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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
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Study First
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. Describes a characteristic of an individual to be measured or observed.
Variable
A Probability measure
Simpson's Paradox
The Covariance between two random variables X and Y - with expected values E(X) =
2. When you have two or more competing models - choose the simpler of the two models.
Conditional distribution
A Random vector
That value is the median value
Law of Parsimony
3. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
An Elementary event
Joint distribution
Particular realizations of a random variable
Pairwise independence
4. 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
Simulation
The standard deviation
A Random vector
Skewness
5. 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
Step 1 of a statistical experiment
Likert scale
Joint distribution
Type II errors
6. A numerical measure that assesses the strength of a linear relationship between two variables.
Correlation coefficient
quantitative variables
Type I errors
A random variable
7. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Statistics
Prior probability
An estimate of a parameter
Experimental and observational studies
8. A sample selected in such a way that each individual is equally likely to be selected as well as any group of size n is equally likely to be selected.
Reliable measure
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A Statistical parameter
Simple random sample
9. Another name for elementary event.
Atomic event
Descriptive statistics
Joint distribution
A data set
10. Describes the spread in the values of the sample statistic when many samples are taken.
the population mean
Valid measure
Variability
Kurtosis
11. 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
categorical variables
Statistical dispersion
Probability
Placebo effect
12. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Quantitative variable
Sampling
the sample or population mean
A sample
13. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are
Observational study
Descriptive statistics
Type 2 Error
Trend
14. 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.
An Elementary event
A sample
Kurtosis
Cumulative distribution functions
15. Of a group of numbers is the center point of all those number values.
An experimental study
Descriptive
The average - or arithmetic mean
A sampling distribution
16. 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.
s-algebras
Valid measure
That value is the median value
Probability
17. A variable describes an individual by placing the individual into a category or a group.
Atomic event
Quantitative variable
Qualitative variable
Sampling frame
18. 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.
Sampling frame
Inferential statistics
Estimator
Simulation
19. Is data that can take only two values - usually represented by 0 and 1.
Binary data
Inferential
Likert scale
Correlation
20. 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
Null hypothesis
the population correlation
expected value of X
experimental studies and observational studies.
21. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
descriptive statistics
A Statistical parameter
hypothesis
Inferential
22. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
quantitative variables
Type I errors
Prior probability
Descriptive
23. Cov[X - Y] :
Marginal probability
An experimental study
A data point
covariance of X and Y
24. Two variables such that their effects on the response variable cannot be distinguished from each other.
Type II errors
Atomic event
Statistical inference
Confounded variables
25. 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 statistic
Standard error
Correlation
applied statistics
26. Have imprecise differences between consecutive values - but have a meaningful order to those values
Ordinal measurements
A Statistical parameter
A data set
The median value
27. 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.
A statistic
Dependent Selection
Statistics
A Distribution function
28. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Type I errors
Posterior probability
Sampling Distribution
Variability
29. Probability of accepting a false null hypothesis.
Posterior probability
Beta value
Conditional distribution
Statistical inference
30. Is its expected value. The mean (or sample mean of a data set is just the average value.
Binary data
The Mean of a random variable
covariance of X and Y
Sample space
31. Many statistical methods seek to minimize the mean-squared error - and these are called
Simple random sample
methods of least squares
Ordinal measurements
Interval measurements
32. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Treatment
Prior probability
nominal - ordinal - interval - and ratio
Conditional distribution
33. A group of individuals sharing some common features that might affect the treatment.
Interval measurements
Block
Step 2 of a statistical experiment
Law of Large Numbers
34. 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
the population mean
Sampling Distribution
35. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
Probability
That is the median value
Greek letters
A Random vector
36. 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.
Kurtosis
Statistical inference
A sample
Sampling Distribution
37. Is the probability distribution - under repeated sampling of the population - of a given statistic.
Type I errors
A sampling distribution
A Statistical parameter
Step 2 of a statistical experiment
38. To find the average - or arithmetic mean - of a set of numbers:
Divide the sum by the number of values.
Type II errors
Conditional probability
the population mean
39. Rejecting a true null hypothesis.
Experimental and observational studies
methods of least squares
Type 1 Error
Joint distribution
40. Any specific experimental condition applied to the subjects
Treatment
Pairwise independence
Step 3 of a statistical experiment
A population or statistical population
41. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Sampling frame
Bias
The average - or arithmetic mean
Statistical adjustment
42. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
experimental studies and observational studies.
Likert scale
Step 2 of a statistical experiment
Inferential statistics
43. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Statistical dispersion
Lurking variable
Dependent Selection
Independent Selection
44. 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.
A population or statistical population
methods of least squares
Conditional distribution
A likelihood function
45. 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}.
A data set
Credence
The sample space
Conditional distribution
46. 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.
Inferential statistics
Experimental and observational studies
The variance of a random variable
The Mean of a random variable
47. Where the null hypothesis is falsely rejected giving a 'false positive'.
Coefficient of determination
the population mean
Quantitative variable
Type I errors
48. Is a sample and the associated data points.
Kurtosis
Step 2 of a statistical experiment
A data set
Binary data
49. 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 median value
expected value of X
inferential statistics
the sample or population mean
50. 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
Seasonal effect
Posterior probability
Bias