CHAPTER 6 Discrete probability distributions to accompany Introduction to business statistics fourth edition by ronald M. Weiers Presentation by priscilla Chaffe-Stengel Donald N. stengel C 2002 The Wadsworth Group
CHAPTER 6 Discrete Probability Distributions to accompany Introduction to Business Statistics fourth edition, by Ronald M. Weiers Presentation by Priscilla Chaffe-Stengel Donald N. Stengel © 2002 The Wadsworth Group
l Chapter 6- learning objectives Distinguish between discrete and continuous random variables Differentiate between the binomial and the Poisson discrete probability distributions and heir applications Construct a probability distribution for a discrete random variable, determine its mean and variance and specify the probability that a discrete random variable will have a given value or value in a given range o 2002 The Wadsworth Group
Chapter 6 - Learning Objectives • Distinguish between discrete and continuous random variables. • Differentiate between the binomial and the Poisson discrete probability distributions and their applications. • Construct a probability distribution for a discrete random variable, determine its mean and variance, and specify the probability that a discrete random variable will have a given value or value in a given range. © 2002 The Wadsworth Group
ll Chapter 6-Key terms Randomⅴ ariables Discrete Continuous Bernoulli process Probability distributions Binomial distribution Poisson distribution o 2002 The Wadsworth Group
Chapter 6 - Key Terms • Random variables – Discrete – Continuous • Bernoulli process • Probability distributions – Binomial distribution – Poisson distribution © 2002 The Wadsworth Group
l Discrete us continuous variables Discrete Variables: Continuous variables: Can take on only Can take on any value certain values along at any point along an an interval interval the number of sales the depth at which a made in a week drilling team strikes oil the volume of milk the volume of milk bought at a store produced by a cow the number of the proportion of defective parts defective parts o 2002 The Wadsworth Group
Discrete vs Continuous Variables • Discrete Variables: Can take on only certain values along an interval – the number of sales made in a week – the volume of milk bought at a store – the number of defective parts • Continuous Variables: Can take on any value at any point along an interval – the depth at which a drilling team strikes oil – the volume of milk produced by a cow – the proportion of defective parts © 2002 The Wadsworth Group
l Describing the distribution for a Discrete random variable The probability distribution for a discrete random variable defines the probability of a discrete value x -Mean:=E(x)=∑xP(x) Variance: 02=El(x-u)2I ∑(x1-+)2P(x) o 2002 The Wadsworth Group
Describing the Distribution for a Discrete Random Variable • The probability distribution for a discrete random variable defines the probability of a discrete value x. – Mean: µ= E(x) = – Variance: s 2 = E[(x – µ)2 ] = © 2002 The Wadsworth Group ( ) i i x P x ( − ) ( ) 2 i i x P x