Term
| null hypothesis H0 regarding to related/matched samples: |
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Definition
the null hypothesis is an statment of the scores from the first and second test to be 0. In other words, no change, no difference between the mean of the two scores.
(d-d=0). so D=0 |
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Term
| the logic behind the null is |
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Definition
| not on the samples but actually interested in the populations (t1 & t2) and basically expecting that there is no difference between the two population. So we expect the mean difference of the population to be 0. |
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Term
| The Central Limit Theorem allows us to make the assumption that |
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Definition
| to compare our observed mean difference to an assumed mean difference of 0. Since we're assuming that the mean difference is zero We can assume that the mean of the sampling distribution of mean differences is also equal to zero. (D=0) |
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Term
| what does the Central Limit Theorem tells us?? |
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Definition
| The CLT tells us that standard error of the sampling distribution will equal the standard deviation of the population divided by the square root of our sample size. |
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Term
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Definition
| we compare our observed mean difference (3.53) to the assumed mean difference of 0, and express the magnitude of any difference between values |
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Term
| What is the definition of the estimate of the standard error in the case of a t test for related sample means? |
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Definition
| it is an estimate of the standard deviation of the sampling distribution of mean differences |
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Term
| ho do we test whether the independent variable has an effect on the dependent variable? |
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Definition
| we would test the significance of the difference between the sample means with an independent-groups, two-tailed t-test |
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Term
| what does the phrase independent sample mean? |
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Definition
| indenpendent samples are samples selected in such a way that the selection of cases or subjects included in one sample has no connection to or influence on the selection of cases or subjects in the other sample |
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Term
what is the logic for independent samples?
(in the t test for differnce of means for independent samples, which difference is the object of interest? |
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Definition
| difference such as the test allowing us to compare the means of two samples with an eye toward whether or not any difference is a reflection of a true difference between the populations |
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Term
| sampling distribution of the differences of means |
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Definition
| plotting the mean differences between two independent groups |
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Term
| the question that constitutes the logic and the Null is |
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Definition
| what constitutes an extreme difference and the magnitude of any observed difference, expressed in standard error units |
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Term
| INdependent samples deals with |
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Definition
| two different samples, and two different sample sizes |
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Term
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Definition
| any measure of the variation that's present in a sample size is, in part, a function of sample size. |
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Term
| the larger the sample size for independent samples |
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Definition
| will give a greater variation = good representation of variation |
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Term
| for independent sample size |
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Definition
| the formula for the estimate of the standard error of the difference of means will be sensitive to the number of cases in each sample. |
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Term
| for independent sample, the formula will |
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Definition
| first look at the sample variances as we set out to calculate the estimate of the standard error, this is because we need to take into account the different sample sizes |
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Term
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Definition
| the square root of the varience |
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Term
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Definition
| the standard deviation squared s^2 |
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Term
| the goal for independent samples is to |
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Definition
| observed difference between the two means to an assumed difference of of 0. then to convert the magnitude of any observed difference into a standard error units. |
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