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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
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. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).
The standard deviation
Simulation
The Covariance between two random variables X and Y - with expected values E(X) =
Step 3 of a statistical experiment
2. 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
Probability density
the population mean
Prior probability
A Probability measure
3. A list of individuals from which the sample is actually selected.
Statistic
Sampling frame
categorical variables
Binary data
4. Failing to reject a false null hypothesis.
Experimental and observational studies
Random variables
Type 2 Error
A likelihood function
5. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
Particular realizations of a random variable
experimental studies and observational studies.
Variability
Quantitative variable
6. 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
Simpson's Paradox
Step 1 of a statistical experiment
P-value
Step 3 of a statistical experiment
7. Working from a null hypothesis two basic forms of error are recognized:
nominal - ordinal - interval - and ratio
Step 3 of a statistical experiment
Statistic
Type I errors & Type II errors
8. 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.
A Distribution function
Descriptive statistics
expected value of X
Nominal measurements
9. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
A data point
Simple random sample
Statistical adjustment
applied statistics
10. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.
The standard deviation
Simpson's Paradox
Dependent Selection
A probability density function
11. 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
The median value
Step 1 of a statistical experiment
quantitative variables
Ratio measurements
12. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.
Inferential statistics
the population cumulants
Law of Large Numbers
Binary data
13. 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.
quantitative variables
Observational study
Lurking variable
Prior probability
14. Is a sample space over which a probability measure has been defined.
The median value
Divide the sum by the number of values.
A probability space
Statistical inference
15. A measure that is relevant or appropriate as a representation of that property.
Skewness
Valid measure
experimental studies and observational studies.
Joint distribution
16. ?
nominal - ordinal - interval - and ratio
The Expected value
the population correlation
A sampling distribution
17. Any specific experimental condition applied to the subjects
Null hypothesis
Step 3 of a statistical experiment
A Statistical parameter
Treatment
18. 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
the population cumulants
variance of X
the sample or population mean
19. Are simply two different terms for the same thing. Add the given values
the population variance
Outlier
Qualitative variable
Average and arithmetic mean
20. The collection of all possible outcomes in an experiment.
Sample space
The Expected value
Probability density functions
Conditional distribution
21. To find the average - or arithmetic mean - of a set of numbers:
Variable
Type 2 Error
Binomial experiment
Divide the sum by the number of values.
22. E[X] :
Independent Selection
Bias
expected value of X
f(z) - and its cdf by F(z).
23. Probability of accepting a false null hypothesis.
Statistics
Outlier
Beta value
Atomic event
24. (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
Sampling Distribution
A likelihood function
The Range
A probability distribution
25. 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)
Independence or Statistical independence
Law of Large Numbers
A probability distribution
Interval measurements
26. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively
Residuals
A probability distribution
Inferential
Variable
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.
descriptive statistics
Probability and statistics
Simple random sample
Simpson's Paradox
28. A numerical measure that assesses the strength of a linear relationship between two variables.
observational study
Correlation coefficient
Experimental and observational studies
variance of X
29. The proportion of the explained variation by a linear regression model in the total variation.
Coefficient of determination
the sample or population mean
expected value of X
Sampling Distribution
30. Two variables such that their effects on the response variable cannot be distinguished from each other.
Law of Large Numbers
Mutual independence
Variable
Confounded variables
31. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Qualitative variable
Bias
Simpson's Paradox
Step 1 of a statistical experiment
32. 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
A data point
Lurking variable
The Covariance between two random variables X and Y - with expected values E(X) =
Probability
33. Of a group of numbers is the center point of all those number values.
applied statistics
Probability density functions
The average - or arithmetic mean
Descriptive statistics
34. Gives the probability distribution for a continuous random variable.
Random variables
A probability density function
Quantitative variable
Statistics
35. Is a parameter that indexes a family of probability distributions.
observational study
Kurtosis
A Statistical parameter
That is the median value
36. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'
Conditional probability
Null hypothesis
Mutual independence
Prior probability
37. 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.
descriptive statistics
Bias
nominal - ordinal - interval - and ratio
the population mean
38. 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.
Law of Large Numbers
hypothesis
the population mean
That value is the median value
39. Cov[X - Y] :
the population correlation
Valid measure
covariance of X and Y
Bias
40. Probability of rejecting a true null hypothesis.
Parameter - or 'statistical parameter'
f(z) - and its cdf by F(z).
hypothesis
Alpha value (Level of Significance)
41. 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.
experimental studies and observational studies.
The median value
Sampling Distribution
The standard deviation
42. Another name for elementary event.
the sample or population mean
Atomic event
The average - or arithmetic mean
Lurking variable
43. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Placebo effect
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
That value is the median value
Likert scale
44. A subjective estimate of probability.
Credence
An Elementary event
Qualitative variable
covariance of X and Y
45. Error also refers to the extent to which individual observations in a sample differ from a central value - such as
the sample or population mean
categorical variables
Probability density functions
Divide the sum by the number of values.
46. There are two major types of causal statistical studies: In both types of studies - the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies
Block
Average and arithmetic mean
Marginal probability
experimental studies and observational studies.
47. Is the probability distribution - under repeated sampling of the population - of a given statistic.
A Statistical parameter
inferential statistics
A sampling distribution
the population mean
48. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.
Parameter
Trend
Type II errors
Inferential statistics
49. 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.
Pairwise independence
Correlation
Experimental and observational studies
Variability
50. A group of individuals sharing some common features that might affect the treatment.
Divide the sum by the number of values.
Standard error
Block
Estimator