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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
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Subjects
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clep
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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. A group of individuals sharing some common features that might affect the treatment.
Block
A probability distribution
nominal - ordinal - interval - and ratio
A Random vector
2. A measurement such that the random error is small
Reliable measure
the population mean
A population or statistical population
Probability density functions
3. Many statistical methods seek to minimize the mean-squared error - and these are called
Law of Large Numbers
nominal - ordinal - interval - and ratio
Independence or Statistical independence
methods of least squares
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.
Alpha value (Level of Significance)
Type 2 Error
The standard deviation
Statistical inference
5. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Statistical adjustment
Placebo effect
Likert scale
6. Is data arising from counting that can take only non-negative integer values.
Count data
Variable
Correlation coefficient
covariance of X and Y
7. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
A random variable
nominal - ordinal - interval - and ratio
Binary data
methods of least squares
8. A numerical measure that assesses the strength of a linear relationship between two variables.
Correlation coefficient
Statistical inference
Experimental and observational studies
Cumulative distribution functions
9. 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
Sampling Distribution
A probability density function
Step 1 of a statistical experiment
Sample space
10. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
observational study
descriptive statistics
Treatment
Individual
11. Gives the probability of events in a probability space.
Law of Large Numbers
A Probability measure
Average and arithmetic mean
variance of X
12. Where the null hypothesis is falsely rejected giving a 'false positive'.
Type I errors
Correlation
Probability density
Bias
13. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Statistical inference
descriptive statistics
Binary data
quantitative variables
14. Is data that can take only two values - usually represented by 0 and 1.
Binary data
the population cumulants
An experimental study
The Mean of a random variable
15. (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.
Seasonal effect
The variance of a random variable
Mutual independence
An Elementary event
16. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called
The sample space
inferential statistics
the population correlation
An Elementary event
17. Long-term upward or downward movement over time.
Confounded variables
The average - or arithmetic mean
Trend
Simple random sample
18. 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.
Statistics
A probability distribution
Dependent Selection
Mutual independence
19. Some commonly used symbols for population parameters
the population mean
Parameter
Sampling Distribution
A sampling distribution
20. 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
A Distribution function
Ratio measurements
Qualitative variable
A Probability measure
21. Have no meaningful rank order among values.
nominal - ordinal - interval - and ratio
Conditional probability
Standard error
Nominal measurements
22. (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
Power of a test
Bias
A probability density function
A likelihood function
23. Describes a characteristic of an individual to be measured or observed.
Skewness
Correlation
Variable
Divide the sum by the number of values.
24. Are simply two different terms for the same thing. Add the given values
Null hypothesis
A likelihood function
Outlier
Average and arithmetic mean
25. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Power of a test
Type II errors
Parameter - or 'statistical parameter'
Pairwise independence
26. Is denoted by - pronounced 'x bar'.
A random variable
Lurking variable
Sampling
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
27. 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.
Kurtosis
A probability density function
Divide the sum by the number of values.
That value is the median value
28. A numerical measure that describes an aspect of a sample.
nominal - ordinal - interval - and ratio
Statistic
quantitative variables
A Random vector
29. 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
methods of least squares
Experimental and observational studies
Conditional probability
30. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
Block
Marginal probability
Type II errors
A statistic
31. 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
categorical variables
Average and arithmetic mean
Placebo effect
32. In particular - the pdf of the standard normal distribution is denoted by
f(z) - and its cdf by F(z).
covariance of X and Y
Individual
An event
33. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
s-algebras
Mutual independence
Marginal distribution
Particular realizations of a random variable
34. (cdfs) are denoted by upper case letters - e.g. F(x).
inferential statistics
Cumulative distribution functions
Lurking variable
expected value of X
35. 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.
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36. ?
Parameter - or 'statistical parameter'
the population correlation
Law of Large Numbers
The variance of a random variable
37. Are usually written in upper case roman letters: X - Y - etc.
Variability
Sample space
Random variables
An estimate of a parameter
38. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
Statistical dispersion
applied statistics
A statistic
Descriptive
39. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'
Statistical adjustment
Conditional probability
Probability density
The median value
40. Cov[X - Y] :
covariance of X and Y
Outlier
A population or statistical population
Type 2 Error
41. 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
Power of a test
Mutual independence
applied statistics
A Statistical parameter
42. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Residuals
Skewness
Sampling Distribution
f(z) - and its cdf by F(z).
43. Is the probability distribution - under repeated sampling of the population - of a given statistic.
A Statistical parameter
variance of X
Variable
A sampling distribution
44. Is a sample space over which a probability measure has been defined.
A probability space
the population mean
covariance of X and Y
Statistical dispersion
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
Greek letters
Statistic
Null hypothesis
A Statistical parameter
46. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Correlation
methods of least squares
A random variable
Descriptive
47. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
Trend
The standard deviation
covariance of X and Y
A random variable
48. 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.
A Distribution function
Outlier
Conditional distribution
Probability
49. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.
Kurtosis
Marginal probability
hypotheses
Beta value
50. Have imprecise differences between consecutive values - but have a meaningful order to those values
Ordinal measurements
Binomial experiment
Count data
Statistics