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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
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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 group of individuals sharing some common features that might affect the treatment.
Variable
A statistic
Block
The standard deviation
2. A list of individuals from which the sample is actually selected.
Sampling frame
The standard deviation
Quantitative variable
A Random vector
3. 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.
Parameter
Simple random sample
Mutual independence
expected value of X
4. The standard deviation of a sampling distribution.
Type II errors
Standard error
Seasonal effect
A probability space
5. 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.
Sampling frame
Marginal probability
Type 1 Error
That value is the median value
6. 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.
Conditional probability
A Distribution function
The median value
Random variables
7. To find the average - or arithmetic mean - of a set of numbers:
A Distribution function
Divide the sum by the number of values.
observational study
Parameter
8. Are simply two different terms for the same thing. Add the given values
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
That is the median value
The Range
Average and arithmetic mean
9. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a
Type 2 Error
Conditional distribution
Step 2 of a statistical experiment
The standard deviation
10. Is its expected value. The mean (or sample mean of a data set is just the average value.
Block
The Mean of a random variable
A sample
Joint distribution
11. 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
s-algebras
the sample or population mean
Descriptive statistics
A likelihood function
12. Are usually written in upper case roman letters: X - Y - etc.
Random variables
Confounded variables
Probability and statistics
A probability density function
13. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.
Placebo effect
Parameter - or 'statistical parameter'
Confounded variables
Type II errors
14. Is the length of the smallest interval which contains all the data.
The Range
Simpson's Paradox
Standard error
experimental studies and observational studies.
15. Data are gathered and correlations between predictors and response are investigated.
the population mean
the population correlation
Atomic event
observational study
16. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Estimator
Statistical dispersion
observational study
Outlier
17. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Statistic
the population correlation
Cumulative distribution functions
An estimate of a parameter
18. S^2
the population variance
Bias
Variability
Correlation
19. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Experimental and observational studies
Prior probability
P-value
A Statistical parameter
20. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
observational study
Qualitative variable
descriptive statistics
applied statistics
21. Rejecting a true null hypothesis.
expected value of X
The average - or arithmetic mean
Type 1 Error
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
22. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.
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23. E[X] :
expected value of X
A Random vector
Atomic event
A data point
24. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
expected value of X
An estimate of a parameter
covariance of X and Y
Statistical adjustment
25. 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
Step 2 of a statistical experiment
Conditional probability
Parameter
26. 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
Probability
Trend
A probability distribution
That is the median value
27. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
Prior probability
Confounded variables
Average and arithmetic mean
A Random vector
28. 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.
The standard deviation
The sample space
Conditional distribution
Marginal distribution
29. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Sample space
quantitative variables
Statistics
Atomic event
30. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present
Joint probability
Step 2 of a statistical experiment
Step 3 of a statistical experiment
variance of X
31. Probability of rejecting a true null hypothesis.
experimental studies and observational studies.
Alpha value (Level of Significance)
A Distribution function
Prior probability
32. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Particular realizations of a random variable
Ordinal measurements
Coefficient of determination
Variability
33. Is a function that gives the probability of all elements in a given space: see List of probability distributions
A probability distribution
Independence or Statistical independence
Simulation
Variable
34. 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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35. A data value that falls outside the overall pattern of the graph.
Sampling Distribution
Outlier
A random variable
categorical variables
36. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl
Bias
Mutual independence
Bias
Placebo effect
37. Gives the probability of events in a probability space.
A Probability measure
Experimental and observational studies
inferential statistics
Ordinal measurements
38. 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
Divide the sum by the number of values.
Valid measure
An experimental study
39. 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.
categorical variables
A population or statistical population
Pairwise independence
Probability density
40. A common goal for a statistical research project is to investigate causality - and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response.
Statistics
Independence or Statistical independence
Power of a test
Experimental and observational studies
41. Var[X] :
Conditional distribution
Parameter - or 'statistical parameter'
Probability density functions
variance of X
42. Many statistical methods seek to minimize the mean-squared error - and these are called
Binary data
Independence or Statistical independence
methods of least squares
Block
43. A numerical measure that assesses the strength of a linear relationship between two variables.
Correlation coefficient
Bias
Type 1 Error
Beta value
44. 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.
the population cumulants
Statistical inference
Valid measure
The Range
45. 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
Skewness
the population mean
A sample
The Expected value
46. Probability of accepting a false null hypothesis.
Kurtosis
Beta value
quantitative variables
Variable
47. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.
Ordinal measurements
The Mean of a random variable
An experimental study
An event
48. Two variables such that their effects on the response variable cannot be distinguished from each other.
Law of Large Numbers
Valid measure
An event
Confounded variables
49.
Bias
Greek letters
the population mean
The standard deviation
50. The proportion of the explained variation by a linear regression model in the total variation.
Coefficient of determination
Descriptive
Observational study
Placebo effect