50 terms

# Stats T/F Answers HW 11-15

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When the population variance (or standard deviation) is unknown, it is impossible to use a z score for a hypothesis test.
True
The larger the value of df, the more a t distribution resembles a normal distribution.
True
The t distribution is symmetrical and has a mean of zero.
True
As sample size increases, the distribution of t statistics becomes flatter and more spread out.
False
For any given value of (ALPHA), as df increases, the critical values in the t distribution table get smaller (move closer to zero).
True
For a hypothesis test with a t statistic, the estimated standard error provides an approximation of the typical distance between a sample mean and the population mean.
True
As sample size increases, the estimated standard error also increases.
False
In general, the larger the value of the estimated standard error, the greater the likelihood of rejecting the null hypothesis.
False
The boundaries for the critical regions in a two-tailed test using a t statistic with (ALPHA)=.05 will never get any closer to zero than +/-1.96.
True
In general, a large value for a t statistic (one that is far from zero) is an indication that the sample data are not consistent with the null hypothesis.
True
When doing an independent-samples t-test, it is usually necessary to compute the pooled variance before calculating the estimated standard error.
True
For a hypothesis test with an independent-samples t, the larger the two sample variances are, the greater the likelihood that you will reject the null hypothesis.
False
For an independent-samples t statistic, the standard error indicates the size of the difference that will typically be found between the two sample means if the null hypothesis is true.
True
The results from an independent-samples t-test are reported as "t(14)=2.13, p > .05, two-tailed." For this test, the null hypothesis was rejected.
False
For a research study comparing two treatment conditions, a related-samples design requires two scores for each participant, whereas an independent-samples design requires only one score for each participant.
True
If df = n1 + n2 - 2 for the t statistic, then it is likely that the researcher was doing a related-samples study.
False
A related-samples study and an independent-samples study both produce t statistics with df = 20. It can be concluded from this that the independent-samples study used more participants.
True
The related-samples t statistic should be used in an experimental design that employs two different samples only if a matching variable has been used to pair, on a one-to-one basis, each participant in one sample with a participant in the other sample.
True
If two treatments are both expected to produce a permanent or long-lasting change in the participants, then a repeated-measures design would not be appropriate for comparing the two treatments.
True
Repeated-measures designs are particularly well suited to research studies examining learning or other changes that occur over time.
True
F-ratios are always greater than or equal to zero.
True
F = 0.00 can be obtained only if all of the separate treatment means in the experiment are exactly the same.
True
F = 1.00 implies that all of the separate treatment means in the experiment are exactly the same.
False
If the null hypothesis is true, the F-ratio is expected to have a value near 1.00.
True
The sampling distribution of F-ratios is negatively skewed.
False
If the F-ratio obtained from an ANOVA is great than the value listed in the table, the appropriate decision is to reject the null hypothesis.
True
When the null hypothesis is true, the F-ratio is balanced so that the numerator and the denominator are both measuring the same source of variance.
True
A research report presents the results of a one-factor ANOVA as follows: F(3,28) = 5.36, p < .01. The study must have compared three treatments.
False
A research report presents the results of a one-factor ANOVA as follows: F(3,28) = 5.36, p < .01. The study must have used a total of 31 participants.
False
If an ANOVA produces SSb = 20 and MSb = 10, then the study must be comparing two treatment conditions.
False
All else being equal, the larger the difference between sample means, the larger the ANOVA F-ratio will be.
True
In an ANOVA, SSb is a measure of how much the treatment means differ from one another.
True
In an ANOVA, MSt will always equal the sum of MSb and MSw.
False
When there are more than 2 treatment conditions in a study, some of the treatment means may not be significantly different from each other even if the null hypothesis is rejected by an ANOVA.
True
If Ho is rejected by an ANOVA, follow-up statistical tests are not needed if the study has just 2 treatment conditions.
True
Follow-up statistical tests are not needed if the decision is based on an ANOVA is to fail to reject the null hypothesis.
True
An ANOVA is used to determine whether any significant differences exist at all among a set of treatment means, whereas follow-up statistical tests are used to determine exactly which means are significantly different from one another.
True
With 3 treatment conditions, the alternative hypothesis for an ANOVA states that at least two of the three treatment means are different from each other.
True
The F-ratio for an ANOVA comparing 3 treatment means with n=10 in each condition would have df = 2, 29
False
If an ANOVA produces SSb = 20 and SSw = 40, then eta sq. = 0.50.
False
In the F-ratio for a repeated-measures ANOVA, the variability that arises from individual differences among participants is always missing by design from the numerator, but must be computer and subtracted from the denominator.
True
In a repeated-measures ANOVA, the variability that is due to differences among the treatment means will contribute to both the numerator and the denominator of the F-ratio.
False
A repeated-measures study used a sample of n=8 participants to evaluate the mean differences between 2 treatment conditions. The ANOVA for this study will have dfe=7
True
For a repeated-measures ANOVA, MSe = MSw - MSb-Ss
False
Based on the results of a repeated-measures ANOVA, a researcher reports F(4, 20) = 11.57, p < .01. For this ANOVA, the null hypothesis was rejected.
True
Based on the results of a repeated-measures ANOVA, a researcher reports F(4, 20) = 11.57, p < .01. For this ANOVA, there were 4 treatment conditions.
False
Tukey's HSD test may be used for post hoc tests with the repeated-measures ANOVA provided MSe is used instead of MSw.
True
The repeated-measures ANOVA begins the same way as the independent-measures ANOVA, with the total variability partitioned into between-treatment and within-treatment components.
True
If there are large individual differences for a particular dependent variable, a repeated-measures study is more likely to detect a treatment effect than an independent-measures study.
True
The effect sized statistic that is appropriate for a repeated-measures analysis is computed in such a way as to take account of the fact that variance due to person cannot possibly affect the value of MSb.
True