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SOCI 3010 Exam 2 Vocabulary
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Gravity
Key Concepts:
Terms in this set (36)
alpha
the probability of error or the probability that a confidence interval does not contain the population value
0.10, 0.05, 0.01, 0.001, or 0.0001
alpha levels are usually set at
bias
a criterion used to select sample statistics as estimators
equal
a statistic is unbiased if the mean of its sampling distribution is ____________ to the population value of interest
central limit theorem
specifies the mean, standard deviation, and shape of the sampling distribution, given that the sample is large
confidence interval
an estimate of a population value in which a range of values is specified
confidence level
a frequently used alternate way of expressing alpha, the probability that an interval estimate will not contain the population value
90%, 95%, 99%, 99.9%, and 99.99%
alpha levels of 0.10, 0.05, 0.01, 0.001, and 0.0001 correspond to confidence levels of
efficiency
the extent to which the sample outcomes are clustered around the mean of the sampling distribution
EPSEM (equal probability of selection method)
every element or case in the population must have an equal probability of selection for the sample
nonprobability sample
does not meet the EPSEM criterion
parameter
a characteristic of a population
representative sample
reproduces the major characteristics of the population from which it was drawn
sampling distribution
the distribution of a statistic for all possible sample outcomes of a certain size
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
the sampling distribution will be
simple random sample
a method for choosing cases from a population by which every case and every combination of cases has an equal chance of being included
standard error of the mean
the standard deviation of a sampling distribution of sample means
critical region (region of rejection)
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
five-step model
A step-by-step guideline for conducting tests of hypotheses; organizes decisions and computations for all tests of significance
hypothesis testing (significance testing)
statistical tests that estimate the probability of sample outcomes if assumptions about the population (the null hypothesis) are true
null hypothesis (H0)
a statement of "no difference"
the population from which the sample was drawn has a certain characteristic or value
in the context of single-sample tests of significance, the null hypothesis states that
one-tailed test
used when the direction of the difference can be predicted or the concern focuses on outcomes in only one direction
research hypothesis (H1)
a statement that contradicts the null hypothesis
the population from which the sample was drawn does not have a certain characteristic or value
in the context of single-sample tests of significance, the research hypothesis says that
student's t-distribution
used to find the critical region for tests of sample means when σ is unknown and the sample size is small
t(critical)
marks the beginning of the critical region of a t distribution
t(obtained)
the test statistic computed in step 4 of the five-step model; sample outcome expressed as a t score
test statistic
the value computed in step 4 of the five-step model that converts the sample outcome into either a t score or a Z score
two-tailed test
used when the direction of the difference cannot be predicted or concern focuses on outcomes in both directions
type I error (alpha error)
the probability of rejecting a null hypothesis that is, in fact, true
type II error (beta error)
the probability of failing to reject a null hypothesis that is, in fact, false
Z(critical)
marks the beginnings of the critical region on a Z distribution
Z(obtained)
the test statistic computed in step 4 of the five step model; sample outcomes expressed as a Z score
independent 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
pooled estimate
an estimate of the standard deviation of the sampling distribution of the difference in sample means based on the standard deviations of both samples
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