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Terms in this set (31)
What is the fundamental difference between t-statistics and z-scores ?
The t statistics uses the sample variance in place of the population variance
Why do we use t-tests?
To test the hypothesis about an unknown population mean.
If two samples are selected from the same population, under what circumstances will the two samples have exactly the same t statistic?
If the sample are the same size and have the same mean and the same variance.
What are the degrees of freedom?
DOF- describe the number or scores in a sample that are independent and free to vary.
What happens as they increase or decrease?
As the value of the df increases, the better the sample variance represents the population variance, and the better the t statistic approximates the z score.
One Sample and paired
What is the effect of a large value on the t-statistic and on hypothesis testing for the estimated standard error?
The larger the variance, the larger the error
What happens to effect size when you change the sample size?
The larger the sample, the smaller the error. NOT TOO MUCH
Corrects the bias in the standard error to combine the sample variances into a single value. Obtained by AVERAGING or "pooling" the TWO SAMPLES variances using a procedure that allows the bigger sample to carry more weight in determining the final value.
Is it impossible to compute a t-statistic for a sample that has only one score.
You cannot compute a t-statisitc for a sample size of 1 b/c the t-statisitc uses the sample standard deviation, which requires you to divide the sum of squares by ( n-1), but if n=1, then you would be dividing by zero, which is not allowed
Uses a separate group of participants for each treatment condition ( or each population). These types of t-test are used to compare groups of participants that are not related in any way. The groups are independent from one another. So, participants in one group have no relationship to participants in the second group BETWEEN
Risk is that the results are biased because the individuals in one sample are systematically different than the individuals in the other sample. Does not cause cause-and-effect
Within- Subjects/Paired Sample-Repeated Measures
the dependent variable is measured two or more rimes for each individual in a singe sample. The same group of subjects is used in all of the treatment conditions. There is no risk that the participants in one treatment are substantially different from the participants in another.
Within- subjects info
These types of test are used to compare groups that are related in some way. There are so many was that participants in two groups can be related. One way is that participants in the second group. THis is sometimes called a repeated measure design .
Within subjects info
A second way is that participants in the second group. For example, a pair of twins could be divided up so one twin participated with the first group and the other twin participated with the second group. A third way is if participants in one group are matched with participants in second group by some attribute. For example, if a participation the first group rates hugh on depression, researches might try to find a participant in the second group that also rates high on depression
What factors are most likely to produce a significant value for an independent t-test
Large samples and small variance
For a paired sample t-test
A larger mean difference increases the likelihood of rejecting the null hypothesis and increases measures of effect size. Larger sample size leads to smaller error
What is a null hypothesis vers a Alternative
Alternative - there is an effect
Type 1 error
when the sample mean FaLLS within a critical region even though the IV did not have an effect ( false positive)
Type 2 error
WHen the sample mean does not fall within the critical region, even though the IV did have an effect (false negative)
What is the difference between a one tailed and two tailed test
Non directional-two tailed ; predicts there will be a difference
predicts there will be no difference
What is the purpose of a random assignment
To distribute the participants characteristic evenly between 2 groups so that neither groups is noticeably smaller, faster, etc than the other. It can be used to control environmental variables
Is it the same as random sampling
No. It required that each individual has an equal chance of being selected and that the probability of being selected stays constant from one selection to the next, if more than one individual is selected.
What is the purpose of counterbalancing
THE GOAL IS TO USE EVERY POSSIBLE ORDER OF TREATMENT CONDITION ..Eliminate the potential for confounding by disrupting any systematic effects from factors related to time or the order of treatments; Change the order in which treatments occurs
are biasing effects that can occur when each participant must participate in each experimental treatment condition
Are sequencing effects that arise from the order in which the treatment are administer. EX; as people complete their participation in their first treatment condition they will become more familiar with the setting and testing process.
Carry over effects
are sequencing effects that occur when the effect of one treatment condition carries over to a second treatment condition. This is participants performance in a later treatment that occurred prior to it.
What is attrition?
Over total number at the beginning
A measure reflecting the average number of citation to recent articles published in the journal
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