Week 8 Chapter 10 Flashcards
Step 1 (Procedure for using the F-max Test)
computation of the sample variance for each of the separate samples
Step 2 (Procedure for using the F-max Test)
computation using the largest and smallest of the sample variances
Step 3 (Procedure for using the F-max Test)
comparison between F-max value and critical value
independent-measures research design aka between-subjects design
strategy using a separate group of participants for each treatment condition or for each population
repeated-measures research design aka within-subjects design
strategy in which two sets of data are obtained from the same group of participants
independent-measures t statistic
formula used when separate groups of participants are used for each treatment condition
pooled variance
all of these:
- method correcting bias in standard error by combining two sample variances into a single value
- is actually an average of the two sample variances, but the average is computed so that the larger sample carries more weight in determining the final value.
homogeneity of variance
assumption stating that the two populations being compared must have the same variance
Hartley’s F-max test
formula used to check whether two populations being compared have the same variance
Which of the following is most likely to be an independent-measures design?
A study comparing self-esteem for children from single-parent homes and children from two-parent homes
Which of the following is most likely to be a repeated-measures design?
A study comparing cholesterol levels before and after a diet featuring oatmeal
An independent-measures study comparing two treatment conditions uses ___ groups of participants and obtains ___ score(s) for each participant.
2; 1
The goal of an independent-measures research study is to
evaluate the mean difference between two populations (or between two treatment conditions).
the null hypothesis for the independent-measures test is
H0: μ1 - μ2 = 0 (No difference between the population means)
The null hypothesis could also be stated as μ1 = μ2, but the first version of H0 produces a specific numerical value (zero) that is used in the calculation of the t statistic. Therefore, we prefer to phrase the null hypothesis in terms of the difference between the two population means.
The alternative hypothesis states that there is a mean difference between the two populations
H1: μ1 - μ2 ≠ 0 (No difference between the population means)
The alternative hypothesis could also be stated as μ1 ≠ μ2
there are two ways to interpret the estimated standard error of
- It measures the standard distance between (M1 - M2) and (μ1 - μ2).
- When the null hypothesis is true, it measures the standard, or average size of (M1 - M2). That is, it measures how much difference is reasonable to expect between the two sample means.
When the two samples are exactly the same size, how does the pooled variance relate to the two sample variances?
The pooled variance is exactly half-way between the
two sample variances.
When the two samples have different sizes, how does the pooled variance relate to the two sample variances?
The pooled variance is between the two sample variances but closer to the variance for the larger sample.
Which of the following is the correct null hypothesis for an independent-measures t test?
There is no difference between the two population means.
Which of the following does not accurately describe the relationship between the formulas for the single-sample t and the independent-measures t?
All of the above accurately describe the relationship.
Hartley’s F-max test is used to evaluate the homogeneity of variance assumption. What is the null hypothesis for this test?
The two population variances are equal.
Which of the following is not an accurate description of a confidence interval for a mean difference using the independent-measures t statistic?
If other factors are held constant, the width of the interval will increase if the difference between the two sample means is increased.
Which of the following accurately describes the 95% confidence interval for an independent-measures study for which a hypothesis test concludes that there is no significant mean difference with a = .05
The confidence interval will include the value 0.
Which of the following accurately describes how the outcome of a hypothesis test and measures of effect size with the independent-measures t statistic are affected when sample size is increased?
The likelihood of rejecting the null hypothesis increases and there is little or no effect on measures of effect size.
Which of the following accurately describes how the outcome of a hypothesis test and measures of effect size with the independent-measures t statistic are affected when sample variance increases?
The likelihood of rejecting the null hypothesis and measures of effect size both decrease.
Which of the following sets of data would produce the largest value for an independent-measures t statistic?
Two sample means of 10 and 20 with variances of 20 and 25
