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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
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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. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Skewness
P-value
Probability density functions
Descriptive statistics
2. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Binomial experiment
Skewness
A likelihood function
An estimate of a parameter
3. A variable describes an individual by placing the individual into a category or a group.
methods of least squares
Inferential statistics
A statistic
Qualitative variable
4. Is denoted by - pronounced 'x bar'.
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
Divide the sum by the number of values.
Inferential statistics
A Random vector
5. 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}.
The variance of a random variable
The sample space
Type 1 Error
Interval measurements
6. A pairwise independent collection of random variables is a set of random variables any two of which are independent.
Treatment
Pairwise independence
Average and arithmetic mean
A probability distribution
7. Long-term upward or downward movement over time.
An experimental study
The Expected value
Trend
Bias
8. A numerical measure that assesses the strength of a linear relationship between two variables.
Treatment
Mutual independence
quantitative variables
Correlation coefficient
9. 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.
Atomic event
The median value
Binary data
Skewness
10. A data value that falls outside the overall pattern of the graph.
Step 3 of a statistical experiment
Outlier
A sampling distribution
Type 1 Error
11. 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.
An experimental study
applied statistics
Probability density functions
Coefficient of determination
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.
observational study
Type 2 Error
Law of Large Numbers
A population or statistical population
13. When you have two or more competing models - choose the simpler of the two models.
categorical variables
Mutual independence
Likert scale
Law of Parsimony
14. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.
the population mean
Statistical dispersion
A probability distribution
The sample space
15. Is the probability distribution - under repeated sampling of the population - of a given statistic.
Statistic
Posterior probability
A sampling distribution
Placebo effect
16. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.
Individual
Bias
Particular realizations of a random variable
quantitative variables
17. ?
the population correlation
nominal - ordinal - interval - and ratio
A probability distribution
Probability
18. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
Likert scale
nominal - ordinal - interval - and ratio
s-algebras
A statistic
19. 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
The Covariance between two random variables X and Y - with expected values E(X) =
Individual
Probability density
Statistical dispersion
20. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.
Parameter - or 'statistical parameter'
Parameter
A Random vector
An estimate of a parameter
21. Statistics involve methods of using information from a sample to draw conclusions regarding the population.
applied statistics
Null hypothesis
the population variance
Inferential
22. Describes the spread in the values of the sample statistic when many samples are taken.
Qualitative variable
Skewness
Variability
Valid measure
23. A list of individuals from which the sample is actually selected.
Sampling frame
Ordinal measurements
Null hypothesis
covariance of X and Y
24. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.
Statistics
Inferential
A statistic
Experimental and observational studies
25. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).
Probability density
Greek letters
Statistical inference
Kurtosis
26. 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
Simpson's Paradox
descriptive statistics
Dependent Selection
27. 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.
Valid measure
Inferential
inferential statistics
Marginal distribution
28. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as
Bias
Type 2 Error
quantitative variables
Confounded variables
29. A group of individuals sharing some common features that might affect the treatment.
nominal - ordinal - interval - and ratio
Independent Selection
Placebo effect
Block
30. To find the average - or arithmetic mean - of a set of numbers:
Greek letters
The Mean of a random variable
Divide the sum by the number of values.
Ordinal measurements
31. 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).
The average - or arithmetic mean
Block
Null hypothesis
Joint probability
32. Some commonly used symbols for sample statistics
Statistic
P-value
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Inferential
33. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.
Step 3 of a statistical experiment
Type 2 Error
the population mean
Descriptive
34. 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
Bias
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
Mutual independence
35. 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
Statistical adjustment
Interval measurements
Reliable measure
36. Patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations - and are then used for drawing inferences about the process or population being studied; this is called
inferential statistics
Statistics
Prior probability
A Distribution function
37. The proportion of the explained variation by a linear regression model in the total variation.
Sampling Distribution
A likelihood function
Coefficient of determination
Experimental and observational studies
38. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co
Alpha value (Level of Significance)
covariance of X and Y
inferential statistics
Step 1 of a statistical experiment
39. 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.
A probability distribution
the population correlation
Seasonal effect
Posterior probability
40. E[X] :
Law of Large Numbers
hypothesis
A population or statistical population
expected value of X
41. 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.
A probability distribution
Variability
Correlation
Conditional distribution
42. 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
A random variable
An estimate of a parameter
Parameter
Null hypothesis
43. 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
Statistical inference
Skewness
Probability
A data point
44. The standard deviation of a sampling distribution.
Statistical inference
Standard error
P-value
Observational study
45. 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
A Random vector
Variability
Inferential statistics
A population or statistical population
46. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.
An estimate of a parameter
Block
A random variable
Quantitative variable
47. Is a sample space over which a probability measure has been defined.
Type 1 Error
Statistical inference
A probability space
Divide the sum by the number of values.
48. Any specific experimental condition applied to the subjects
Power of a test
Beta value
Correlation
Treatment
49. Describes a characteristic of an individual to be measured or observed.
Bias
Variable
A sampling distribution
A probability distribution
50. 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
A Distribution function
s-algebras
Observational study
Experimental and observational studies