Dictionary
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**element**- A member of or an object in a set (
*cf*Venn Diagrams Discussion). **empty set**- The empty set, Ø, is the set that has no members.
**end point convention**- In histograms, one needs to decide where to count values that are on the exact boundary between two intervals: either in the left or in the right interval. Let readers of the histogram know which side is chosen (
*cf*Class Interval: Scale and Impression Discussion). **equally likely**- In probability, when there are the same chances for more than one event to happen, the events are
*equally likely*to occur. For example, if someone flips a coin, the chances of getting heads or tails are the same. There are equally likely chances of getting heads or tails (*cf*Fair Choice Discussion). **escapees**- Values for C in the Julia Set or Mandelbrot set where at each iteration the resulting value grows larger and larger, approaching infinity (
*cf*Prisoners and Escapees -- Julia Sets Discussion). **estimate**- The best guess arrived at after considering all the information given in a problem (
*cf*Making Estimates Discussion , From Geometry to Probability Discussion ). **Euclidean algorithm**- The method for finding remainders by multiplying the divisor by the quotient and subtracting that amount from the number being divided. For example, when finding the remainder for 25 divided by 4, the quotient is 6, so one multiplies 6 times 4 (giving 24) and then subtracts 25 from 24, leaving 1 as the remainder (
*cf*What are Remainders Discussion). **event**- In probability, an event is an occurrence or the possibility of an occurrence that is being investigated.
**expected value**- The amount that is predicted to be gained, using the calculation for average expected payoff (
*cf*Expected Value Discussion). **exponent**- An expression of the number of times that a base is used as a factor (
*cf*Exponents and Logarithms Discussion). **experimental probability**- The chances of something happening, based on repeated testing and observing results. It is the ratio of the number of times an event occurred to the number of times tested. For example, to find the experimental probability of winning a game, one must play the game many times, then divide the number of games won by the total number of games played (
*cf*Probability and Outcome Discussion).
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