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. Gives the probability of events in a probability space.
Skewness
A Probability measure
A Distribution function
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
2. Is the length of the smallest interval which contains all the data.
Binomial experiment
An estimate of a parameter
A Statistical parameter
The Range
3. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Type 1 Error
Likert scale
An estimate of a parameter
Step 3 of a statistical experiment
4. A data value that falls outside the overall pattern of the graph.
Sampling Distribution
Parameter - or 'statistical parameter'
Outlier
Independent Selection
5. A measurement such that the random error is small
f(z) - and its cdf by F(z).
inferential statistics
Reliable measure
Seasonal effect
6. Is denoted by - pronounced 'x bar'.
Independence or Statistical independence
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A probability density function
Coefficient of determination
7. 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
Marginal distribution
Step 3 of a statistical experiment
Lurking variable
Step 2 of a statistical experiment
8. 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
Step 1 of a statistical experiment
Descriptive statistics
Type 2 Error
expected value of X
9. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Statistical dispersion
Outlier
Observational study
A probability distribution
10. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Prior probability
Simpson's Paradox
Individual
Type 1 Error
11. 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
Type I errors & Type II errors
Conditional distribution
Sample space
Probability
12. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
hypothesis
A statistic
Ordinal measurements
Treatment
13. 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
Pairwise independence
Mutual independence
Step 2 of a statistical experiment
An estimate of a parameter
14. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
P-value
The Covariance between two random variables X and Y - with expected values E(X) =
the population mean
Posterior probability
15. 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.
16. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.
Observational study
A population or statistical population
applied statistics
Block
17. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
The sample space
Probability density
A Random vector
the population cumulants
18. 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
experimental studies and observational studies.
Quantitative variable
The Expected value
Average and arithmetic mean
19. 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
Observational study
Probability density functions
variance of X
20. E[X] :
Likert scale
expected value of X
Conditional distribution
A Random vector
21. ?r
hypothesis
the population cumulants
Atomic event
observational study
22. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Statistical dispersion
Descriptive
Residuals
That value is the median value
23. Is data arising from counting that can take only non-negative integer values.
P-value
Law of Large Numbers
Count data
Alpha value (Level of Significance)
24. Some commonly used symbols for sample statistics
A probability space
The Range
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Quantitative variable
25. A list of individuals from which the sample is actually selected.
the sample or population mean
Step 2 of a statistical experiment
Individual
Sampling frame
26. Have imprecise differences between consecutive values - but have a meaningful order to those values
nominal - ordinal - interval - and ratio
experimental studies and observational studies.
An estimate of a parameter
Ordinal measurements
27. 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
the population cumulants
Reliable measure
Probability density
Descriptive statistics
28. A numerical measure that assesses the strength of a linear relationship between two variables.
Skewness
Type I errors & Type II errors
Correlation coefficient
hypothesis
29. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).
Standard error
Joint probability
Statistical dispersion
Step 2 of a statistical experiment
30. 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.
Marginal probability
A probability density function
Posterior probability
An experimental study
31. Two variables such that their effects on the response variable cannot be distinguished from each other.
Confounded variables
Treatment
Joint distribution
Residuals
32. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Sampling Distribution
The Range
Binomial experiment
hypotheses
33. A group of individuals sharing some common features that might affect the treatment.
Independence or Statistical independence
Law of Parsimony
Joint probability
Block
34. 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.
Seasonal effect
A sample
Sampling Distribution
Correlation coefficient
35. Any specific experimental condition applied to the subjects
Sampling frame
Seasonal effect
Law of Large Numbers
Treatment
36. 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.
Residuals
Atomic event
That value is the median value
Statistical adjustment
37. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Inferential
Statistical adjustment
Conditional probability
A probability distribution
38. 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.
covariance of X and Y
Simulation
Statistical adjustment
Dependent Selection
39. 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
A random variable
Observational study
the population mean
A population or statistical population
40. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Treatment
Particular realizations of a random variable
A population or statistical population
The median value
41. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Individual
Seasonal effect
the population mean
quantitative variables
42. 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.
A Statistical parameter
Prior probability
Bias
Law of Large Numbers
43. 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
Independent Selection
Lurking variable
the population cumulants
44. Is a measure of the asymmetry of the probability distribution of a real-valued random variable. Roughly speaking - a distribution has positive skew (right-skewed) if the higher tail is longer and negative skew (left-skewed) if the lower tail is longe
The standard deviation
Skewness
The variance of a random variable
Block
45. 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
Null hypothesis
Joint distribution
Random variables
Sampling Distribution
46. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
Statistical inference
s-algebras
Experimental and observational studies
Kurtosis
47. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Joint probability
Greek letters
That value is the median value
A probability distribution
48. The standard deviation of a sampling distribution.
Atomic event
Seasonal effect
Standard error
experimental studies and observational studies.
49. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Trend
Quantitative variable
P-value
the sample or population mean
50. Statistical methods can be used for summarizing or describing a collection of data; this is called
descriptive statistics
That value is the median value
Cumulative distribution functions
Quantitative variable