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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. The collection of all possible outcomes in an experiment.






2. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.






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






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






5. 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






6. 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






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. 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






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






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






11. 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.






12. 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.






13. 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.






14. Is denoted by - pronounced 'x bar'.






15. Probability of accepting a false null hypothesis.






16. A subjective estimate of probability.






17. (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.






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






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






20. Another name for elementary event.






21. 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.






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






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






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






25. Is used to describe probability in a continuous probability distribution. For example - you can't say that the probability of a man being six feet tall is 20% - but you can say he has 20% of chances of being between five and six feet tall. Probabilit






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






27. 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.






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






29. 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






30. Any specific experimental condition applied to the subjects






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






32. 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)






33. 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.






34. The standard deviation of a sampling distribution.






35. 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.






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






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






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






39. The proportion of the explained variation by a linear regression model in the total variation.






40. Interpretation of statistical information in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured can often involve the development of a






41. 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.






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






44. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






45. Var[X] :






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






47. Have no meaningful rank order among values.






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






49. Changes over time that show a regular periodicity in the data where regular means over a fixed interval; the time between repetitions is called the period.






50. Rejecting a true null hypothesis.