SUBJECTS
|
BROWSE
|
CAREER CENTER
|
POPULAR
|
JOIN
|
LOGIN
Business Skills
|
Soft Skills
|
Basic Literacy
|
Certifications
About
|
Help
|
Privacy
|
Terms
|
Email
Search
Test your basic knowledge |
CLEP General Mathematics: Probability And Statistics
Start Test
Study First
Subjects
:
clep
,
math
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
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 defined as the expected value of random variable (X -
Simple random sample
Conditional probability
The Covariance between two random variables X and Y - with expected values E(X) =
s-algebras
2. The standard deviation of a sampling distribution.
Interval measurements
Atomic event
Standard error
the population mean
3. S^2
The median value
Law of Large Numbers
Quantitative variable
the population variance
4. 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.
The Mean of a random variable
hypotheses
Likert scale
A population or statistical population
5. Is that part of a population which is actually observed.
the sample or population mean
Atomic event
A sample
Trend
6. Another name for elementary event.
experimental studies and observational studies.
The standard deviation
Sampling frame
Atomic event
7. Is a function that gives the probability of all elements in a given space: see List of probability distributions
Descriptive statistics
Inferential statistics
A probability distribution
Inferential
8. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.
Credence
P-value
hypotheses
A probability space
9. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.
experimental studies and observational studies.
Dependent Selection
Block
Prior probability
10. Is a sample and the associated data points.
Inferential
the population mean
A data set
Reliable measure
11. 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
Statistical dispersion
Skewness
P-value
Marginal probability
12. Working from a null hypothesis two basic forms of error are recognized:
A statistic
Type I errors & Type II errors
Statistical dispersion
Individual
13. 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.
Type I errors & Type II errors
Experimental and observational studies
Atomic event
hypotheses
14. A numerical facsimilie or representation of a real-world phenomenon.
Bias
Ordinal measurements
Simulation
f(z) - and its cdf by F(z).
15. 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.
the sample or population mean
The Covariance between two random variables X and Y - with expected values E(X) =
Probability density
Simple random sample
16. Var[X] :
expected value of X
Parameter - or 'statistical parameter'
variance of X
Pairwise independence
17. 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.
Warning
: Invalid argument supplied for foreach() in
/var/www/html/basicversity.com/show_quiz.php
on line
183
18. (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
Type I errors & Type II errors
The Expected value
Inferential statistics
Law of Large Numbers
19. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)
Individual
expected value of X
Correlation
Prior probability
20. 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.
Variable
Bias
The Mean of a random variable
A population or statistical population
21. 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.
Probability
Dependent Selection
Prior probability
Statistical inference
22. Is a sample space over which a probability measure has been defined.
Sampling Distribution
Quantitative variable
A probability space
observational study
23. 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
Confounded variables
applied statistics
Alpha value (Level of Significance)
24. 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
That is the median value
Nominal measurements
Step 2 of a statistical experiment
inferential statistics
25. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.
The Mean of a random variable
Likert scale
Pairwise independence
hypothesis
26. 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
the sample or population mean
Null hypothesis
The Range
27. Many statistical methods seek to minimize the mean-squared error - and these are called
Sample space
Type 1 Error
methods of least squares
Joint probability
28. A numerical measure that assesses the strength of a linear relationship between two variables.
Bias
Correlation coefficient
Pairwise independence
Coefficient of determination
29. Failing to reject a false null hypothesis.
applied statistics
Type 2 Error
experimental studies and observational studies.
Count data
30. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as
Marginal probability
The Expected value
categorical variables
The average - or arithmetic mean
31. A measurement such that the random error is small
the population cumulants
Reliable measure
The variance of a random variable
An estimate of a parameter
32. In particular - the pdf of the standard normal distribution is denoted by
f(z) - and its cdf by F(z).
Nominal measurements
Statistical inference
Correlation
33. Describes the spread in the values of the sample statistic when many samples are taken.
Variability
Beta value
Independence or Statistical independence
Estimator
34. 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
experimental studies and observational studies.
Alpha value (Level of Significance)
The arithmetic mean of a set of numbers x1 - x2 - ... - xn
the population mean
35. A data value that falls outside the overall pattern of the graph.
Statistic
A sampling distribution
Posterior probability
Outlier
36. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)
Reliable measure
Parameter
s-algebras
A Statistical parameter
37. 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.
Lurking variable
Descriptive statistics
An experimental study
A probability density function
38. A variable describes an individual by placing the individual into a category or a group.
The variance of a random variable
Sampling
A statistic
Qualitative variable
39. Of a group of numbers is the center point of all those number values.
An Elementary event
Type I errors
The average - or arithmetic mean
Probability
40. 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.
The Mean of a random variable
The variance of a random variable
Greek letters
the sample mean - the sample variance s2 - the sample correlation coefficient r - the sample cumulants kr.
41. Statistical methods can be used for summarizing or describing a collection of data; this is called
A population or statistical population
descriptive statistics
Estimator
A Random vector
42. Some commonly used symbols for population parameters
A Random vector
Quantitative variable
the population mean
Conditional distribution
43. Can be - for example - the possible outcomes of a dice roll (but it is not assigned a value). The distribution function of a random variable gives the probability of different results. We can also derive the mean and variance of a random variable.
Joint distribution
A random variable
expected value of X
Observational study
44. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.
Inferential statistics
Marginal distribution
Binomial experiment
Observational study
45. ?r
Interval measurements
Binomial experiment
An Elementary event
the population cumulants
46. The probability of correctly detecting a false null hypothesis.
Atomic event
Power of a test
Placebo effect
Type I errors & Type II errors
47. ?
the population mean
A data set
the population correlation
Sample space
48. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.
Statistical inference
The variance of a random variable
Bias
Probability density functions
49. 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
applied statistics
Step 1 of a statistical experiment
the sample or population mean
experimental studies and observational studies.
50. A group of individuals sharing some common features that might affect the treatment.
Atomic event
Experimental and observational studies
Block
Individual