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Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
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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. A subjective estimate of probability.
Quantitative variable
Credence
The sample space
Parameter - or 'statistical parameter'
2. Have imprecise differences between consecutive values - but have a meaningful order to those values
Cumulative distribution functions
Ordinal measurements
A probability space
Treatment
3. Are simply two different terms for the same thing. Add the given values
The sample space
Simpson's Paradox
Average and arithmetic mean
Residuals
4. Have no meaningful rank order among values.
Nominal measurements
Mutual independence
Law of Large Numbers
The average - or arithmetic mean
5. 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.
Probability
The Expected value
The variance of a random variable
Lurking variable
6. Many statistical methods seek to minimize the mean-squared error - and these are called
methods of least squares
Qualitative variable
Nominal measurements
A random variable
7. The collection of all possible outcomes in an experiment.
Sample space
Count data
variance of X
The Mean of a random variable
8. 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
Alpha value (Level of Significance)
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Block
Probability and statistics
9. The proportion of the explained variation by a linear regression model in the total variation.
The Expected value
categorical variables
experimental studies and observational studies.
Coefficient of determination
10. The probability of correctly detecting a false null hypothesis.
An event
An experimental study
Power of a test
Lurking variable
11. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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12. A data value that falls outside the overall pattern of the graph.
quantitative variables
Alpha value (Level of Significance)
Outlier
Probability
13. The standard deviation of a sampling distribution.
Standard error
Type 2 Error
Sampling Distribution
Type I errors
14.
descriptive statistics
the population mean
covariance of X and Y
Coefficient of determination
15. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Sample space
A probability distribution
A Random vector
categorical variables
16. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Beta value
Statistic
Mutual independence
Quantitative variable
17. Statistical methods can be used for summarizing or describing a collection of data; this is called
The variance of a random variable
Qualitative variable
Null hypothesis
descriptive statistics
18. Is data arising from counting that can take only non-negative integer values.
Ratio measurements
Law of Parsimony
Conditional probability
Count data
19. Data are gathered and correlations between predictors and response are investigated.
Joint distribution
observational study
Inferential
A probability density function
20. 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).
Law of Parsimony
Dependent Selection
An event
Skewness
21. 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
An experimental study
Correlation coefficient
Simple random sample
22. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.
Treatment
A data point
The Expected value
the population mean
23. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Confounded variables
Standard error
Simulation
Greek letters
24. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Quantitative variable
Pairwise independence
Individual
Conditional distribution
25. Is the length of the smallest interval which contains all the data.
Joint distribution
Type 1 Error
The standard deviation
The Range
26. 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.
Null hypothesis
The Mean of a random variable
That value is the median value
Pairwise independence
27. In particular - the pdf of the standard normal distribution is denoted by
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
f(z) - and its cdf by F(z).
The standard deviation
Probability
28. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.
A probability density function
A random variable
the population mean
The median value
29. Gives the probability distribution for a continuous random variable.
An experimental study
A Random vector
Type I errors
A probability density function
30. 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.
The variance of a random variable
Step 3 of a statistical experiment
Sampling Distribution
An estimate of a parameter
31. Is its expected value. The mean (or sample mean of a data set is just the average value.
methods of least squares
The Mean of a random variable
Likert scale
Random variables
32. Failing to reject a false null hypothesis.
Type 2 Error
A Statistical parameter
Probability density
the sample or population mean
33. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Reliable measure
Ratio measurements
Sample space
Type II errors
34. A group of individuals sharing some common features that might affect the treatment.
Block
Bias
Credence
That value is the median value
35. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
An estimate of a parameter
the population cumulants
Qualitative variable
Individual
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.
Law of Parsimony
Parameter
Statistical inference
variance of X
37. Is the study of the collection - organization - analysis - and interpretation of data. It deals with all aspects of this - including the planning of data collection in terms of the design of surveys and experiments.
Credence
Inferential statistics
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Statistics
38. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Trend
Binomial experiment
Individual
Probability
39. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.
Type 1 Error
Simple random sample
Alpha value (Level of Significance)
Joint distribution
40. 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
A Distribution function
Placebo effect
applied statistics
41. 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
Variable
Beta value
That value is the median value
42. To find the average - or arithmetic mean - of a set of numbers:
Divide the sum by the number of values.
Parameter
f(z) - and its cdf by F(z).
Simple random sample
43. Probability of accepting a false null hypothesis.
Kurtosis
A data point
An event
Beta value
44. 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
Credence
Inferential
Descriptive statistics
Joint probability
45. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Count data
Treatment
P-value
Descriptive
46. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
The standard deviation
Type 2 Error
A probability density function
Valid measure
47. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Statistics
Statistical dispersion
Sampling Distribution
Placebo effect
48. When there is an even number of values...
Marginal distribution
Qualitative variable
That is the median value
Variable
49. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i
Independence or Statistical independence
A Distribution function
Random variables
Inferential statistics
50. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
Estimator
A probability distribution
s-algebras
hypotheses