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. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
An event
hypotheses
Skewness
Statistical dispersion
2. Is its expected value. The mean (or sample mean of a data set is just the average value.
The variance of a random variable
Marginal distribution
A Random vector
The Mean of a random variable
3. ?r
A Statistical parameter
Treatment
Beta value
the population cumulants
4. Var[X] :
variance of X
the population mean
A probability space
A Statistical parameter
5. 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
Observational study
inferential statistics
Kurtosis
Divide the sum by the number of values.
6. The probability of correctly detecting a false null hypothesis.
Credence
Power of a test
Sampling
Random variables
7. Some commonly used symbols for population parameters
observational study
Count data
Conditional distribution
the population mean
8. 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.
experimental studies and observational studies.
Seasonal effect
Likert scale
Simulation
9. Describes a characteristic of an individual to be measured or observed.
A statistic
Sampling
Variable
Confounded variables
10. A group of individuals sharing some common features that might affect the treatment.
Type 1 Error
Block
the population correlation
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
11. 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)
Kurtosis
Interval measurements
Experimental and observational studies
An experimental study
12. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Independence or Statistical independence
Residuals
Type 1 Error
The average - or arithmetic mean
13. A numerical facsimilie or representation of a real-world phenomenon.
A Probability measure
Mutual independence
Atomic event
Simulation
14. A numerical measure that describes an aspect of a sample.
Statistic
the population cumulants
Power of a test
Step 1 of a statistical experiment
15. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
A Random vector
That is the median value
Count data
Power of a test
16. To find the average - or arithmetic mean - of a set of numbers:
Reliable measure
Divide the sum by the number of values.
descriptive statistics
Kurtosis
17. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Type 1 Error
Credence
Lurking variable
Prior probability
18. A measurement such that the random error is small
Reliable measure
nominal - ordinal - interval - and ratio
An experimental study
Statistical dispersion
19. 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).
Joint probability
Step 2 of a statistical experiment
Experimental and observational studies
Probability
20. Any specific experimental condition applied to the subjects
A Distribution function
Ratio measurements
The variance of a random variable
Treatment
21. 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
Marginal probability
A Probability measure
Descriptive
hypotheses
22. Probability of accepting a false null hypothesis.
Beta value
Residuals
The average - or arithmetic mean
Law of Large Numbers
23. 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.
Type I errors
That is the median value
An experimental study
Average and arithmetic mean
24. Gives the probability distribution for a continuous random variable.
A probability density function
Marginal probability
Correlation
Power of a test
25. A subjective estimate of probability.
P-value
A likelihood function
Credence
Observational study
26. Have no meaningful rank order among values.
Sampling Distribution
Nominal measurements
Sampling
s-algebras
27. 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
28. 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.
That value is the median value
Nominal measurements
The variance of a random variable
A Probability measure
29. 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.
The standard deviation
Average and arithmetic mean
Experimental and observational studies
That value is the median value
30. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
the sample or population mean
Nominal measurements
Atomic event
Variability
31. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Variable
An experimental study
hypotheses
Pairwise independence
32. Is a sample space over which a probability measure has been defined.
covariance of X and Y
A probability space
The Expected value
A random variable
33. 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
Divide the sum by the number of values.
the population cumulants
Binary data
34. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Placebo effect
Step 2 of a statistical experiment
Correlation
Law of Large Numbers
35. Is a sample and the associated data points.
A data set
An event
variance of X
The Covariance between two random variables X and Y - with expected values E(X) =
36. Some commonly used symbols for sample statistics
Divide the sum by the number of values.
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Probability
A data set
37. Failing to reject a false null hypothesis.
Treatment
Bias
Type 2 Error
the population cumulants
38. 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
Mutual independence
An event
Individual
covariance of X and Y
39. Gives the probability of events in a probability space.
Sample space
A Probability measure
Inferential statistics
Individual
40. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Coefficient of determination
Inferential
Power of a test
Placebo effect
41. 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.
The variance of a random variable
the population cumulants
Dependent Selection
Binomial experiment
42. Is denoted by - pronounced 'x bar'.
Standard error
Treatment
Step 1 of a statistical experiment
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
43. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
The median value
A probability density function
Valid measure
Probability density functions
44. Is a function that gives the probability of all elements in a given space: see List of probability distributions
Block
Type 2 Error
A probability distribution
Binomial experiment
45. Many statistical methods seek to minimize the mean-squared error - and these are called
methods of least squares
the population mean
Individual
Binary data
46. 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.
Conditional probability
Credence
A statistic
A random variable
47. 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
48. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Likert scale
Step 3 of a statistical experiment
Experimental and observational studies
A random variable
49. A list of individuals from which the sample is actually selected.
Type II errors
covariance of X and Y
Type 2 Error
Sampling frame
50. Cov[X - Y] :
covariance of X and Y
Greek letters
the population variance
The Covariance between two random variables X and Y - with expected values E(X) =