / mean square for error. D. mean square for error / mean square for treatments

C

To maximize the statistical power and minimize the prob of committing a type II error, researchers should measure the DV on a(n)______measure A. nominal B. ordinal C. scale D. nonparametric

C

. A scatter plot of number of teachers and number of people with college degrees for cities in California reveals a positive association. The most likely explanation for this positive association is: a. Teachers encourage people to get college degrees, so an increase in the number of teachers is causing an increase in the number of people with college degrees. b. Larger cities tend to have both more teachers and more people with college degrees, so the association is explained by a third variable, the size of the city. c. Teaching is a common profession for people with college degrees, so an increase in the number of people with college degrees causes an increase in the number of teachers. d. Cities with higher incomes tend to have more teachers and more people going to college, so income is a confounding variable, making causation between number of teachers and number of people with college degrees difficult to prove.

B

In analysis of variance, the F-ratio is a ratio of __________. a. two (or more) sample means b. two variances c. sample means divided by sample variances

B

The ANOVA test will tolerate some violation of the model assumptions as long as a. sample size is quite small b. sample sizes are roughly equal c. at least one sample is greater than 50 d. there are more than four separate samples

B

The chi square test is frequently used because it is relatively easy to satisfy the model assumptions (step 1 of the five-step model). These assumptions require, in the case of chi square, a. a normal population distribution b. no assumption about the shape of the sampling distribution c. expected frequencies of equal value d. a difference in expected and observed frequencies

B

Which statement is true? Correlations (a) reveal significant differences (b) do not imply cause and effect (c) require nominal data only (d) cannot be used with ordinal data

B

Which statistical technique is appropriate when we describe a single population of qualitative data with two or more categories? a. The z-test of the difference between two proportions b. The chi-squared goodness-of-fit test c. The chi-squared test of a contingency table d. Both (a) and (b

B

If two variables are absolutely independent of each other the correlation between them must be: (a) -1 (b) 0 (c) +1 (d) +.1

B bc Ha is that Dv (Y) is dependent (varies according to) IV (X); aka there is a correlation/association between the two

An F statistic is a ratio of an estimate of the population variance based on variation among the _____ to an estimate of the population variance based on variation among the_____ A. scores in each sample, means of each sample B. means of each sample, scores in each sample C. scores in each pop, means of each pop D. means of each pop, scores in each pop

B. ANOVA tests 3 or more SAMPLE MEAN differences by comparing two estimates of POPULATION VARIANCE. Those two estimates being (B).

In an ANOVA, which of the following is most likely to produce a large value for he F-ratio? A. Small mean diff and small sample variances B. large mean diff and small sample variances C. Small mean diff and large sample variances D. large mean diff and largesample variances

B.Large mean differences and small sample variances

ANOVA may be thought of as an extension of the ____ a. confidence interval estimation procedure b. t test for the significance of the difference between two sample proportions c. t test for the significance of the difference between two sample means d. t test for the significance of the difference between two matched samples

C

ANOVA proceeds by developing two separate estimates of the a. population mean b. population standard deviation c. population variance d. sample variance

C

An analysis of variance comparing three treatment conditions produces dfwithin = 21. If the samples are all the same size, how many individuals are in each sample? a. 6 b. 7 c. 8 d. It is impossible for the samples to be the same size if dfwithin = 21.

C

Cell frequencies computed under the assumption that the null hypothesis is true are called a. observed frequencies b. experimental frequencies c. expected frequencies d. random frequencies

C

If there is no association between two variables, knowledge of the independent variable a. causes us to make more prediction errors b. improves the accuracy of our predictions c. does not change the number of errors of prediction d. makes prediction of the dependent variable impossible

C

In a study relating mean house mortgage interest rates per annum and the number of new applicants for mortgages over the last 10 years: (a) the mean house mortgage interest rate per annum is the dependent variable (b) in a scattergraph, the mean house mortgage interest rate per annum would be placed on the Y axis (c) the number of new applicants per annum is represented on the Y axis (d) in a scattergraph, the number of new applicants per annum is the independent variable represented on the Y axis

