Stats exam 2

Difference scores

Difference between a person's score on one testing and the same person's score on another testing; often an after-score minus a before-score, in which case it is also called a change score

Distribution of differences between means

Distribution of differences between means of pairs of samples such that, for each pair of means , one is from one population and the other is from a second population; the comparison distribution in a t test for independent means

Distribution of means

Distribution of means of samples of a given size from a population (also called a sampling distribution of the mean); comparison distribution when testing hypotheses involving a single sample of more than one individual

Biased estimate

Estimate of a population parameter that is likely systematically to overestimate or underestimate the true value of the population parameter. For example, SD^2 would be a biased estimate of the population variance (it would systematically underestimate it)

Robustness

Extent to which a particular hypothesis-testing procedure is reasonably accurate even when its assumptions are violated

Type II error

Failing to reject the null hypothesis when in fact it is false; failing to get a statistically significant result when in fact the research hypothesis is true

T test from a single sample

Hypothesis-testing procedure in which a sample mean is being compared to a known population mean and the population variance is unknown.

T test for dependent means

Hypothesis-testing procedure in which there are two scores dfor each person and the population variance is not known; it determines the significance of a hypothesis that is being tested using difference or change scores from a single group of people

T test for independent means

Hypothesis-testing procedure in which there are two separate groups of people tested and in which the population variance is not known

Z test

Hypothesis-testing procedure in which there is a single sample and the population variance is known

T-test

Hypothesis=testing procedure in which the population variance is unknown; it compares t scores from a sample to a comparison distribution called a t distribution

T-distribution

Mathematically defined curve that is the comparison distribution used in a t test

T-score

On a t distribution, number of standard deviations from the mean (like a Zscpre, but on a t distribution)

Variance of a distribution of differences between means(S^2 difference)

One of the numbers figured as part of a t test for independent means; it equals the sum of the variances of the distributions of means associated with each of the two samples

Weighted average

Average in which the scores being averaged do not have equal influence on the Tate al, as in figuring th pooled variance estimate in a t test for independent means

95% confidence interval

Confidence interval in which, roughly speaking, there is a 95% chance that the population mean falls within this interval.

99% confidence interval

Confidence interval in which, roughly speaking, there is a 99% chance that the population mean falls within this interval

Alpha (o)

Probability of making a type I error, same as significance level

Beta (B)

Probability of making a type II error

Statistics power

Probability that the study will give a significant result if the research hypothesis is true

Type I error

Rejecting the null hypothesis when in fact it is true; getting a statistically significant result when in fact the research hypothesis is not true

Repeated measures design

Research strategy in which each person is tested more than once; same as within-subjects design

Confidence interval (CI)

Roughly speaking, the range of scores (that is the scores between an upper and lower value) that is likely to include the true population mean; more precisely, the range of possible population means from which it is not highly unlikely that you could have obtained your sample mean.

Standard error of the mean (SEM)

Same as standard deviation of a distribution of means, also called standard error (SE)

Standard error (SE)

Same as standard deviation of a distribution of means, also called standard error of the mean (SEM)

Power table

Table for a hypothesis-testing procedure showing the statistical power of a study fro various effect sizes and sample sizes

T-table

Table of cutoff scores on the t distribution for various degrees of freedom, significance levels, and one-and two-tailed tests

Mean of a distribution of means

The mean of a distribution of means of samples of a given size from a population; it comes out to be the same as the mean of the population of individuals

Confidence limit

Upper or lower value of a confidence interval

O^2m

Variance of a distribution of means

Variance of a distribution of means

Variance of the population divided by the number of scores in each sample

Assumption

A condition, such as a ppopulation's having a normal distribution, required for carrying out a particular hypothesis-testing procedure; a partn of the mathematical foundation for the accuracy of the tables used in determining cutoff values

Standard deviation of the distribution of differences between means ( S difference)

In a t test for independent means, square root of the variance of the distribution of differences between means

Poodles estimate of the population variance (S^2 pooled)

In a t test for independent means, weighted average of the estimates of the population variance from two samples (each estimate weighted by the proportion consisting of its sample's degrees of freedom divided by the total degrees of freedom for both samples)

Decision errors

Incorrect conclusions in hypothesis testing in relation to the real (but unknown) situation, such as deciding the null hypothesis is false when it is really true.

Standard deviation of a distribution of means

Square root of the variance of a distribution of means, also called standard. Error of the mean (SEM) and standard (SE)

Om

Standard deviation of a distribution of means

Effect size conventions

Standard rules about what to consider a small, medium, and large effect size, based on what is typical in psychology research; also known as Cohen's convention

Effect size

Standardized measure of difference (lack of overlap) between populations. Effect size increases with greater differences between means.

Meta-analysis

Statistical method for combining effect sizes from different studies