Presentation is loading. Please wait.

Presentation is loading. Please wait.

W~N(20,16) P(W<25) P(W<16) P(15<W<24) P(9<W<18). It is given that the variable X follows normal distribution such that X~N(15,4) find... P(X<18) P(X<12)

Published byWilfred Leonard Modified over 8 years ago

Similar presentations

Presentation on theme: "W~N(20,16) P(W<25) P(W<16) P(15<W<24) P(9<W<18). It is given that the variable X follows normal distribution such that X~N(15,4) find... P(X<18) P(X<12)"— Presentation transcript:

1 W~N(20,16) P(W<25) P(W<16) P(15<W<24) P(9<W<18)

2 It is given that the variable X follows normal distribution such that X~N(15,4) find... P(X<18) P(X<12) P(12<X<18)

3 Aims: To get more practice standardising and finding probabilities.

4 The main purpose of today’s lesson is to practise using standardising in questions where the info is given in a context.

5 Ex 4C p106 Q7-9 top of page Next Lesson: “Inverse” Normal problems. Finding data values from probability. Robert Adrian 1775-1843: US Mathematician who developed the Normal Probability Laws independently of Gauss.

6

Download ppt "W~N(20,16) P(W<25) P(W<16) P(15<W<24) P(9<W<18). It is given that the variable X follows normal distribution such that X~N(15,4) find... P(X<18) P(X<12)"

Similar presentations

Normal Distribution 2 To be able to transform a normal distribution into Z and use tables To be able to use normal tables to find and To use the normal.

Normal Distribution 2 To be able to transform a normal distribution into Z and use tables To be able to use normal tables to find and To use the normal.
The Normal Distribution

The Normal Distribution
THE NORMAL DISTRIBUTION Lesson 1. Objectives To introduce the normal distribution The standard normal distribution Finding probabilities under the curve.

THE NORMAL DISTRIBUTION Lesson 1. Objectives To introduce the normal distribution The standard normal distribution Finding probabilities under the curve.
Graphics Calculator Probability Distributions Graphics Calculator Binomial Dist Graphics Calc Poisson Dist Graphics Calc Normal Dist.

Graphics Calculator Probability Distributions Graphics Calculator Binomial Dist Graphics Calc Poisson Dist Graphics Calc Normal Dist.
Probability Distribution

Probability Distribution
2003/02/13 Chapter 4 1頁1頁 Chapter 4 : Multiple Random Variables 4.1 Vector Random Variables.

2003/02/13 Chapter 4 1頁1頁 Chapter 4 : Multiple Random Variables 4.1 Vector Random Variables.
Samples vs. Distributions Distributions: Discrete Random Variable Distributions: Continuous Random Variable Another Situation: Sample of Data.

Samples vs. Distributions Distributions: Discrete Random Variable Distributions: Continuous Random Variable Another Situation: Sample of Data.
Lesson #15 The Normal Distribution. For a truly continuous random variable, P(X = c) = 0 for any value, c. Thus, we define probabilities only on intervals.

Lesson #15 The Normal Distribution. For a truly continuous random variable, P(X = c) = 0 for any value, c. Thus, we define probabilities only on intervals.
Lesson #16 Standardizing a Normal Distribution.  X ~ N( ,  2 )   X -   Z = ~ N( ,  )

Lesson #16 Standardizing a Normal Distribution.  X ~ N( ,  2 )   X -   Z = ~ N( ,  )
Statistics 270 - Lecture 14. Example Consider a rv, X, with pdf Sketch pdf.

Statistics Lecture 14. Example Consider a rv, X, with pdf Sketch pdf.
A random variable that has the following pmf is said to be a binomial random variable with parameters n, p The Binomial random variable.

A random variable that has the following pmf is said to be a binomial random variable with parameters n, p The Binomial random variable.
STARTER The probability that a particular page in a maths book has a misprint is 0.2. Find the probability that of 12 pages in the book: 4 of them have.

STARTER The probability that a particular page in a maths book has a misprint is 0.2. Find the probability that of 12 pages in the book: 4 of them have.
Chapter 4 Joint Distribution & Function of rV. Joint Discrete Distribution Definition.

Chapter 4 Joint Distribution & Function of rV. Joint Discrete Distribution Definition.
Mutually Exclusive: P(not A) = 1- P(A) Complement Rule: P(A and B) = 0 P(A or B) = P(A) + P(B) - P(A and B) General Addition Rule: Conditional Probability:

Mutually Exclusive: P(not A) = 1- P(A) Complement Rule: P(A and B) = 0 P(A or B) = P(A) + P(B) - P(A and B) General Addition Rule: Conditional Probability:
Binomial test (a) p = 0.07 n = 17 X ~ B(17, 0.07) (i) P(X = 2) = 0.22437 = 0.224 using Bpd on calculator Or 17 C 2 x 0.07 2 x 0.93 15 (ii) n = 50 X ~ B(50,

Binomial test (a) p = 0.07 n = 17 X ~ B(17, 0.07) (i) P(X = 2) = = using Bpd on calculator Or 17 C 2 x x (ii) n = 50 X ~ B(50,
Notes – Chapter 17 Binomial & Geometric Distributions.

Notes – Chapter 17 Binomial & Geometric Distributions.
Lesson 24 Aim: What is a ratio and how do we find the unit rate?

Lesson 24 Aim: What is a ratio and how do we find the unit rate?
Normal distribution (2) When it is not the standard normal distribution.

Normal distribution (2) When it is not the standard normal distribution.
7.3 APPLICATIONS OF THE NORMAL DISTRIBUTION. PROBABILITIES We want to calculate probabilities and values for general normal probability distributions.

7.3 APPLICATIONS OF THE NORMAL DISTRIBUTION. PROBABILITIES We want to calculate probabilities and values for general normal probability distributions.
Math 10 Chapter 6 Notes: The Normal Distribution Notation: X is a continuous random variable X ~ N( ,  ) Parameters:  is the mean and  is the standard.

Math 10 Chapter 6 Notes: The Normal Distribution Notation: X is a continuous random variable X ~ N( ,  ) Parameters:  is the mean and  is the standard.

Similar presentations

Ads by Google