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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. 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






2. 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






3. 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






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






5. 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






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






7. 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).






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






9. 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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10. 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.






11.






12. 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.






13. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






14. Have no meaningful rank order among values.






15. Occurs when a subject receives no treatment - but (incorrectly) believes he or she is in fact receiving treatment and responds favorably.






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






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






18. ?r






19. 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).






20. The standard deviation of a sampling distribution.






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






22. 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.






23. 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.






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






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






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






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






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






29. Is a sample and the associated data points.






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






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






32. 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.






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






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






35. 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.






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






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






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






40. 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)






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. 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






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






44. Failing to reject a false null hypothesis.






45. 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.






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






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






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






49. ?






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