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






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






3. 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.






4. 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






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






6. 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






7. 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.






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






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






10. 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.






11. 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.






12. Have no meaningful rank order among values.






13. 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






14. Failing to reject a false null hypothesis.






15. 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.






16. 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.






17. The probability of correctly detecting a false null hypothesis.






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






19. The standard deviation of a sampling distribution.






20. 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.






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






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






23. Are usually written with upper case calligraphic (e.g. F for the set of sets on which we define the probability P)






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






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






26. Another name for elementary event.






27. The errors - or difference between the estimated response y^i and the actual measured response yi - collectively






28. 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.






29. 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.






30. Data are gathered and correlations between predictors and response are investigated.






31. 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






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






33. 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.






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






35. Is its expected value. The mean (or sample mean of a data set is just the average value.






36. 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






37. Is that part of a population which is actually observed.






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






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






40.






41. A measurement such that the random error is small






42. 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






43. A numerical measure that describes an aspect of a population.






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






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






46. 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






47. 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.






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






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






50. Some commonly used symbols for sample statistics