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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.
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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. Is that part of a population which is actually observed.
Variable
Mutual independence
the population correlation
A sample
2. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Placebo effect
the population cumulants
Sampling Distribution
A statistic
3. 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
Likert scale
Probability
Valid measure
Block
4. Two variables such that their effects on the response variable cannot be distinguished from each other.
Likert scale
Confounded variables
The Mean of a random variable
A random variable
5. Long-term upward or downward movement over time.
Binary data
Treatment
Trend
the population mean
6. 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
Greek letters
Correlation
Reliable measure
A data set
7. Many statistical methods seek to minimize the mean-squared error - and these are called
The standard deviation
methods of least squares
descriptive statistics
Joint distribution
8. The collection of all possible outcomes in an experiment.
Statistic
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Sample space
A sampling distribution
9. 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 sample space
Divide the sum by the number of values.
quantitative variables
Variable
10. 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
Independent Selection
Beta value
The Range
Inferential statistics
11. Describes a characteristic of an individual to be measured or observed.
expected value of X
Experimental and observational studies
Interval measurements
Variable
12. Is a parameter that indexes a family of probability distributions.
A Statistical parameter
A likelihood function
A data point
Skewness
13. 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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14. Is a function that gives the probability of all elements in a given space: see List of probability distributions
quantitative variables
Kurtosis
Bias
A probability distribution
15. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
s-algebras
Marginal distribution
Atomic event
Sampling
16. 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
Ratio measurements
Variable
Kurtosis
Sample space
17. 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.
Bias
Correlation coefficient
Step 2 of a statistical experiment
The variance of a random variable
18. 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
Type 1 Error
quantitative variables
Observational study
19. 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
Descriptive statistics
Statistical inference
An Elementary event
A sample
20. Working from a null hypothesis two basic forms of error are recognized:
Bias
Type I errors & Type II errors
Outlier
That value is the median value
21. A measurement such that the random error is small
Probability
The standard deviation
Reliable measure
Law of Parsimony
22. 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
Credence
variance of X
Beta value
23. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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24. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Simpson's Paradox
That is the median value
Type I errors & Type II errors
An estimate of a parameter
25. A subjective estimate of probability.
experimental studies and observational studies.
A data point
The Mean of a random variable
Credence
26. 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.
The median value
A data set
observational study
That is the median value
27. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
applied statistics
A statistic
Conditional distribution
Parameter - or 'statistical parameter'
28. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
experimental studies and observational studies.
Probability density functions
Law of Large Numbers
methods of least squares
29. A measure that is relevant or appropriate as a representation of that property.
Experimental and observational studies
Probability
Confounded variables
Valid measure
30. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
A Random vector
The sample space
Conditional distribution
Statistical adjustment
31. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Inferential
covariance of X and Y
Probability and statistics
The standard deviation
32. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Confounded variables
Greek letters
Posterior probability
Outlier
33. Some commonly used symbols for population parameters
An Elementary event
Independence or Statistical independence
the population mean
Quantitative variable
34. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
quantitative variables
Type 1 Error
Statistical adjustment
Posterior probability
35. A numerical measure that assesses the strength of a linear relationship between two variables.
the population mean
hypothesis
Correlation coefficient
A statistic
36. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Observational study
Likert scale
Placebo effect
the sample or population mean
37. Have imprecise differences between consecutive values - but have a meaningful order to those values
Ordinal measurements
The Covariance between two random variables X and Y - with expected values E(X) =
the population cumulants
Kurtosis
38. Is the probability distribution - under repeated sampling of the population - of a given statistic.
A sampling distribution
A Distribution function
The average - or arithmetic mean
categorical variables
39. 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.
The Mean of a random variable
methods of least squares
the population cumulants
Marginal probability
40. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Pairwise independence
Coefficient of determination
Experimental and observational studies
A sampling distribution
41. 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.
Conditional probability
Pairwise independence
Sampling
Joint distribution
42. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
the sample or population mean
Law of Large Numbers
A probability distribution
Conditional distribution
43. The standard deviation of a sampling distribution.
inferential statistics
Sample space
Simple random sample
Standard error
44. The proportion of the explained variation by a linear regression model in the total variation.
Conditional probability
A data point
Coefficient of determination
A probability density function
45. Is the length of the smallest interval which contains all the data.
Interval measurements
The Range
Null hypothesis
Correlation
46. 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).
Qualitative variable
An event
nominal - ordinal - interval - and ratio
A data point
47. (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.
An Elementary event
the population variance
Sample space
A statistic
48. Failing to reject a false null hypothesis.
Conditional distribution
Variable
Type 2 Error
Dependent Selection
49. Is data arising from counting that can take only non-negative integer values.
A Distribution function
Residuals
Count data
Block
50. 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.
Placebo effect
Statistics
Residuals
Independence or Statistical independence