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Statistics for Psychology Final Exam
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Gravity
10, 11, and all the remaining chapters. Entered as we go through the class and as I read the chapters.
Terms in this set (22)
when does an observed sample qualify as a common outcome?
if the difference between its value and that of the hypothesized population mean is small enought o be viewed as a probable outcome under the null hypothesis; it does not exceed your predefined significance level (alpha)
when does an observed sample qualify as a rare outcome?
if the difference between its value and that of the hypothesized value is too large to be reasonably viewed as a probable outcome under the null hypothesis; it meets or exceeds your predefined criteria for significance (alpha)
sampling distribution of z
the distribution of z values that would be obtained if a value of z were calculated for each sample mean for all possible random samples
formula for standard score
(raw score-mean)/standard deviation
standard score
indicates the deviation of the raw score (sample mean), in standard deviation units, above or below the hypothesized population mean
z test for a population mean
a hypothesis test that evaluates how far the observed sample mean deviates, in standard error units, from the hypothesized population mean; is accrate only when the population is normally distributed or the sample size is large enough to satisfy the requirements of the central limit theorem and the population standard deviation is known
how to calculate a z test for population mean
define research problem, write statistical hypotheses (Ho and H1), create your decision rule, (.05 or .01 significance and corresponding z score), do the calculations, make decision to retain or reject, write out the interpretation
null hypothesis
a statistical hypothesis that ususally asserts that nothing special is happening with respect to some characterisitc of the underlying population
alternative hypothesis
the opposite of the null hypothesis
research hypothesis
usually identified with the alternative hypothesis, this is the informal hypothesis or hunch that inspires the entire investigation
decision rule
specifies precisely when Ho should be rejected (because the observed z qualifies as a rare outcome)
critical z score
a z score that seperates common from rare outcomes and hence dictates whether Ho should be retained or rejected
level of significance
the degree of rarity required of an observed outcome in order to reject the null hypothesis
4 decision outcomes
true negative, false negative, false positive, true positive
true negative
there really is no effect, retain Ho; p = 1-alpha
false positive
there really is no effect, reject Ho; type I error; p = alpha
false negative
there really is some effect, retain Ho, type II error, p = some b looking thing
true positive
there really is some effect, reject Ho, p (power) = 1-b looking thingy
why the research hypothesis isn't tested directly
lacks precision, supported by a strong decision to reject null hypothesis; because the research hypothesis is identifies with the alternative hypothesis, the decision to reject the null hypothesis will provide strong support for the research hypothesis, while the decision to retain the null hypothesis will provide, at most, weak support for the null hypothesis
two tailed or nondirectional test
rejection regions are located in both tails of the sampling distribution
one tailed or directional test
rejection region is located in just one tail of the sampling distribution
difference of level of significance between one and two tailed tests
with a two tailed test, if your significance level = .05, your rejection region will = .025 (half the total) ; with a one tailed test, the significance level will NOT be divided, so the rejection region would = .05
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