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






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






3. 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






4. Some commonly used symbols for population parameters






5. 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.






6. 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






7. (e.g. ? - b) are commonly used to denote unknown parameters (population parameters).






8. 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






9. 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






10. E[X] :






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






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






13. 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.






14. Error also refers to the extent to which individual observations in a sample differ from a central value - such as






15. 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).






16. 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.






17. S^2






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






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






20. 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






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






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






23. Is the length of the smallest interval which contains all the data.






24. 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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25. The probability of correctly detecting a false null hypothesis.






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. Is denoted by - pronounced 'x bar'.






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






29. 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.






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






31. 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






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. Involves taking measurements of the system under study - manipulating the system - and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.






34. 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.






35. 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.






36. Is a measure of its statistical dispersion - indicating how far from the expected value its values typically are. The variance of random variable X is typically designated as - - or simply s2.






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

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38.






39. 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






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






41. 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






42. Given two jointly distributed random variables X and Y - the conditional probability distribution of Y given X (written 'Y | X') is the probability distribution of Y when X is known to be a particular value.






43. Is the probability distribution - under repeated sampling of the population - of a given statistic.






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






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






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






47. Any specific experimental condition applied to the subjects






48. Some commonly used symbols for sample statistics






49. Is a sample and the associated data points.






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