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






2. 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






3. 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.






4. 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






5. Var[X] :






6. 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






7. Is often denoted by placing a caret over the corresponding symbol - e.g. - pronounced 'theta hat'.






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






9. 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.






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






11. 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.






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






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






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






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






16. 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






17. In Bayesian inference - this represents prior beliefs or other information that is available before new data or observations are taken into account.






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






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






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






21. 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.






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


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






24. 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)






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






26. 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






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






28. 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.


29. Long-term upward or downward movement over time.






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






31. Failing to reject a false null hypothesis.






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






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






34. Is data arising from counting that can take only non-negative integer values.






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






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






37. 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.






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






39. 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






40. 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






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






42. The collection of all possible outcomes in an experiment.






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






44. 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






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






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






47. 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






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






49.






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