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






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






3. Have no meaningful rank order among values.






4. Is the probability of an event - ignoring any information about other events. The marginal probability of A is written P(A). Contrast with conditional probability.






5. A collection of events is mutually independent if for any subset of the collection - the joint probability of all events occurring is equal to the product of the joint probabilities of the individual events. Think of the result of a series of coin-fl






6. The result of a Bayesian analysis that encapsulates the combination of prior beliefs or information with observed data






7. The objects described by a set of data: person (animal) - place - and - thing. (SUBJECTS)






8. 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






9. 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.






10. A numerical measure that assesses the strength of a linear relationship between two variables.






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






12. Consists of a number of independent trials repeated under identical conditions. On each trial - there are two possible outcomes.






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






14. Some commonly used symbols for population parameters






15. Another name for elementary event.






16. Have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data






17. 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)






18. 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.






19.






20. 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






21. 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






22. 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






23. 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.






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






25. A list of individuals from which the sample is actually selected.






26. Is the function that gives the probability distribution of a random variable. It cannot be negative - and its integral on the probability space is equal to 1.






27. 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






28. 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






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






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






31. Is a sample and the associated data points.






32. ?r






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






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






35. 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.






36. 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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37. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.






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






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






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






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






42. 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.






43. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.






44. Given two random variables X and Y - the joint distribution of X and Y is the probability distribution of X and Y together.






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






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






47. Are written in corresponding lower case letters. For example x1 - x2 - ... - xn could be a sample corresponding to the random variable X.






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






49. A pairwise independent collection of random variables is a set of random variables any two of which are independent.






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