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A theorem that specifies the mean, standard deviation, and shape of the sampling distribution, given that the sample is large.
n>100 


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A method of sampling by which geographical units are randomly selected and all cases within each selected unit are tested. 


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The Equal Probability of SElection Method for selecting samples. Every element of case in the population must have an equal probability of selection for the sample. 


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The mean of a sampling distribution of sample means. 


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The mean of a sampling distribution of sample proportions. 


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Any population proportion 


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The quality a sample is said to have if it reproduces the major characteristics of the population from which it was drawn. 


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The distribution of a statistic for all possible sample outcomes of a vertain size.
Under conditions specified in two theorems, the sampling distribution will be normal in shape, with a mean equal to the population value and a standard deviation equal to the population standard deviation divided by the square root of N. 


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A method for choosing cases from a population by which every case and every combination of cases has an equal chance of being included. 


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Standard error of the mean 

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The standard deviation of a sampling distribution of sample means. 


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A method of sampling by which cases are selected from sublists of the population. 


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A method of sampling by which the first case from a list of the population is randomly selected. Thereafter, every kth case is selected. 


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The probability of error, or the probability that a confidence interval does not contain the population value. Alpha levels are usually set at 0.10, 0.05 


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A criterion used to select sample statistics as estimators. A statistic is unbiased if the mean of its sampling distribution is equal to the population value of interest. 


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An estimate of a population value in which a range of values is specified. 


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A frequently used alternate way of expressing alpha, the probability that an interval estimate will not contain the population value. Confidence Levels of 90%, 95% correspond to alphas of 0.10 and 0.05. 


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The extent to which the sample outcomes are clustered around the mean of the sampling distribution. 


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An estimate of a population value where a single value is specified. 


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The proportion of area under the sampling distribution that contains unlikely sample outcomes, given the null hypothesis is true, it is the probability of Type 1 error 


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Critical Region (region of rejection) 

Definition
The area under the sampling distribution that, in advance of the test itself, is defined as including unlikely sample outcomes, given that the null hypothesis is true. 


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1make assumptions
2null and research hypothesis
3draw picture
4state alpha, df, and t or z critical
5 compute equation
6findings 


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Statistical tests that estimate the probability of sample outcomes if assumptions about the population (null hypothesis) are true. 


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A statement of "no difference" in the context of single sample tests of significanece, the population from which the sample was drawn is assumed to have a certain characteristic or value. 


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A type of hypothesis test used when 1 the direction of the difference can be predicted or 2 concern focuses on outcomes in only one tail of the sampling distribution 


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Research Hypothesis (Hsub1) 

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A statement that contradicts the null hypothesis. In the context of single sample tests of significance, the research hypothesis says the population from which the sample was drawn does not have a certain characteristic or value 


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A distribution used to find the critical region for tests of sample means when σ is unknown and sample size is small. 


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The t score that marks the beginning of the critical region of a t distribution 


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The test statistic computed in step 5 of the sixstep model. The sample outcome into either a t score or a z score. 


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The value computed in step 5 of the 6 step model that converts the sample outcome into either a t or z score. 


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a type of hypothesis test used when 1 the direction of the difference cannot be predicted or 2 concerns focus on outcomes in both tails of the sampling distribution. 


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Type 1 and Type 2 Errors
Alpha and Beta 

Definition
Alpha Error the probability of rejecting a null hypothesis that is, in fact, false.
Beta Error The probability of failing to reject a null hypothesis that is, in fact, false. 


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Independent Random Samples 

Definition
Random samples gathered in such a way that the selection of a particular case for one sample has no effect on the probability that any other particular case will be selected for the other samples. 


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An estimate of the standard deviation of the sampling distribution of the difference in sample means based on the standard deviation of both samples. 


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symbol for the standard deviation of the sampling distribution of the differences in sample proportions. 


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symbol for the standard deviation of the sampling distribution of the differences in sample means 


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A test of significance appropriate for situations in which we are concerened with the differences among more than two sample means.



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The test statistic computed in step 5 of the ANOVA test 


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OneWay Analysis of Variance 

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Applications of ANOVA in which the effect of a single independent variable on a dependent variable is observed. 


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A technique for determining which pairs of means are significantly different 


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Sum of Squares Between (SSB) 

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The sum of the squared deviations of the sample means from the overall mean, weighted by sample size 


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Sum of Squares Within (SSW) 

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The sum of the squared deviations of scores from the category means 


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Total Sum of Squares (SST) 

Definition
The sum of the squared deviations of teh scores from the overall mean. 

