Helps determine if your meta-analysis sampled from multiple populations

The central limit theorem states:

A sampling distribution is approximately normal for almost any population

The probability of any given event occurring

The four levels of measurement, from least detailed to most detailed:

Nominal, ordinal, interval, and ratio

When the CI includes the Null

The results are not significant

The probability of rejecting the null when the alternative is true

The repeatability or consistency of a measure

In essence heterogeneity tells you

That you accidentally sampled from more than one population

The distance of a data point from the mean, in standard deviation units

The Null Hypothesis is:

A statement indicating the absence of an expected effect

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Exam 4

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Questions 20

Answers

1
A moderator analysis
Helps determine if your meta-analysis meets statistical significance
None of these
Helps determine the overall effect size of your meta-analysis
Helps determine if your meta-analysis sampled from multiple populations
2
A p-value can be between:
0 - 1
None of these
0 - 100
-1 - 1
3
The central limit theorem states:
A sampling distribution is approximately normal for half of all populations
y=∑(𝒙−x̄)
A sampling distribution is approximately normal for almost any population
Measures of central tendency are more effective than measures of spread
4
Risk is:
The probability of a given bad event occurring
The probability of any given event occurring
None of these
The probability of a given good event occuring
5
The four levels of measurement, from least detailed to most detailed:
Ordinal, nominal, ratio, interval
This question sucks
Nominal, ordinal, interval, and ratio
Ratio, nominal, interval, ordinal
6
When the CI includes the Null
The results are significant
The results are not significant
The results of the effect are undetermined
The results show a small effect
7
Power is
The probability of rejecting the alternative when the null is true
The probability of rejecting the null when the alternative is true
A one-sided alternative to the null
A risk expressed in natural frequencies
8
Standard error:
Both Triangle and Circle
Is composed of error and individual differences
Is the standard deviation of a sampling distribution
None of these
9
Reliability is:
The extent that a measure actually measures what it's designed to measure
Relative to the square of the SD
The repeatability or consistency of a measure
Calculated by including the unbiased estimate
10
p = .01
These results show a small effect size
These results are not significant
These results show a large effect size
These results are significant
11
In essence heterogeneity tells you
That your meta-analysis has a very small diamond ratio
That you accidentally sampled from more than one population
That your meta-analysis has a very large effect size
That you accidentally sampled from more than one sample
12
Precision and Power both depend on:
The null hypothesis
The sample size
The statistical tests used
None of these
13
Type I error is a:
False negative
True positive
False positive
True negative
14
When results are statistically significant
Both Triangle and Circle
None of these
They represent a large effect
They are clinically significant
15
A sampling distribution of sample means
Is often close to normally distributed
Plots the means of multiple samples along a distribution
All of these
Functions according to the central limit theorem
16
Why is there a replicability crisis?
Lack of replication
Selective publication
All of these
The .05 imperative
17
Mean, Median, Mode
Measures of Spread
Measures of Location
Measures of Variance
18
Type II error is a:
False negative
True negative
False positive
True positive
19
Z-scores:
The distance of a data point from the mean, in standard deviation units
The odds of a zebra winning a horse race
The distance of a given X from a given Y, in standardized units of measure
A test statistic that allows the calculation of a p-value
20
The Null Hypothesis is:
A bad sci-fi movie
A statement indicating the absence of an expected effect
A statement indicating the confirmation of an expected effect
An approach to statistical inference

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