C

In the case of a perfect association, predictions from one variable to another can be made a. only if variables are measured at the nominal level b. when at least one variable is ordinal c. without error d. only if the relationship is positive

C

The Co-efficient of Determination (strength of the association) expresses the amount of the variation in the dependent variable that can be explained by: (a) the proportion of Y (b) the variation in the independent variable Y (c) the variation in the independent variable X (d) all of the above (e) none of the above

C

The chi square goodness of fit test assumes: (a) normal distribution against which the observed data will be compared (b) a non-normal distribution against which the observed data will be compared (c) a particular distribution against which the observed data will be compared (d) no known distribution

C

Under what circumstances is the experimentwise alpha level a concern? a. whenever you do an analysis of variance b. whenever an experiment compares exactly two treatments c. whenever an experiment involves more than one hypothesis test d. whenever the alpha level is greater than .05

C

What is the effect of an outlier on the value of a correlation coefficient? a. An outlier will always decrease a correlation coefficient. b. An outlier will always increase a correlation coefficient. c. An outlier might either decrease or increase a correlation coefficient, depending on where it is in relation to the other points. d. An outlier will have no effect on a correlation coefficient.

C

When 'r' is negative, one variable increases in value: (a) the other increases (b) the other increases at a greater rate (c) the other variable decreases in value (d) there is no change in the other variable (e) all of the above

C

i) If the presence of a disease is independent of exposure to some risk factor, the relative risk would be: a) 0 b) greater than 0, but less than 1 c) 1 d) greater than 1

C

In a goodness of fit test to determine whether there are significantly more petrol (gas) price increases on particular days of the week, what percentage of the total increases should be expected on each day of a seven day week? (a) 7% (b) 70% (c) 14.3% (d) 7/10ths

C 100%/7 = 14.3%

43. The chi-square distribution becomes more symmetrical as A) number of variables increase. B) the chi-square value increases. C) degrees of freedom decrease. D) degrees of freedom increase.

D

Suppose the correlation between height and weight for adults is +0.90. What is the percentage of variability in height is explained by variability in weight? a. 90% b. 45% c. 100 - 90 = 10% d. 81%

D

The ANOVA test is most appropriate for dependent variables that are a. discrete and ordinal b. discrete and continuous c. continuous and nominal d. continuous and interval-ratio

D

The following table shows the results of an analysis of variance comparing three treatment conditions with a sample of n = 7 participants in each treatment. Note that several values are missing in the table. What is the missing value for SStotal? Source.......SS df MS F Between....20 xx xx xx Within.......xx xx 2 Total..........xx xx a. 16 b. 23 c. 29 d. 56

D

Suppose there is a correlation of +0.87 between the length of time a person is in prison and the amount of aggression the person displays on a psychological inventory. This means that spending a longer amount of time in prison causes people to become more aggressive. a. T b. F

False no causation

what are the null and research hypotheses in a chi-square test for independence? what are the null and research hypotheses in a chi-square goodness of fit test? what are the null and research hypotheses in an ANOVA? what are the null and research hypotheses in a correlation test?

Ho: the nominal variables are independent/ not related to one another (if this is true then observe will be like expected) Ha: the nominal variables are dependent/ related of one another Ho: observations seen in sample are like those expected in population; (expected chi-square (mean) is df) (distribution is unifrom) Ha: observations seen in sample are different from those expected in population Ho: mu1=mu2=mu3 Ha: at least one mean is diff from the others Ho: p=0 Ha: p =/= 0

A study looking at exceeding speed limit and age Age.............Always Not Always Total Under 30.... 100........ 100..........200 Over 30........ 40.........160......... 200 Total.............140....... 260........ 400 Calculate the relative risk that people under 30 always exceed the speed limit

You are asking how much more likely is it that people who always exceed the speed limit (DV) are under the age of 30 (age being IV), as opposed to people under the ago of 30: (always;under 30)/ (always, over 30)= 0.5/ 0.2= 2.5


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