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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. 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.






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






3. Probability of rejecting a true null hypothesis.






4. Some commonly used symbols for population parameters






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






6. To find the average - or arithmetic mean - of a set of numbers:






7. 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.






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






9. In number theory - scatter plots of data generated by a distribution function may be transformed with familiar tools used in statistics to reveal underlying patterns - which may then lead to






10. A numerical measure that describes an aspect of a sample.






11. 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






12. Probability of accepting a false null hypothesis.






13. 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.






14. E[X] :






15. (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






16. Is a sample and the associated data points.






17. The standard deviation of a sampling distribution.






18. 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






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






20. Is data arising from counting that can take only non-negative integer values.






21. 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






22. 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.

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23. 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.






24. Are simply two different terms for the same thing. Add the given values






25. Is a typed measurement - it can be a boolean value - a real number - a vector (in which case it's also called a data vector) - etc.






26. Is the probability distribution - under repeated sampling of the population - of a given statistic.






27. Another name for elementary event.






28. Is a sample space over which a probability measure has been defined.






29. Statistics involve methods of using information from a sample to draw conclusions regarding the population.






30. Any specific experimental condition applied to the subjects






31. 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






32. 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.






33. 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






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






35. ?r






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






37. A numerical facsimilie or representation of a real-world phenomenon.






38. Two variables such that their effects on the response variable cannot be distinguished from each other.






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






40. When there is an even number of values...






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






42. In particular - the pdf of the standard normal distribution is denoted by






43. 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.






44. Long-term upward or downward movement over time.






45. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are






46. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






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






48. Is a function that gives the probability of all elements in a given space: see List of probability distributions






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






50. 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}.