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. In particular - the pdf of the standard normal distribution is denoted by
A sample
Nominal measurements
f(z) - and its cdf by F(z).
A Distribution function
2. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
Bias
A Random vector
A Distribution function
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
3. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Parameter - or 'statistical parameter'
Quantitative variable
Law of Large Numbers
Sampling
4. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.
the population mean
Correlation coefficient
Prior probability
A Distribution function
5. Probability of accepting a false null hypothesis.
Particular realizations of a random variable
nominal - ordinal - interval - and ratio
Beta value
Kurtosis
6. Var[X] :
applied statistics
variance of X
Marginal distribution
Placebo effect
7. Failing to reject a false null hypothesis.
Type 2 Error
Joint distribution
the population mean
Step 1 of a statistical experiment
8. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Standard error
Residuals
quantitative variables
Seasonal effect
9. 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
Statistic
Quantitative variable
The Mean of a random variable
Probability and statistics
10. 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.
Probability density functions
Kurtosis
descriptive statistics
Trend
11. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
Quantitative variable
s-algebras
Inferential
Conditional probability
12. ?r
categorical variables
A likelihood function
the population cumulants
The median value
13. 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.
Atomic event
Type 1 Error
A population or statistical population
variance of X
14. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Observational study
An estimate of a parameter
expected value of X
The Mean of a random variable
15. 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
Type 1 Error
hypotheses
A data set
Sampling
16. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
An Elementary event
Type II errors
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A data set
17. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data
Dependent Selection
Quantitative variable
quantitative variables
Ratio measurements
18. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
A Statistical parameter
experimental studies and observational studies.
Coefficient of determination
Pairwise independence
19. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
Conditional probability
A population or statistical population
A probability distribution
Probability density functions
20. 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).
Statistics
the population mean
Joint probability
Treatment
21. Is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data. The mean can be used as an estimator.
Estimator
The average - or arithmetic mean
Step 2 of a statistical experiment
Sampling frame
22. Is a measure of its statistical dispersion - indicating how far from the expected value its values typically are. The variance of random variable X is typically designated as - - or simply s2.
applied statistics
The standard deviation
Standard error
The variance of a random variable
23. 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
Inferential statistics
A statistic
the population mean
f(z) - and its cdf by F(z).
24. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
descriptive statistics
categorical variables
Qualitative variable
the population variance
25. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Block
Statistical adjustment
A random variable
f(z) - and its cdf by F(z).
26. 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
A probability space
Correlation
Power of a test
27. Is a parameter that indexes a family of probability distributions.
A Statistical parameter
A Distribution function
Sample space
categorical variables
28. Is a sample and the associated data points.
the population mean
Probability density functions
nominal - ordinal - interval - and ratio
A data set
29. Is its expected value. The mean (or sample mean of a data set is just the average value.
Standard error
Posterior probability
The Mean of a random variable
A sample
30. Of a group of numbers is the center point of all those number values.
The average - or arithmetic mean
variance of X
Simple random sample
Seasonal effect
31. A numerical measure that describes an aspect of a sample.
Statistic
applied statistics
Independent Selection
Posterior probability
32. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Null hypothesis
Bias
Sampling Distribution
covariance of X and Y
33. A numerical facsimilie or representation of a real-world phenomenon.
Kurtosis
Simulation
Treatment
Probability and statistics
34. 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.
methods of least squares
Independent Selection
Sample space
Statistical adjustment
35. 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)
Descriptive
The median value
Interval measurements
An experimental study
36. 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.
Variability
Conditional distribution
Statistical dispersion
That is the median value
37. Are usually written in upper case roman letters: X - Y - etc.
A Probability measure
Ratio measurements
Simple random sample
Random variables
38. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a
Step 2 of a statistical experiment
Binomial experiment
Residuals
hypothesis
39. Is that part of a population which is actually observed.
Dependent Selection
A sample
Quantitative variable
Parameter - or 'statistical parameter'
40. Working from a null hypothesis two basic forms of error are recognized:
Dependent Selection
Variability
Statistical adjustment
Type I errors & Type II errors
41. 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
The sample space
Binomial experiment
Probability
Dependent Selection
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.
the sample or population mean
Reliable measure
Bias
A population or statistical population
43. Describes a characteristic of an individual to be measured or observed.
A population or statistical population
variance of X
Probability
Variable
44. Gives the probability of events in a probability space.
Type II errors
Inferential
A Probability measure
Quantitative variable
45. Have no meaningful rank order among values.
Coefficient of determination
Probability and statistics
Nominal measurements
Divide the sum by the number of values.
46. To find the average - or arithmetic mean - of a set of numbers:
hypothesis
Divide the sum by the number of values.
Binomial experiment
Posterior probability
47. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Descriptive
Type 2 Error
Outlier
Step 3 of a statistical experiment
48.
Placebo effect
The median value
the population cumulants
the population mean
49. 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.
A data set
the population correlation
Seasonal effect
Binary data
50. S^2
the population variance
experimental studies and observational studies.
Standard error
A sampling distribution