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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
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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 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
An experimental study
Valid measure
Skewness
Probability
2. 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.
An experimental study
Average and arithmetic mean
Seasonal effect
covariance of X and Y
3. A data value that falls outside the overall pattern of the graph.
Outlier
Mutual independence
Lurking variable
observational study
4. (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
Greek letters
Statistic
A likelihood function
Credence
5. (or multivariate random variable) is a vector whose components are random variables on the same probability space.
Standard error
Descriptive
A Random vector
Conditional probability
6. 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.
Quantitative variable
the population mean
That value is the median value
Conditional distribution
7. A numerical measure that describes an aspect of a sample.
Joint probability
Prior probability
Statistic
f(z) - and its cdf by F(z).
8. Failing to reject a false null hypothesis.
The average - or arithmetic mean
Block
Type 2 Error
An Elementary event
9. 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.
Posterior probability
Estimator
Joint probability
Statistical adjustment
10. 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
Kurtosis
Ratio measurements
Posterior probability
P-value
11. Rejecting a true null hypothesis.
Variable
Type 1 Error
Statistic
methods of least squares
12. Data are gathered and correlations between predictors and response are investigated.
Kurtosis
A data point
Sampling Distribution
observational study
13. 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
Experimental and observational studies
Greek letters
A random variable
14. Working from a null hypothesis two basic forms of error are recognized:
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Type I errors & Type II errors
Estimator
Kurtosis
15.
Residuals
Dependent Selection
Correlation coefficient
the population mean
16. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Statistic
Greek letters
Descriptive statistics
A data point
17. 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.
Probability and statistics
covariance of X and Y
A Distribution function
Mutual independence
18. The probability of correctly detecting a false null hypothesis.
the population mean
Power of a test
Estimator
Confounded variables
19. Is the length of the smallest interval which contains all the data.
the population correlation
The sample space
The Range
Divide the sum by the number of values.
20. The collection of all possible outcomes in an experiment.
Pairwise independence
Valid measure
Particular realizations of a random variable
Sample space
21. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Joint distribution
That value is the median value
Law of Large Numbers
applied statistics
22. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
Ordinal measurements
nominal - ordinal - interval - and ratio
Divide the sum by the number of values.
Outlier
23. Of a group of numbers is the center point of all those number values.
Residuals
Seasonal effect
The average - or arithmetic mean
Conditional probability
24. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Coefficient of determination
Descriptive
A Probability measure
A sample
25. A list of individuals from which the sample is actually selected.
Sampling frame
A sampling distribution
Ratio measurements
Probability density
26. A variable describes an individual by placing the individual into a category or a group.
Qualitative variable
An Elementary event
The variance of a random variable
hypothesis
27. A numerical facsimilie or representation of a real-world phenomenon.
Ratio measurements
Simulation
expected value of X
Experimental and observational studies
28. A measure that is relevant or appropriate as a representation of that property.
expected value of X
The Mean of a random variable
Valid measure
variance of X
29. 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.
A Probability measure
The variance of a random variable
covariance of X and Y
Variable
30. 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.
Statistical inference
Dependent Selection
Outlier
The standard deviation
31. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Sampling Distribution
Estimator
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
s-algebras
32. 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.
Correlation coefficient
Outlier
Parameter
Statistics
33. 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.
Random variables
Independent Selection
Lurking variable
Joint probability
34. Describes the spread in the values of the sample statistic when many samples are taken.
The Covariance between two random variables X and Y - with expected values E(X) =
Ordinal measurements
Binary data
Variability
35. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
variance of X
Independence or Statistical independence
Probability density functions
categorical variables
36. 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
Variability
covariance of X and Y
A likelihood function
Observational study
37. Two variables such that their effects on the response variable cannot be distinguished from each other.
Greek letters
Confounded variables
Credence
Type I errors
38. Any specific experimental condition applied to the subjects
Count data
Treatment
Alpha value (Level of Significance)
That is the median value
39. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
observational study
Sampling frame
P-value
quantitative variables
40. 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).
P-value
A likelihood function
An event
Average and arithmetic mean
41. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Coefficient of determination
That value is the median value
Binomial experiment
categorical variables
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.
Sampling
A probability distribution
Count data
Trend
43. (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.
Credence
Reliable measure
A Statistical parameter
An Elementary event
44. A numerical measure that describes an aspect of a population.
Ordinal measurements
Ratio measurements
Parameter
Probability
45. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Prior probability
A Distribution function
Probability and statistics
Probability
46. When there is an even number of values...
That is the median value
Variable
Beta value
Null hypothesis
47. 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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48. ?
the population correlation
Simpson's Paradox
Simulation
Descriptive statistics
49. A measurement such that the random error is small
Reliable measure
Likert scale
Coefficient of determination
An estimate of a parameter
50. A numerical measure that assesses the strength of a linear relationship between two variables.
the population variance
Correlation coefficient
Dependent Selection
Step 2 of a statistical experiment