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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. 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'






2. 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)






3. 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






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






5. 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






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






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






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






9. 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






10. The proportion of the explained variation by a linear regression model in the total variation.






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






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






13. S^2






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






15. 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.






16. 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






17. Probability of rejecting a true null hypothesis.






18. Two events are independent if the outcome of one does not affect that of the other (for example - getting a 1 on one die roll does not affect the probability of getting a 1 on a second roll). Similarly - when we assert that two random variables are i






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






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






21. 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






22. 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.






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






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






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






26. 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






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






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






29. To find the median value of a set of numbers: Arrange the numbers in numerical order. Locate the two middle numbers in the list. Find the average of those two middle values.






30. Any specific experimental condition applied to the subjects






31. 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






32. 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.






33. The probability of the observed value or something more extreme under the assumption that the null hypothesis is true.






34. 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}.






35. Var[X] :






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






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

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38. Cov[X - Y] :






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






40. 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.






41. In the long run - as the sample size increases - the relative frequencies of outcomes approach to the theoretical probability.






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






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






44. 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






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






46. 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.






47. 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.






48. E[X] :






49. 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.






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