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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.
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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 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}.






2. Any specific experimental condition applied to the subjects






3. 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).






4. 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.






5. 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)






6. 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






7. Statistics involve methods of using information from a sample to draw conclusions regarding the population.






8. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






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






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






11. Another name for elementary event.






12. A consistent - repeated deviation of the sample statistic from the population parameter in the same direction when many samples are taken.






13. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






14. 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.






15. Describes the spread in the values of the sample statistic when many samples are taken.






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






17. 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.






18. 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






19. 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.






20. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. 4. Further examining the data set in secondary analyses - to suggest new hypotheses for future study. 5. Documenting and present






21. 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.






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






23. 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






24. 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






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






26. 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.






27. 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






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






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






30. A measurement such that the random error is small






31. 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






32. 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






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






34. 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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35. The probability of correctly detecting a false null hypothesis.






36. 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.






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






38. A subjective estimate of probability.






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






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






41. Probability of accepting a false null hypothesis.






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






43. Is a sample and the associated data points.






44. Some commonly used symbols for population parameters






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






46. ?






47. 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






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






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. Some commonly used symbols for sample statistics