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. 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.
Bias
A likelihood function
methods of least squares
The sample space
2. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Joint probability
The median value
Bias
Statistical inference
3. 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)
The Expected value
Interval measurements
Parameter - or 'statistical parameter'
Type I errors & Type II errors
4. A numerical facsimilie or representation of a real-world phenomenon.
the population mean
Simulation
Parameter - or 'statistical parameter'
hypotheses
5. A subjective estimate of probability.
Credence
descriptive statistics
Dependent Selection
quantitative variables
6. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
categorical variables
A probability space
The variance of a random variable
7. The collection of all possible outcomes in an experiment.
expected value of X
Sample space
Joint distribution
Trend
8. 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
Standard error
Observational study
Descriptive
Joint probability
9. Is that part of a population which is actually observed.
Simulation
That value is the median value
Step 1 of a statistical experiment
A sample
10. 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
Probability density
Bias
Conditional probability
s-algebras
11. Rejecting a true null hypothesis.
Type 1 Error
A probability density function
Inferential statistics
An Elementary event
12. Failing to reject a false null hypothesis.
Particular realizations of a random variable
inferential statistics
Type 2 Error
Skewness
13. Is a sample and the associated data points.
A data set
Statistical dispersion
Average and arithmetic mean
An experimental study
14. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.
Probability and statistics
Probability
Random variables
The median value
15. A numerical measure that describes an aspect of a sample.
Inferential
s-algebras
Statistic
Step 3 of a statistical experiment
16. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Step 1 of a statistical experiment
Law of Large Numbers
Treatment
Count data
17. 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.
Placebo effect
Count data
Experimental and observational studies
An experimental study
18. 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).
An event
Probability density
The variance of a random variable
Posterior probability
19. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Descriptive
Greek letters
Interval measurements
Type II errors
20. Is the length of the smallest interval which contains all the data.
Greek letters
The Range
A random variable
Binary data
21. 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 studies and observational studies.
Experimental and observational studies
Probability density
A Statistical parameter
22. Gives the probability distribution for a continuous random variable.
An event
the population variance
experimental studies and observational studies.
A probability density function
23. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Type II errors
Placebo effect
Type 1 Error
Experimental and observational studies
24. A group of individuals sharing some common features that might affect the treatment.
Block
The Range
Alpha value (Level of Significance)
Estimator
25. (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
Seasonal effect
A probability density function
Parameter
A likelihood function
26. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
That value is the median value
Confounded variables
Divide the sum by the number of values.
A Random vector
27. 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
Skewness
Type 2 Error
Estimator
Type 1 Error
28. Of a group of numbers is the center point of all those number values.
Cumulative distribution functions
Outlier
The average - or arithmetic mean
inferential statistics
29. Is a parameter that indexes a family of probability distributions.
Lurking variable
Cumulative distribution functions
A Statistical parameter
Statistics
30. Many statistical methods seek to minimize the mean-squared error - and these are called
Likert scale
Law of Parsimony
categorical variables
methods of least squares
31. Some commonly used symbols for sample statistics
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Descriptive
A data set
Simple random sample
32. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
Prior probability
Seasonal effect
Reliable measure
33. Is data arising from counting that can take only non-negative integer values.
A population or statistical population
Independence or Statistical independence
Quantitative variable
Count data
34. Describes a characteristic of an individual to be measured or observed.
Confounded variables
Inferential statistics
Variable
A data set
35. A list of individuals from which the sample is actually selected.
Probability and statistics
Variable
variance of X
Sampling frame
36. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Individual
Block
The median value
Statistic
37. Probability of accepting a false null hypothesis.
Beta value
Probability density functions
quantitative variables
The median value
38. 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.
Independent Selection
Probability and statistics
Average and arithmetic mean
methods of least squares
39. 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 average - or arithmetic mean
Joint distribution
Bias
experimental studies and observational studies.
40. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Block
Prior probability
Type I errors & Type II errors
Correlation
41. A variable describes an individual by placing the individual into a category or a group.
Likert scale
s-algebras
Qualitative variable
Confounded variables
42. Some commonly used symbols for population parameters
the population mean
A probability distribution
expected value of X
Valid measure
43. A measure that is relevant or appropriate as a representation of that property.
Alpha value (Level of Significance)
Sampling frame
Law of Parsimony
Valid measure
44. Is defined as the expected value of random variable (X -
Divide the sum by the number of values.
Credence
Type I errors
The Covariance between two random variables X and Y - with expected values E(X) =
45. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
experimental studies and observational studies.
A statistic
Probability and statistics
Credence
46. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
A population or statistical population
Trend
Null hypothesis
Likert scale
47. 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
Step 3 of a statistical experiment
Mutual independence
Ordinal measurements
Quantitative variable
48. 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.
An event
That value is the median value
Conditional distribution
Particular realizations of a random variable
49. To find the average - or arithmetic mean - of a set of numbers:
Divide the sum by the number of values.
The Range
the population mean
Credence
50. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
The standard deviation
covariance of X and Y
Posterior probability
Ordinal measurements