Chapter 6 AP Statistics Flashcards

5850297187	Random Variable	takes numerical values determined by the outcome of a chance process	0
5850303070	Probability Distribution	tells us what the possible values of X are and how probabilities are assigned to those values	1
5850314116	Discrete Random Variable	has a fixed set of possible values with gaps between them	2
5850322317	Continuous Random Variable	takes all values in some interval of numbers	3
5850331508	Mean (Expected Value) of a Random Variable	the balance point of the probability distribution density curve or histogram	4
5850344020	Mean of a Discrete Random Variable		5
5850367197	Variance of a Random Variable	the "average" squared deviation of the values of the variable from their mean	6
5850374054	Standard Deviation	the square root of the variance and measures the typical distance of the values in the distribution from the mean	7
5850385163	Variance of a Discrete Random Variable		8
5850399599	Adding/Subtracting/Multiplying/Dividing Constants to a Random Variable	adding/subtracting changes the mean but not the standard deviation and multiplying/dividing affects both but does not change the shape of the distribution	9
5850423311	Linear Transformation	involves adding or subtracting a constant, multiplying or dividing a constant, or both Y=a+bx	10
5850436523	Shape of a Linear Transformation	same as the probability distribution of X is b>0	11
5850444384	Center of a Linear Transformation	uy=a+bux	12
5850449282	Spread of a Linear Transformation	oy=IbIox	13
5850458909	Mean of the Sum of Two Random Variables	the sum of their means	14
5850465482	Mean of the Difference of Two Random Variables	the difference of their means	15
5850472061	Independent Random Variables	knowing the value of one variable tells you nothing about the other	16
5850479976	The Variance of the Sum of Two Independent Random Variables	the sum of their variances	17
5850486368	The Variance of the Difference of Two Independent Random Variables	the sum of their variances	18
5850493688	Binomial Setting	consists of independent trials of the same chance process, each resulting in success or failure, with probability of success on each trial	19
5850505228	Binomial Random Variable	the count X of successes	20
5850509739	Binomial Distribution	its probability distribution	21
5850513822	Binomial Coefficient		22
5850517779	Factorial	n!=n(n-1)(n-2)...(3)(2)(1)	23
5850531263	Binomial Probability		24
5850535212	Mean of a Binomial Random Variable		25
5850537496	Standard Deviation of a Binomial Random Variable		26
5850543044	10% Condition	the binomial distribution with trials n and probability p success gives a good approximation to the count of successes in an SRS of size n from a large population containing proportion n of successes as long as the same size n is no more than 10% of the population size N	27
5850565588	Normal Approximation	if X is a count of successes having the binomial distribution with parameters n and p, then when n is large, X is approximately Normally distributed with mean np and standard deviation square root of np(1-p)	28
5850586285	Large Counts Condition	using normal approximation when np>=10 and n(1-p)>=10	29
5850601712	Geometric Setting	consists of repeated trials of the same chance process in which the probability p of successes is the same on each trial, and the goal is to count the number of trials it takes to get one success	30
5850617258	Geometric Random Variable	Y when Y= the number of trials required to obtain the first success	31
5850625386	Geometric Distribution	its probability distribution	32
5850629850	Geometric Probability		33
5850636856	Mean of a Geometric Random Variable	uy=1/p	34