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. Is defined as the expected value of random variable (X -
Conditional distribution
Independence or Statistical independence
The Covariance between two random variables X and Y - with expected values E(X) =
Ordinal measurements
2. 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
Power of a test
Null hypothesis
observational study
A Distribution function
3. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
Binomial experiment
f(z) - and its cdf by F(z).
the sample or population mean
A likelihood function
4. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Parameter - or 'statistical parameter'
Sampling
Statistical dispersion
The standard deviation
5. Rejecting a true null hypothesis.
Parameter - or 'statistical parameter'
Power of a test
experimental studies and observational studies.
Type 1 Error
6. Are usually written in upper case roman letters: X - Y - etc.
Random variables
The average - or arithmetic mean
Conditional probability
P-value
7. Probability of accepting a false null hypothesis.
Beta value
The average - or arithmetic mean
Type I errors
A sample
8. 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
The variance of a random variable
Probability and statistics
That value is the median value
Interval measurements
9. Is that part of a population which is actually observed.
A sample
Probability density functions
variance of X
That is the median value
10. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
Warning
: Invalid argument supplied for foreach() in
/var/www/html/basicversity.com/show_quiz.php
on line
183
11. (cdfs) are denoted by upper case letters - e.g. F(x).
That is the median value
hypotheses
Inferential statistics
Cumulative distribution functions
12. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
A population or statistical population
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Probability density functions
Bias
13. 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
14. Is a sample and the associated data points.
covariance of X and Y
Prior probability
A data set
the population cumulants
15. 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
Sampling
Nominal measurements
16. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.
A statistic
Conditional probability
Marginal distribution
Ratio measurements
17. 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
Power of a test
the population variance
hypotheses
A random variable
18.
the population mean
Valid measure
That value is the median value
Individual
19. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Probability density functions
The Covariance between two random variables X and Y - with expected values E(X) =
A random variable
Pairwise independence
20. 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
Step 1 of a statistical experiment
A probability density function
Step 3 of a statistical experiment
Variable
21. Long-term upward or downward movement over time.
The standard deviation
descriptive statistics
Trend
Marginal distribution
22. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
the sample or population mean
Type I errors & Type II errors
Descriptive
Binary data
23. Is a function that gives the probability of all elements in a given space: see List of probability distributions
A probability distribution
hypotheses
Law of Large Numbers
The average - or arithmetic mean
24. Another name for elementary event.
Atomic event
categorical variables
expected value of X
A Probability measure
25. ?
Likert scale
Law of Large Numbers
Type 2 Error
the population correlation
26. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Valid measure
A Statistical parameter
A random variable
Prior probability
27. 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 I errors
Parameter
Individual
Mutual independence
28. Is used in 'mathematical statistics' (alternatively - 'statistical theory') to study the sampling distributions of sample statistics and - more generally - the properties of statistical procedures. The use of any statistical method is valid when the
Skewness
variance of X
Probability
An Elementary event
29. 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.
Marginal probability
Seasonal effect
Average and arithmetic mean
Posterior probability
30. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.
Marginal probability
A random variable
The standard deviation
Independent Selection
31. Two variables such that their effects on the response variable cannot be distinguished from each other.
Confounded variables
Dependent Selection
That is the median value
The Expected value
32. Describes a characteristic of an individual to be measured or observed.
Divide the sum by the number of values.
That is the median value
Variable
A sample
33. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.
Interval measurements
Type II errors
Null hypothesis
Experimental and observational studies
34. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
Estimator
Inferential statistics
The standard deviation
Joint probability
35. In particular - the pdf of the standard normal distribution is denoted by
Pairwise independence
f(z) - and its cdf by F(z).
A Random vector
The variance of a random variable
36. Is the probability distribution - under repeated sampling of the population - of a given statistic.
Random variables
Skewness
Bias
A sampling distribution
37. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Inferential
the population mean
Sampling Distribution
categorical variables
38. 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.
expected value of X
Probability density functions
Inferential
Conditional distribution
39. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
A Probability measure
Inferential
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Bias
40. Is inference about a population from a random sample drawn from it or - more generally - about a random process from its observed behavior during a finite period of time.
That is the median value
Random variables
Statistical inference
methods of least squares
41. 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
Type II errors
the sample or population mean
A population or statistical population
Inferential statistics
42. 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).
A sample
An event
Divide the sum by the number of values.
Variable
43. Data are gathered and correlations between predictors and response are investigated.
observational study
quantitative variables
Valid measure
The Range
44. Is a parameter that indexes a family of probability distributions.
Residuals
Dependent Selection
Valid measure
A Statistical parameter
45. A numerical measure that assesses the strength of a linear relationship between two variables.
That value is the median value
Placebo effect
A Probability measure
Correlation coefficient
46. Have no meaningful rank order among values.
Atomic event
A Probability measure
Nominal measurements
Statistics
47. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
An estimate of a parameter
A data set
A population or statistical population
Bias
48. 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.
Lurking variable
Statistical dispersion
Skewness
Cumulative distribution functions
49. The collection of all possible outcomes in an experiment.
A population or statistical population
Sample space
s-algebras
Random variables
50. The probability of correctly detecting a false null hypothesis.
Marginal distribution
Power of a test
An event
Prior probability
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