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Mid-term Exam (Statistics for Business & Economics)

I. (Questions requiring a short answer, mostly concepts. 1 point each).
(1) The likelihood that an event will occur given that another event has already occurred.   conditional probability
(2) A concept of probability (a method of assigning probability) based on the assumption that each of the all possible outcomes is euqally likely. Classical probability
(3) A collection of one or more outcomes of an experiment   event
(4) A table used to classify observations according to two nominal (qualitative) characteristics ? Contingency table
(5) A quantity resulting from an experiment that, by chance, can assume different values.   Random variable
(6) A characteristic of a normal probability distribution that its probability curve gets closer and closer to X-axis (to either (+) or (-) direction), but never touches it. asymptotic
(7) A member of the family of normal probability distributions, with its mean being 0 and standard deviation being 1. Standard normal (z) distribution
(8) A formula to count the number of possible arrangements of certain number (r) of objects from a single group of (n) objects, with the order of objects being not important. nCr (n Combination r)
(9) The sampling distribution of the sample means will approach a normal distribution (regardless of the population distribution), if the size of sample is sufficiently large. Central limit theorem
(10) A single value computed from a sample and used to estimate a population parameter, contrasted with interval estimate.   Point estimate
(11) The difference between a sample statistic and the corresponding population parameter. Sampling error
(12) A sampling method in which population is ordered in a way, such as alphabetically, then a starting point is randomly selected & every kth item from it belongs to sample. Systematic random sampling
(13) What does the ‘df’ shown in the first column of t-distribution table stand for?   Degree of freedom...

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