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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. 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
Step 2 of a statistical experiment
Type 2 Error
Trend
Step 1 of a statistical experiment
2. Some commonly used symbols for population parameters
the population mean
Trend
categorical variables
Step 2 of a statistical experiment
3. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Trend
Seasonal effect
categorical variables
Variability
4. 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.
That is the median value
Probability and statistics
Sample space
The median value
5. 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.
Ordinal measurements
A sample
Parameter - or 'statistical parameter'
Experimental and observational studies
6. A numerical measure that describes an aspect of a population.
The standard deviation
Joint probability
Parameter
Credence
7. 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
Correlation
Type 2 Error
the population correlation
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
8. Probability of rejecting a true null hypothesis.
The average - or arithmetic mean
Alpha value (Level of Significance)
Probability density functions
Confounded variables
9. Is its expected value. The mean (or sample mean of a data set is just the average value.
Experimental and observational studies
Reliable measure
An estimate of a parameter
The Mean of a random variable
10. (or expectation) of a random variable is the sum of the probability of each possible outcome of the experiment multiplied by its payoff ('value'). Thus - it represents the average amount one 'expects' to win per bet if bets with identical odds are re
The Expected value
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Law of Parsimony
Step 3 of a statistical experiment
11. 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
A random variable
Probability and statistics
Joint distribution
the population mean
12. 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
The median value
nominal - ordinal - interval - and ratio
Standard error
13. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
methods of least squares
The median value
Block
quantitative variables
14. 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
Sampling Distribution
The median value
Inferential statistics
descriptive statistics
15. 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.
Conditional distribution
Count data
Pairwise independence
Estimator
16. Another name for elementary event.
An estimate of a parameter
Confounded variables
Greek letters
Atomic event
17. In particular - the pdf of the standard normal distribution is denoted by
the population variance
The sample space
f(z) - and its cdf by F(z).
A probability space
18. Statistical methods can be used for summarizing or describing a collection of data; this is called
Atomic event
The sample space
Step 2 of a statistical experiment
descriptive statistics
19. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.
Outlier
Residuals
Joint distribution
nominal - ordinal - interval - and ratio
20. Var[X] :
Quantitative variable
variance of X
A probability distribution
the sample or population mean
21. Are usually written in upper case roman letters: X - Y - etc.
Random variables
Qualitative variable
A Random vector
Simpson's Paradox
22. Is data that can take only two values - usually represented by 0 and 1.
Divide the sum by the number of values.
Power of a test
Simulation
Binary data
23. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Statistical adjustment
the population mean
nominal - ordinal - interval - and ratio
experimental studies and observational studies.
24. S^2
Law of Parsimony
the population variance
Probability density
That is the median value
25. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Independence or Statistical independence
Statistics
Likert scale
Sampling Distribution
26. When there is an even number of values...
That is the median value
Dependent Selection
Observational study
Alpha value (Level of Significance)
27. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise
Marginal distribution
applied statistics
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Simple random sample
28. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Variable
Simulation
Law of Large Numbers
Outlier
29. Gives the probability distribution for a continuous random variable.
Trend
Binary data
The standard deviation
A probability density function
30. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that
Marginal distribution
hypothesis
methods of least squares
Probability density functions
31. Failing to reject a false null hypothesis.
Type 2 Error
Step 3 of a statistical experiment
Law of Parsimony
A random variable
32. Is a parameter that indexes a family of probability distributions.
Average and arithmetic mean
Statistical adjustment
the population variance
A Statistical parameter
33. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).
Experimental and observational studies
A Probability measure
Probability density functions
An Elementary event
34. Long-term upward or downward movement over time.
Binomial experiment
Type 2 Error
Trend
categorical variables
35. Some commonly used symbols for sample statistics
Sampling Distribution
Coefficient of determination
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
A data point
36. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Individual
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
A Random vector
A population or statistical population
37. Is denoted by - pronounced 'x bar'.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
A likelihood function
expected value of X
the population mean
38. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data
the population correlation
Posterior probability
A Distribution function
Pairwise independence
39. 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
Sampling frame
Simple random sample
Skewness
Ratio measurements
40. Gives the probability of events in a probability space.
A sample
Atomic event
A Probability measure
hypotheses
41. A measure that is relevant or appropriate as a representation of that property.
Prior probability
Valid measure
The sample space
Count data
42. The proportion of the explained variation by a linear regression model in the total variation.
Placebo effect
Count data
Coefficient of determination
expected value of X
43. 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.
That value is the median value
methods of least squares
Dependent Selection
hypothesis
44. 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.
A data point
Descriptive statistics
Residuals
Independent Selection
45. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.
Marginal distribution
Probability density functions
Inferential statistics
the population variance
46. A numerical measure that assesses the strength of a linear relationship between two variables.
An Elementary event
Statistical inference
Variable
Correlation coefficient
47. Are simply two different terms for the same thing. Add the given values
Trend
Average and arithmetic mean
Variable
covariance of X and Y
48. A variable describes an individual by placing the individual into a category or a group.
Average and arithmetic mean
Qualitative variable
categorical variables
Sampling Distribution
49. Rejecting a true null hypothesis.
Probability
Type 1 Error
Sampling frame
A sampling distribution
50. A data value that falls outside the overall pattern of the graph.
Statistical adjustment
Standard error
Kurtosis
Outlier