Terms : Hide Images
| 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 |
