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CLEP General Mathematics: Probability And Statistics

Subjects : clep, math
Instructions:
  • Answer 50 questions in 15 minutes.
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  • 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. To find the average - or arithmetic mean - of a set of numbers:






2. Samples are drawn from two different populations such that there is a matching of the first sample data drawn and a corresponding data value in the second sample data.






3. A variable that has an important effect on the response variable and the relationship among the variables in a study but is not one of the explanatory variables studied either because it is unknown or not measured.






4. 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.






5. A measurement such that the random error is small






6. 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)






7. Probability of accepting a false null hypothesis.






8. 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






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






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






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






13. Have imprecise differences between consecutive values - but have a meaningful order to those values






14. (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.






15. Rejecting a true null hypothesis.






16. 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).






17. Any specific experimental condition applied to the subjects






18. ?r






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






20. When info. in a contingency table is re-organized into more or less categories - relationships seen can change or reverse.

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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. 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}.






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






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






25. Is the probability of two events occurring together. The joint probability of A and B is written P(A and B) or P(A - B).






26. 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.






27. Is that part of a population which is actually observed.






28. 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.






29. Used to reduce bias - this measure weights the more relevant information higher than less relevant info.






30. 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.






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






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






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






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






36. 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.






37. (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






38. E[X] :






39.






40. 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.






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






42. Some commonly used symbols for population parameters






43. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






44. 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.






45. 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






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






47. Can refer either to a sample not being representative of the population - or to the difference between the expected value of an estimator and the true value.






48. Have no meaningful rank order among values.






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






50. ?