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






2. Statistics involve methods of organizing - picturing - and summarizing information from samples or population.






3. E[X] :






4. 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






5. Where the null hypothesis is falsely rejected giving a 'false positive'.






6. (or just likelihood) is a conditional probability function considered a function of its second argument with its first argument held fixed. For example - imagine pulling a numbered ball with the number k from a bag of n balls - numbered 1 to n. Then






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






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






9. Summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights) - while frequency and percentage are






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






11. 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.






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






13. 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.






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






15.






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






17. 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.






18. Is the probability of some event A - assuming event B. Conditional probability is written P(A|B) - and is read 'the probability of A - given B'






19. 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






20. 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.






21. 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






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






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






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






25. A variable has a value or numerical measurement for which operations such as addition or averaging make sense.






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






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






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






29. Is a measure of the 'peakedness' of the probability distribution of a real-valued random variable. Higher kurtosis means more of the variance is due to infrequent extreme deviations - as opposed to frequent modestly sized deviations.






30. 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.






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






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. Cov[X - Y] :






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






35. 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






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






37. 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.






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






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






40. 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.






41. (or atomic event) is an event with only one element. For example - when pulling a card out of a deck - 'getting the jack of spades' is an elementary event - while 'getting a king or an ace' is not.






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






43. Is the exact middle value of a set of numbers Arrange the numbers in numerical order. Find the value in the middle of the list.






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






45. Design of experiments - using blocking to reduce the influence of confounding variables - and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage - the experimenters a






46. 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.






47. 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.


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






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






50. Samples are drawn from two different populations such that the sample data drawn from one population is completely unrelated to the selection of sample data from the other population.