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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
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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. 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
Conditional distribution
Observational study
inferential statistics
Outlier
2. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
observational study
A statistic
Probability density functions
descriptive statistics
3. Statistical methods can be used for summarizing or describing a collection of data; this is called
Skewness
Sampling
Credence
descriptive statistics
4. 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.
the sample or population mean
Type 1 Error
Experimental and observational studies
Dependent Selection
5. A group of individuals sharing some common features that might affect the treatment.
Probability density functions
Block
Type II errors
A population or statistical population
6. Is its expected value. The mean (or sample mean of a data set is just the average value.
The Mean of a random variable
Null hypothesis
inferential statistics
Experimental and observational studies
7. The probability of correctly detecting a false null hypothesis.
Bias
Law of Parsimony
Independence or Statistical independence
Power of a test
8. 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
Inferential
Bias
Skewness
Estimator
9. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Atomic event
applied statistics
Quantitative variable
Binomial experiment
10. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
Coefficient of determination
Average and arithmetic mean
Type 1 Error
s-algebras
11. Is a sample space over which a probability measure has been defined.
Count data
A probability space
Step 1 of a statistical experiment
Type I errors
12.
Statistical inference
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
the population mean
Marginal probability
13. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
covariance of X and Y
Posterior probability
A probability space
Standard error
14. 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 likelihood function
Marginal distribution
Bias
hypothesis
15. 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.
Simulation
The median value
Marginal probability
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
16. Where the null hypothesis is falsely rejected giving a 'false positive'.
hypothesis
Type I errors
Statistic
A random variable
17. 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
Independence or Statistical independence
Inferential
Binomial experiment
18. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Ratio measurements
Quantitative variable
Count data
A population or statistical population
19. To find the average - or arithmetic mean - of a set of numbers:
Statistical dispersion
Power of a test
Divide the sum by the number of values.
observational study
20. Gives the probability of events in a probability space.
A Probability measure
A probability distribution
P-value
Independence or Statistical independence
21. ?r
Coefficient of determination
Block
the population cumulants
the population mean
22. 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
Statistic
Step 1 of a statistical experiment
hypotheses
Count data
23. Is denoted by - pronounced 'x bar'.
Quantitative variable
nominal - ordinal - interval - and ratio
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Statistical adjustment
24. 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'
Greek letters
Conditional probability
Statistical adjustment
Coefficient of determination
25. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
Coefficient of determination
Likert scale
A statistic
The average - or arithmetic mean
26. Is a function that gives the probability of all elements in a given space: see List of probability distributions
A probability distribution
Mutual independence
Random variables
The standard deviation
27. 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).
A population or statistical population
An event
Residuals
Quantitative variable
28. Of a group of numbers is the center point of all those number values.
Beta value
Treatment
The average - or arithmetic mean
Bias
29. 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
The Covariance between two random variables X and Y - with expected values E(X) =
hypotheses
A probability density function
Statistical dispersion
30. A measurement such that the random error is small
Experimental and observational studies
A probability density function
Reliable measure
Sampling Distribution
31. 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
A population or statistical population
Divide the sum by the number of values.
Descriptive statistics
Correlation
32. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.
Simulation
the population mean
expected value of X
Lurking variable
33. When there is an even number of values...
A probability distribution
That is the median value
Average and arithmetic mean
Parameter - or 'statistical parameter'
34. 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.
An experimental study
hypothesis
the population mean
Cumulative distribution functions
35. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
That is the median value
Descriptive
Coefficient of determination
Placebo effect
36. Is a parameter that indexes a family of probability distributions.
Trend
A sampling distribution
A Statistical parameter
A data set
37. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
The Covariance between two random variables X and Y - with expected values E(X) =
Pairwise independence
Experimental and observational studies
Greek letters
38. Have imprecise differences between consecutive values - but have a meaningful order to those values
A sample
Ordinal measurements
Statistical inference
Descriptive
39. In particular - the pdf of the standard normal distribution is denoted by
Dependent Selection
f(z) - and its cdf by F(z).
Confounded variables
Observational study
40. Many statistical methods seek to minimize the mean-squared error - and these are called
Step 3 of a statistical experiment
Alpha value (Level of Significance)
variance of X
methods of least squares
41. A subjective estimate of probability.
That is the median value
Step 2 of a statistical experiment
Credence
Coefficient of determination
42. Is a process of selecting observations to obtain knowledge about a population. There are many methods to choose on which sample to do the observations.
the sample or population mean
Sampling
Dependent Selection
Cumulative distribution functions
43. Is the length of the smallest interval which contains all the data.
The Range
Descriptive statistics
categorical variables
s-algebras
44. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.
the population cumulants
Simple random sample
Ordinal measurements
The sample space
45. The standard deviation of a sampling distribution.
Standard error
Simpson's Paradox
Treatment
The variance of a random variable
46. 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
Prior probability
s-algebras
Random variables
Inferential statistics
47. Have no meaningful rank order among values.
Mutual independence
Marginal probability
Nominal measurements
The Mean of a random variable
48. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Credence
Likert scale
Probability and statistics
Observational study
49. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
covariance of X and Y
Law of Large Numbers
Qualitative variable
Inferential
50. Another name for elementary event.
Pairwise independence
Atomic event
The variance of a random variable
That value is the median value