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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. 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.






2. When you have two or more competing models - choose the simpler of the two models.






3. The probability of correctly detecting a false null hypothesis.






4. A measurement such that the random error is small






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






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






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






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






9. 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.






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






11.






12. E[X] :






13. 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.






14. ?r






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






16. Var[X] :






17. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






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 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






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






21. Probability of rejecting a true null hypothesis.






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






23. 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






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






25. Have no meaningful rank order among values.






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






27. (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






28. 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.






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






30. A data value that falls outside the overall pattern of the graph.






31. 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






32. Are usually written in upper case roman letters: X - Y - etc.






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






34. Is the length of the smallest interval which contains all the data.






35. (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.






36. Cov[X - Y] :






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






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






39. 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.






40. Ratio and interval measurements which can be either discrete or continuous - due to their numerical nature are grouped together as






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






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






43. (cdfs) are denoted by upper case letters - e.g. F(x).






44. 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'






45. 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






46. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






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






48. Of a group of numbers is the center point of all those number values.






49. (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






50. S^2