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. When there is an even number of values...
The average - or arithmetic mean
A Probability measure
That is the median value
Confounded variables
2. In particular - the pdf of the standard normal distribution is denoted by
f(z) - and its cdf by F(z).
Likert scale
Posterior probability
the population cumulants
3. 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
Marginal probability
Coefficient of determination
Probability density
Outlier
4. 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.
Statistical inference
A population or statistical population
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A Distribution function
5. 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
the population mean
Mutual independence
Independence or Statistical independence
P-value
6. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.
Confounded variables
The sample space
A Random vector
Trend
7. 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 Probability measure
Lurking variable
That value is the median value
Step 2 of a statistical experiment
8. Many statistical methods seek to minimize the mean-squared error - and these are called
methods of least squares
the population cumulants
the sample or population mean
Credence
9. 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.
Kurtosis
Likert scale
A data point
Parameter
10. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Likert scale
Atomic event
Independence or Statistical independence
Block
11. Are usually written in upper case roman letters: X - Y - etc.
Law of Large Numbers
Random variables
Variable
Parameter
12. 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
Joint distribution
Law of Large Numbers
Variability
Correlation
13. (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
Conditional distribution
Alpha value (Level of Significance)
A likelihood function
P-value
14. 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
Bias
Correlation coefficient
The Mean of a random variable
Step 3 of a statistical experiment
15. 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
the population mean
Null hypothesis
Experimental and observational studies
s-algebras
16. ?r
the population cumulants
Sampling frame
Statistical adjustment
Type 1 Error
17. Are simply two different terms for the same thing. Add the given values
Estimator
Sampling Distribution
inferential statistics
Average and arithmetic mean
18. Probability of accepting a false null hypothesis.
A probability distribution
Beta value
f(z) - and its cdf by F(z).
Skewness
19. A variable describes an individual by placing the individual into a category or a group.
Qualitative variable
Simple random sample
Pairwise independence
Ordinal measurements
20. Have no meaningful rank order among values.
That value is the median value
Parameter - or 'statistical parameter'
Nominal measurements
Statistical adjustment
21. 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.
Pairwise independence
That value is the median value
The Mean of a random variable
Ordinal measurements
22. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Inferential
A sample
Divide the sum by the number of values.
A data point
23. 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.
Statistical dispersion
Conditional distribution
Trend
Inferential statistics
24. 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
hypothesis
descriptive statistics
Beta value
Average and arithmetic mean
25. Is its expected value. The mean (or sample mean of a data set is just the average value.
The Mean of a random variable
Inferential
A sampling distribution
Average and arithmetic mean
26. 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.
A statistic
A probability distribution
Statistics
Sample space
27. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
The Covariance between two random variables X and Y - with expected values E(X) =
A probability density function
Joint probability
28. S^2
An estimate of a parameter
the population variance
That is the median value
Random variables
29. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies
The Covariance between two random variables X and Y - with expected values E(X) =
experimental studies and observational studies.
Law of Parsimony
Correlation
30. Where the null hypothesis is falsely rejected giving a 'false positive'.
A likelihood function
Type I errors
Experimental and observational studies
Beta value
31. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
A population or statistical population
Nominal measurements
Atomic event
A statistic
32. Describes the spread in the values of the sample statistic when many samples are taken.
Mutual independence
Valid measure
Variability
Descriptive
33.
the population mean
the population cumulants
A sampling distribution
Correlation
34. 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.
An event
Pairwise independence
Marginal distribution
Simpson's Paradox
35. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.
Correlation
Dependent Selection
Type I errors
Law of Parsimony
36. 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.
Experimental and observational studies
Type I errors & Type II errors
the population mean
A population or statistical population
37. (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.
Probability density
An Elementary event
The Range
Null hypothesis
38. 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.
Experimental and observational studies
A random variable
Dependent Selection
An experimental study
39. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
A Random vector
The median value
Cumulative distribution functions
A sampling distribution
40. Is defined as the expected value of random variable (X -
An experimental study
The Covariance between two random variables X and Y - with expected values E(X) =
hypothesis
A Distribution function
41. Another name for elementary event.
Statistic
Cumulative distribution functions
Atomic event
P-value
42. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Binomial experiment
Sampling Distribution
The sample space
The average - or arithmetic mean
43. 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
44. 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
A probability space
A Statistical parameter
hypotheses
Probability
45. 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.
A random variable
Sampling Distribution
Statistic
Marginal distribution
46. A numerical measure that describes an aspect of a population.
Null hypothesis
An experimental study
A population or statistical population
Parameter
47. 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
Probability
A Distribution function
the population mean
Divide the sum by the number of values.
48. 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)
Interval measurements
Descriptive statistics
Greek letters
A data set
49. ?
A random variable
Probability and statistics
Inferential statistics
the population correlation
50. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Observational study
Binary data
experimental studies and observational studies.
Descriptive
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