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






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






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






4. When there is an even number of values...






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






6. 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.






7. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






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






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






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






11. 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.






12. Probability of rejecting a true null hypothesis.






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






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






15. 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






16. 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






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






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






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






20. Have no meaningful rank order among values.






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






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






23. 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).






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






25. 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






26. 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.






27. 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






28. S^2






29. 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






30. Planning the research - including finding the number of replicates of the study - using the following information: preliminary estimates regarding the size of treatment effects - alternative hypotheses - and the estimated experimental variability. Co






31. 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






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






33. 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.






34. 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)






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






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






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






38. A subjective estimate of probability.






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






40. Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically - sometimes they are grouped together as






41. The standard deviation of a sampling distribution.






42. Rejecting a true null hypothesis.






43. 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.






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






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






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






47. 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






48. Some commonly used symbols for sample statistics






49. 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






50. Two variables such that their effects on the response variable cannot be distinguished from each other.