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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.
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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. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Observational study
f(z) - and its cdf by F(z).
Particular realizations of a random variable
Greek letters
2. Is the set of possible outcomes of an experiment. For example - the sample space for rolling a six-sided die will be {1 - 2 - 3 - 4 - 5 - 6}.
Average and arithmetic mean
observational study
The sample space
Parameter - or 'statistical parameter'
3. 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
Simple random sample
Beta value
Sampling
Step 2 of a statistical experiment
4. A list of individuals from which the sample is actually selected.
Binary data
The Range
Sampling frame
Kurtosis
5. Is a sample and the associated data points.
observational study
A data set
A statistic
Step 2 of a statistical experiment
6. Are usually written in upper case roman letters: X - Y - etc.
Parameter - or 'statistical parameter'
An Elementary event
A sampling distribution
Random variables
7. 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.
A data point
Valid measure
Nominal measurements
Statistics
8. Is data that can take only two values - usually represented by 0 and 1.
Skewness
Binary data
A Statistical parameter
Probability and statistics
9. 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
inferential statistics
Ratio measurements
Kurtosis
Step 3 of a statistical experiment
10. A measure that is relevant or appropriate as a representation of that property.
nominal - ordinal - interval - and ratio
Valid measure
Interval measurements
Probability
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.
A random variable
The variance of a random variable
Probability and statistics
Sampling frame
12. Gives the probability of events in a probability space.
the population mean
Qualitative variable
Variable
A Probability measure
13. 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.
Individual
Sampling
the population mean
Block
14. ?r
Beta value
Treatment
An event
the population cumulants
15. Some commonly used symbols for sample statistics
Step 3 of a statistical experiment
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Quantitative variable
Independent Selection
16. Is a parameter that indexes a family of probability distributions.
Type 2 Error
A Statistical parameter
Binomial experiment
Joint distribution
17. Working from a null hypothesis two basic forms of error are recognized:
Type I errors & Type II errors
Statistical dispersion
Sampling Distribution
Cumulative distribution functions
18. 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
hypothesis
Correlation
Statistical adjustment
Correlation coefficient
19. Is the length of the smallest interval which contains all the data.
P-value
An Elementary event
The Range
The average - or arithmetic mean
20. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.
Ratio measurements
A Distribution function
Statistical adjustment
the population variance
21. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
Statistical dispersion
Random variables
Atomic event
Credence
22. Another name for elementary event.
Atomic event
Descriptive statistics
Inferential
Type 1 Error
23. The standard deviation of a sampling distribution.
Step 2 of a statistical experiment
Standard error
Treatment
Bias
24. Have no meaningful rank order among values.
quantitative variables
An Elementary event
Nominal measurements
Probability
25. 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.
Sampling Distribution
Parameter - or 'statistical parameter'
the population mean
Conditional distribution
26. 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
Sampling frame
Type I errors
Type 2 Error
Observational study
27. 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
Confounded variables
A statistic
Probability density
Atomic event
28. 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.
Sampling frame
methods of least squares
Dependent Selection
An experimental study
29. (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
Ordinal measurements
Type I errors
nominal - ordinal - interval - and ratio
A likelihood function
30. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
Inferential
Placebo effect
Observational study
Sampling frame
31. 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.
An event
A population or statistical population
the population mean
methods of least squares
32. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i
Independence or Statistical independence
Probability
Cumulative distribution functions
Conditional distribution
33. Failing to reject a false null hypothesis.
Estimator
Ordinal measurements
Type 2 Error
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
34. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
The standard deviation
Step 1 of a statistical experiment
Likert scale
Type II errors
35. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
A population or statistical population
An experimental study
P-value
Atomic event
36. Var[X] :
Ordinal measurements
Divide the sum by the number of values.
variance of X
quantitative variables
37. 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
descriptive statistics
Skewness
Null hypothesis
A Statistical parameter
38. Data are gathered and correlations between predictors and response are investigated.
Pairwise independence
Dependent Selection
Quantitative variable
observational study
39. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).
A data set
An experimental study
Joint probability
methods of least squares
40. Is a function that gives the probability of all elements in a given space: see List of probability distributions
A probability distribution
A population or statistical population
The average - or arithmetic mean
The median value
41. ?
Bias
the population correlation
s-algebras
Statistical inference
42.
the sample or population mean
Coefficient of determination
A Random vector
the population mean
43. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.
Beta value
hypothesis
Sampling Distribution
Marginal distribution
44. Describes the spread in the values of the sample statistic when many samples are taken.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Type 1 Error
Variability
Block
45. 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 likelihood function
A population or statistical population
A data set
Probability and statistics
46. 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
An estimate of a parameter
Inferential statistics
A Probability measure
Dependent Selection
47. Any specific experimental condition applied to the subjects
Treatment
Atomic event
Independent Selection
Type 2 Error
48. 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
Nominal measurements
Divide the sum by the number of values.
The variance of a random variable
49. Of a group of numbers is the center point of all those number values.
The average - or arithmetic mean
The sample space
Null hypothesis
Joint distribution
50. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Ordinal measurements
Individual
Variable
Block