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multiple choice - exam 2

Terms in this set (33)

an investigator is performing an independent groups t-test. there are 11 subjects in group 1, and 9 subjects in group 2. the null and alternative hypotheses are stated in a non-directional manner, and she sets the significance level of the test at α=.05. then the critical values of t are equal to
+/- 2.101
conventionally, a large effect size (measured using cohen's d) is said to arise when the value of d first reaches
0.8
the standard error of the distribution of sample means provide a measure of
variability
a type 1 error occurs when
rejects the null hypothesis when it is true
a type 2 error occurs when
fails to reject the null hypothesis when it is false
what test do you run when the standard deviation is known
z-test
nondirectional
two tailed
directional
one tailed
if the population standard deviation is known, and the alternative hypothesis is directional is nature, then one should use a
one-tailed z-test
which of the following is the correct alternative hypothesis for a non directional independent measures t test?
μ1 - μ2 does not equal 0
when the null hypothesis is true, what is measured by the estimated standard error in the denominator of the independent measures t-test
the standard distance between two sample means selected from the same population
how does the shape of a t distribution compare to a normal distribution
the t distribution is flatter and more spread out, especially when sample size n is small
in general, as sample size n increases
- the power of the test increases
- the probability of a type 1 error increases
- the probability of a type 2 error decreases
in the standard hypothesis-testing procedure, the null hypothesis is generally
the hypothesis that is tentatively held to be true and that states that there was no effect of the treatment or experimental manipulation
the problem with increasing power by increasing the significance level of the test is that
it will also increase the probability of a type 1 error
the probability of a type 2 error is equal to
β
the probability of a type 1 error is equal to
α
all other things equal, as ample size increases, the width of the confidence interval for the mean decreases because
the standard error of the mean decreases
the sampling distribution of the mean is the
distribution of sample means for all possible random samples
all other things equal, which is generally true of the confidence interval for the mean
- the width of the 99% confidence interval for the mean is greater than the width of the 95% confidence interval for the mean
- the width if the confidence interval for the mean decreases as the sample size 'n' increases
one rejects the null hypothesis if
the experimental result is very unlikely , given that the null hypothesis is true
which of the following would not tend to increase the power of a statistical test
changing the significance level for α=.05 to α=.01
when the null and alternative hypothesis are stated in non-directional terms, then one uses a
t test
as sample size increases, σM will
decreases
assume the sample size is n, and let μM denote the mean of distribution of sample means formed from a population with me μ=? then it is the case that
μM = μ
consider the population of scores 2,4,6, and 8. the population has a standard deviation equal to 2.236. suppose now that one selects all possible samples (with replacement) of size 3 from the population and computes the mean of each sample. there are 64 such sample means. the standard deviation of that distribution of sample means (rounded to. two decimal places) is equal to
1.29
suppose that the 95% confidence interval for the mean is (70,80) and that the 99% confidence interval for the mean is (65,85. then one would
reject the null hypothesis μ=68 at the α= 0.05 significance level but not at the α=.01 significance level
which of the following is not an assumption for the z-score hypothesis test
the original population distributed from which the scores were sampled must be normal in form
the estimates effect size is not influenced by
size of sample
the estimated effect size is influenced by
- the difference between the sample mean and the hypothesis
- the standard deviation of the population
- the sample must be obtained by random sampling
regarding statistical decision making and power, which of the following is true
the critical region for the α=.05 significance level is larger in area than the critical region for the α=.01 significance level
according to the central limit theorem, which will be true regarding the distribution of sample means
- as ample size n approaches infinity, the distribution of sample means will be normally distributed even if the original population was not normally distributed
- if the original population was normally distributed then the distribution of sample means will be normally distributed, regardless of sample size n
the power of a statistical test is the probability that one
rejects the null hypothesis when it is false
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