SUBJECTS
|
BROWSE
|
CAREER CENTER
|
POPULAR
|
JOIN
|
LOGIN
Business Skills
|
Soft Skills
|
Basic Literacy
|
Certifications
About
|
Help
|
Privacy
|
Terms
Search
Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
Start Test
Study First
Subjects
:
clep
,
math
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
A probability distribution
A Statistical parameter
Placebo effect
the sample or population mean
2. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.
Average and arithmetic mean
Random variables
A probability space
Independent Selection
3. Is a sample space over which a probability measure has been defined.
A sampling distribution
Step 3 of a statistical experiment
A probability space
Probability and statistics
4. Probability of accepting a false null hypothesis.
Estimator
covariance of X and Y
Beta value
Random variables
5. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present
covariance of X and Y
A random variable
Step 3 of a statistical experiment
The Expected value
6. Some commonly used symbols for population parameters
Block
Statistics
the population mean
Joint distribution
7. Failing to reject a false null hypothesis.
Type 2 Error
Variability
The sample space
A probability density function
8. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.
Probability
Random variables
Sampling
Count data
9. A numerical facsimilie or representation of a real-world phenomenon.
Statistical dispersion
Simulation
Random variables
A random variable
10. A data value that falls outside the overall pattern of the graph.
Outlier
Correlation coefficient
Binary data
The average - or arithmetic mean
11. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.
A data set
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Lurking variable
Average and arithmetic mean
12. Of a group of numbers is the center point of all those number values.
Variability
The average - or arithmetic mean
observational study
Posterior probability
13. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Independent Selection
the population variance
Individual
Marginal probability
14. When there is an even number of values...
That is the median value
Sampling
Standard error
Conditional probability
15. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Pairwise independence
Bias
Likert scale
A probability space
16. Cov[X - Y] :
Random variables
covariance of X and Y
That is the median value
Quantitative variable
17. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data
Sampling
Correlation
Ratio measurements
Joint probability
18. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Standard error
Greek letters
Bias
observational study
19. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Statistics
Step 3 of a statistical experiment
Bias
Estimator
20. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.
A Random vector
An experimental study
Type I errors & Type II errors
the population mean
21. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to
An estimate of a parameter
hypotheses
Correlation coefficient
A Statistical parameter
22. Var[X] :
categorical variables
variance of X
Probability and statistics
nominal - ordinal - interval - and ratio
23. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are
Descriptive statistics
A data point
Experimental and observational studies
Quantitative variable
24. Is the probability distribution - under repeated sampling of the population - of a given statistic.
The average - or arithmetic mean
The variance of a random variable
Experimental and observational studies
A sampling distribution
25. ?
Joint distribution
Dependent Selection
Simple random sample
the population correlation
26. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Treatment
Pairwise independence
Simulation
variance of X
27. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co
expected value of X
f(z) - and its cdf by F(z).
Step 1 of a statistical experiment
applied statistics
28. Is that part of a population which is actually observed.
quantitative variables
Sampling Distribution
A sample
A statistic
29. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Cumulative distribution functions
Inferential
Placebo effect
Reliable measure
30. Are usually written in upper case roman letters: X - Y - etc.
Binary data
Probability
Parameter - or 'statistical parameter'
Random variables
31. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.
Ordinal measurements
A data point
The Mean of a random variable
Conditional distribution
32. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then
A likelihood function
Descriptive
Particular realizations of a random variable
Power of a test
33. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re
The Covariance between two random variables X and Y - with expected values E(X) =
The Expected value
hypotheses
Posterior probability
34. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
An estimate of a parameter
Coefficient of determination
the population cumulants
Null hypothesis
35. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'
Conditional probability
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Divide the sum by the number of values.
Probability
36. Many statistical methods seek to minimize the mean-squared error - and these are called
Qualitative variable
methods of least squares
Probability
Bias
37. Working from a null hypothesis two basic forms of error are recognized:
Type I errors & Type II errors
Bias
Type II errors
Placebo effect
38. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.
Residuals
Seasonal effect
That is the median value
A population or statistical population
39. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a
Probability density
the population cumulants
Step 2 of a statistical experiment
descriptive statistics
40. Is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case - the researchers would collect o
the population mean
Observational study
An experimental study
Independence or Statistical independence
41. A measurement such that the random error is small
Reliable measure
Statistical inference
A statistic
An estimate of a parameter
42. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
f(z) - and its cdf by F(z).
Probability
Interval measurements
A statistic
43. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.
Statistical inference
That value is the median value
A random variable
Independent Selection
44. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Credence
Statistical inference
Binomial experiment
methods of least squares
45. A numerical measure that describes an aspect of a population.
Parameter
A likelihood function
Inferential
Individual
46. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)
experimental studies and observational studies.
Interval measurements
The variance of a random variable
Statistical dispersion
47. Have imprecise differences between consecutive values - but have a meaningful order to those values
s-algebras
Random variables
Particular realizations of a random variable
Ordinal measurements
48.
Statistical adjustment
the population mean
Variability
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
49. Uses patterns in the sample data to draw inferences about the population represented - accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing) - estimating numerical characteris
Probability density
A population or statistical population
Variable
Inferential statistics
50. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that
experimental studies and observational studies.
Ratio measurements
hypothesis
The Covariance between two random variables X and Y - with expected values E(X) =