Test your basic knowledge |

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 measurement such that the random error is small






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






3. 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.


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






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






6. 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






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






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






9. 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






10. S^2






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






13. 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.






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






15. Rejecting a true null hypothesis.






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






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






18. Failing to reject a false null hypothesis.






19. 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






20. A data value that falls outside the overall pattern of the graph.






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






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






23. Is a sample and the associated data points.






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






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






26. 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.






27. 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.






28. 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






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






30. 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






31. Some commonly used symbols for sample statistics






32. 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






33. Some commonly used symbols for population parameters






34. 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.






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






36. 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






37. Cov[X - Y] :






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






39. 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).






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






41. 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}.






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






43. 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.






44. 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.






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






46. Have no meaningful rank order among values.






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






48. Any specific experimental condition applied to the subjects






49. 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






50. E[X] :