SUBJECTS
|
BROWSE
|
CAREER CENTER
|
POPULAR
|
JOIN
|
LOGIN
Business Skills
|
Soft Skills
|
Basic Literacy
|
Certifications
About
|
Help
|
Privacy
|
Terms
|
Email
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. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
A data point
Bias
Simple random sample
Qualitative variable
2. Is a function that gives the probability of all elements in a given space: see List of probability distributions
Step 1 of a statistical experiment
Confounded variables
A probability distribution
Type 1 Error
3. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
A sample
Pairwise independence
An event
An estimate of a parameter
4. A list of individuals from which the sample is actually selected.
The median value
A random variable
Step 1 of a statistical experiment
Sampling frame
5. A variable describes an individual by placing the individual into a category or a group.
Qualitative variable
quantitative variables
Average and arithmetic mean
Correlation
6. Many statistical methods seek to minimize the mean-squared error - and these are called
A Statistical parameter
methods of least squares
A sample
A Probability measure
7.
The variance of a random variable
Independent Selection
the population mean
Descriptive
8. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i
Power of a test
Independence or Statistical independence
Law of Parsimony
Qualitative variable
9. Where the null hypothesis is falsely rejected giving a 'false positive'.
Divide the sum by the number of values.
Independence or Statistical independence
The Mean of a random variable
Type I errors
10. ?r
Sampling Distribution
the population cumulants
Placebo effect
Average and arithmetic mean
11. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
The Expected value
Statistics
Inferential statistics
12. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called
The sample space
inferential statistics
Lurking variable
Independence or Statistical independence
13. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
A statistic
Cumulative distribution functions
Statistics
the sample or population mean
14. Interpretation of statistical information in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured can often involve the development of a
Statistics
Bias
Parameter
Null hypothesis
15. E[X] :
That value is the median value
covariance of X and Y
quantitative variables
expected value of X
16. Have no meaningful rank order among values.
Marginal probability
Correlation coefficient
A likelihood function
Nominal measurements
17. Have imprecise differences between consecutive values - but have a meaningful order to those values
Ordinal measurements
An Elementary event
Marginal probability
Greek letters
18. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.
An Elementary event
The Mean of a random variable
the population correlation
Type II errors
19. Describes the spread in the values of the sample statistic when many samples are taken.
methods of least squares
Kurtosis
nominal - ordinal - interval - and ratio
Variability
20. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl
Type 1 Error
Type II errors
Mutual independence
The sample space
21. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Variable
Particular realizations of a random variable
the population cumulants
The Covariance between two random variables X and Y - with expected values E(X) =
22. Gives the probability of events in a probability space.
A Probability measure
Simple random sample
Conditional probability
A likelihood function
23. 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
The median value
Placebo effect
24. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
nominal - ordinal - interval - and ratio
Descriptive
Marginal distribution
Valid measure
25. Data are gathered and correlations between predictors and response are investigated.
the population correlation
A population or statistical population
Kurtosis
observational study
26. A group of individuals sharing some common features that might affect the treatment.
The Mean of a random variable
Block
A sampling distribution
Correlation
27. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).
Type I errors
An event
Binary data
An estimate of a parameter
28. Cov[X - Y] :
covariance of X and Y
The standard deviation
Type I errors & Type II errors
A Probability measure
29. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Lurking variable
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
categorical variables
30. Are two related but separate academic disciplines. Statistical analysis often uses probability distributions - and the two topics are often studied together. However - probability theory contains much that is of mostly of mathematical interest and no
Probability and statistics
Quantitative variable
The Expected value
Correlation coefficient
31. Some commonly used symbols for population parameters
The sample space
Interval measurements
the population mean
Parameter
32. Is the length of the smallest interval which contains all the data.
Variable
The Range
hypotheses
Qualitative variable
33. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit
Block
Estimator
Interval measurements
Probability density
34. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
the sample or population mean
Posterior probability
Statistical adjustment
Count data
35. Are simply two different terms for the same thing. Add the given values
Beta value
Block
Average and arithmetic mean
Joint probability
36. Can be a population parameter - a distribution parameter - an unobserved parameter (with different shades of meaning). In statistics - this is often a quantity to be estimated.
Warning
: Invalid argument supplied for foreach() in
/var/www/html/basicversity.com/show_quiz.php
on line
183
37. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
Power of a test
Type I errors & Type II errors
A Random vector
A sample
38. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.
Law of Large Numbers
Credence
Bias
An experimental study
39. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.
Joint distribution
Step 1 of a statistical experiment
Kurtosis
the population mean
40. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Standard error
Descriptive
Placebo effect
Treatment
41. The standard deviation of a sampling distribution.
A sample
The median value
Standard error
Interval measurements
42. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
the sample or population mean
observational study
f(z) - and its cdf by F(z).
covariance of X and Y
43. Is its expected value. The mean (or sample mean of a data set is just the average value.
Marginal distribution
The Mean of a random variable
Mutual independence
Statistics
44. Is that part of a population which is actually observed.
Statistical adjustment
Placebo effect
Joint probability
A sample
45. Long-term upward or downward movement over time.
Trend
inferential statistics
The standard deviation
Statistical dispersion
46. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
categorical variables
Type II errors
Prior probability
Random variables
47. When there is an even number of values...
the population variance
That is the median value
A likelihood function
Step 3 of a statistical experiment
48. Rejecting a true null hypothesis.
Type 1 Error
That is the median value
Particular realizations of a random variable
Binary data
49. Some commonly used symbols for sample statistics
Quantitative variable
Type II errors
Dependent Selection
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
50. Also called correlation coefficient - is a numeric measure of the strength of linear relationship between two random variables (one can use it to quantify - for example - how shoe size and height are correlated in the population). An example is the P
The median value
Correlation coefficient
Correlation
Binary data
Sorry!:) No result found.
Can you answer 50 questions in 15 minutes?
Let me suggest you:
Browse all subjects
Browse all tests
Most popular tests
Major Subjects
Tests & Exams
AP
CLEP
DSST
GRE
SAT
GMAT
Certifications
CISSP go to https://www.isc2.org/
PMP
ITIL
RHCE
MCTS
More...
IT Skills
Android Programming
Data Modeling
Objective C Programming
Basic Python Programming
Adobe Illustrator
More...
Business Skills
Advertising Techniques
Business Accounting Basics
Business Strategy
Human Resource Management
Marketing Basics
More...
Soft Skills
Body Language
People Skills
Public Speaking
Persuasion
Job Hunting And Resumes
More...
Vocabulary
GRE Vocab
SAT Vocab
TOEFL Essential Vocab
Basic English Words For All
Global Words You Should Know
Business English
More...
Languages
AP German Vocab
AP Latin Vocab
SAT Subject Test: French
Italian Survival
Norwegian Survival
More...
Engineering
Audio Engineering
Computer Science Engineering
Aerospace Engineering
Chemical Engineering
Structural Engineering
More...
Health Sciences
Basic Nursing Skills
Health Science Language Fundamentals
Veterinary Technology Medical Language
Cardiology
Clinical Surgery
More...
English
Grammar Fundamentals
Literary And Rhetorical Vocab
Elements Of Style Vocab
Introduction To English Major
Complete Advanced Sentences
Literature
Homonyms
More...
Math
Algebra Formulas
Basic Arithmetic: Measurements
Metric Conversions
Geometric Properties
Important Math Facts
Number Sense Vocab
Business Math
More...
Other Major Subjects
Science
Economics
History
Law
Performing-arts
Cooking
Logic & Reasoning
Trivia
Browse all subjects
Browse all tests
Most popular tests