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






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






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






4. 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.






5. 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).






6. 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.






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






8. Some commonly used symbols for sample statistics






9. Where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a 'false negative'.






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






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






12. 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






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






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






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






16. 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






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






18. (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.






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






20. ?r






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






22. 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






23. 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.






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






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






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






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. Where the null hypothesis is falsely rejected giving a 'false positive'.






29. Failing to reject a false null hypothesis.






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






31. (also called statistical variability) is a measure of how diverse some data is. It can be expressed by the variance or the standard deviation.






32. 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}.






33. (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






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






35. 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)






36. Some commonly used symbols for population parameters






37. 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






38. A measurement such that the random error is small






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






40. Working from a null hypothesis two basic forms of error are recognized:






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






42. (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






43. 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






44. 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.






45. To find the average - or arithmetic mean - of a set of numbers:






46. To prove the guiding theory further - these predictions are tested as well - as part of the scientific method. If the inference holds true - then the descriptive statistics of the new data increase the soundness of that






47. 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






48. Cov[X - Y] :






49. Is data that can take only two values - usually represented by 0 and 1.






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