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






2. 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






3. 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.






4. 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)






5. Var[X] :






6. 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.






7. 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






8. 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.






9. 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.






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






11. 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






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

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






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






15. Given two jointly distributed random variables X and Y - the marginal distribution of X is simply the probability distribution of X ignoring information about Y.






16. A group of individuals sharing some common features that might affect the treatment.






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






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






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






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






21. 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.






22. Probability of rejecting a true null hypothesis.






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






24. 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






25. Is a sample and the associated data points.






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






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






28. 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






29. Any specific experimental condition applied to the subjects






30. 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






31. Probability of accepting a false null hypothesis.






32. 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.






33. Another name for elementary event.






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






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






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






37. 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






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






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






40. 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.






41. 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.






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






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






44. ?r






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






46. 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






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






48.






49. Is the result of applying a statistical algorithm to a data set. It can also be described as an observable random variable.






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