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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
.
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. The collection of all possible outcomes in an experiment.
Placebo effect
Sample space
Statistics
hypotheses
2. 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.
Simpson's Paradox
The average - or arithmetic mean
Individual
Independent Selection
3. Is its expected value. The mean (or sample mean of a data set is just the average value.
hypotheses
descriptive statistics
The Mean of a random variable
applied statistics
4. Is defined as the expected value of random variable (X -
The Covariance between two random variables X and Y - with expected values E(X) =
Nominal measurements
A Distribution function
The average - or arithmetic mean
5. 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
Estimator
Ratio measurements
Conditional distribution
covariance of X and Y
6. 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
Count data
Null hypothesis
Observational study
Correlation coefficient
7. 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.
Conditional distribution
Average and arithmetic mean
Power of a test
Probability and statistics
8. 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
quantitative variables
Descriptive statistics
That value is the median value
Likert scale
9. A measure that is relevant or appropriate as a representation of that property.
Mutual independence
Valid measure
Probability density
Variable
10. Is the length of the smallest interval which contains all the data.
Divide the sum by the number of values.
The Range
variance of X
Bias
11. 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
Reliable measure
The variance of a random variable
Statistical adjustment
12. Is a set of entities about which statistical inferences are to be drawn - often based on random sampling. One can also talk about a population of measurements or values.
Placebo effect
Statistic
A population or statistical population
f(z) - and its cdf by F(z).
13. 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.
Statistics
Marginal probability
Atomic event
Law of Large Numbers
14. Is denoted by - pronounced 'x bar'.
Reliable measure
A sample
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
That is the median value
15. Probability of accepting a false null hypothesis.
Reliable measure
Sample space
variance of X
Beta value
16. A subjective estimate of probability.
Independent Selection
Simpson's Paradox
Variability
Credence
17. (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.
Kurtosis
An Elementary event
Simulation
Confounded variables
18. Gives the probability of events in a probability space.
P-value
A Probability measure
Conditional probability
Law of Large Numbers
19. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Law of Large Numbers
Conditional probability
Type II errors
Binomial experiment
20. Another name for elementary event.
the sample or population mean
covariance of X and Y
Atomic event
Parameter
21. 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.
A sample
Kurtosis
the population cumulants
f(z) - and its cdf by F(z).
22. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Residuals
A Distribution function
Variable
Joint probability
23. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
Probability density functions
A sampling distribution
The standard deviation
Reliable measure
24. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
The variance of a random variable
Prior probability
Parameter
Quantitative variable
25. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit
quantitative variables
the population mean
Conditional probability
Probability density
26. Are usually written in upper case roman letters: X - Y - etc.
A likelihood function
Ordinal measurements
The Covariance between two random variables X and Y - with expected values E(X) =
Random variables
27. 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.
Simple random sample
Step 1 of a statistical experiment
Alpha value (Level of Significance)
Probability density functions
28. Statistical methods can be used for summarizing or describing a collection of data; this is called
descriptive statistics
Alpha value (Level of Significance)
Type I errors
Variable
29. 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
The standard deviation
That value is the median value
Bias
Correlation
30. Any specific experimental condition applied to the subjects
Dependent Selection
Treatment
Simulation
variance of X
31. The probability of correctly detecting a false null hypothesis.
Treatment
Simple random sample
Type II errors
Power of a test
32. Have meaningful distances between measurements defined - but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit)
Interval measurements
The Mean of a random variable
Null hypothesis
experimental studies and observational studies.
33. 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.
An estimate of a parameter
Observational study
Statistical inference
covariance of X and Y
34. The standard deviation of a sampling distribution.
expected value of X
Coefficient of determination
Standard error
Mutual independence
35. 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.
Type 2 Error
The Mean of a random variable
Seasonal effect
Estimator
36. A group of individuals sharing some common features that might affect the treatment.
Greek letters
Block
A statistic
Null hypothesis
37. Is a sample space over which a probability measure has been defined.
The variance of a random variable
f(z) - and its cdf by F(z).
A probability space
Beta value
38. (cdfs) are denoted by upper case letters - e.g. F(x).
Cumulative distribution functions
hypothesis
Individual
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
39. The proportion of the explained variation by a linear regression model in the total variation.
A Statistical parameter
Coefficient of determination
hypothesis
the population variance
40. 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
Simpson's Paradox
Beta value
Null hypothesis
Bias
41. 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.
the sample or population mean
A data point
Type 2 Error
Independence or Statistical independence
42. 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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43. In particular - the pdf of the standard normal distribution is denoted by
Marginal probability
f(z) - and its cdf by F(z).
Atomic event
Residuals
44. 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.
Bias
P-value
That value is the median value
Type II errors
45. Var[X] :
categorical variables
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A Random vector
variance of X
46. Is data arising from counting that can take only non-negative integer values.
Count data
Block
hypotheses
Bias
47. Have no meaningful rank order among values.
Skewness
Mutual independence
Standard error
Nominal measurements
48. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Statistical inference
Sampling Distribution
A Distribution function
Random variables
49. 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.
Likert scale
A probability density function
Seasonal effect
A population or statistical population
50. Rejecting a true null hypothesis.
Type 1 Error
A population or statistical population
variance of X
observational study