# CLEP General Mathematics: Probability And Statistics

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. Long-term upward or downward movement over time.

2. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.

3. Data are gathered and correlations between predictors and response are investigated.

4. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.

5. 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

6. Rejecting a true null hypothesis.

7. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively

8. 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.

9. 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

10. Many statistical methods seek to minimize the mean-squared error - and these are called

11. Is a parameter that indexes a family of probability distributions.

12. The probability distribution of a sample statistic based on all the possible simple random samples of the same size from a population.

13. 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

14. Another name for elementary event.

15. Gives the probability distribution for a continuous random variable.

16. 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.

17. Describes a characteristic of an individual to be measured or observed.

18. 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.

19. Is its expected value. The mean (or sample mean of a data set is just the average value.

20. Working from a null hypothesis two basic forms of error are recognized:

21. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.

22. Some commonly used symbols for sample statistics

23. A measure that is relevant or appropriate as a representation of that property.

24. Is defined as the expected value of random variable (X -

25. (pdfs) and probability mass functions are denoted by lower case letters - e.g. f(x).

26. Is a subset of the sample space - to which a probability can be assigned. For example - on rolling a die - 'getting a five or a six' is an event (with a probability of one third if the die is fair).

27. A scale that represents an ordinal scale such as looks on a scale from 1 to 10.

28. S^2

29. Descriptive statistics and inferential statistics (a.k.a. - predictive statistics) together comprise

30. Error also refers to the extent to which individual observations in a sample differ from a central value - such as

31. 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'

32. A group of individuals sharing some common features that might affect the treatment.

33. 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

34. 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.

35. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).

36. Probability of accepting a false null hypothesis.

37. (or multivariate random variable) is a vector whose components are random variables on the same probability space.

38. A subjective estimate of probability.

39. Var[X] :

40. 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.

41. A variable describes an individual by placing the individual into a category or a group.

42. Is data that can take only two values - usually represented by 0 and 1.

43. 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

44. Statistical methods can be used for summarizing or describing a collection of data; this is called

45. 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.

46. Where the null hypothesis is falsely rejected giving a 'false positive'.

47. Is the most commonly used measure of statistical dispersion. It is the square root of the variance - and is generally written s (sigma).

48. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as

49. Gives the probability of events in a probability space.

50. There are four main levels of measurement used in statistics: Each of these have different degrees of usefulness in statistical research.