Statistics 113 Lab 2: Central limit theorem Nigel Chou Lab Section 02D _
Problem 1: Commented code included at end of assignment. Discussion of part 1: As p increases from 0 to 1 with n held constant, the peak of the pdf (given by np) moves to the ri
Nigel Chou Final Project, Stat 113, Fall 2007
Random Number Generators
To understand Random number Generators (RNGs), we first have to define what random numbers are. A random number is a value in a set that has an equal probability of being selecte
MATH 108 MIDTERM 2
November 15, 2005
Name: I have neither given nor received any unauthorized help on this exam and I have conducted myself within the guidelines of the Duke Community Standard. Signature:
Instructions: Please print your name clearly and r
Math 108 Third Midterm Examination December 1, 2010
NAME
(Please print)
Page Score 2 3 4 5 6 Total (Max Possible: 100)
Instructions: 1. Do all computations on the examination paper. You may use the backs of the pages if necessary. 2. Put answers inside th
Normal distribution known variance Large sample CI, or CLT to the rescue Small sample normal, thank Guinness Condence intervals on the spread or variance Condence bounds Sample size computations
Condence intervals
Sayan Mukherjee
Sta. 113 Chapter 7
General concepts Properties of estimators Maximum Likelihood estimation
Point estimation
Sayan Mukherjee
Sta. 113 Chapter 6 of Devore
October 18, 2007
Sayan Mukherjee
Point estimation
General concepts Properties of estimators Maximum Likelihood
Jointly distributed random variables
Joint distributions and the central limit theorem
Sayan Mukherjee
Sta. 113 Chapter 5 of Devore
September 27, 2007
Sayan Mukherjee
Joint distributions and the central limit theorem
Jointly distributed random v
Continuous random variables Continuous distributions
Continuous random variables and probability distributions
Sayan Mukherjee
Sta. 113 Chapter 4 of Devore
September 13, 2007
Sayan Mukherjee
Continuous random variables and probability distributio
Discrete random variables and probability distributions
Sayan Mukherjee
Sta. 113 Chapter 3 of Devore
August 30, 2007
Sayan Mukherjee
Discrete random variables and probability distributions
Table of contents
Sayan Mukherjee
Discrete random varia
Discrete probability
Introduction to discrete probability
Sayan Mukherjee
Sta. 113 Chapter 2 of Devore
August 30, 2007
Sayan Mukherjee
Introduction to discrete probability
Discrete probability
Table of contents
1
Discrete probability Set theo
Hypotheses and test procedures Tests for population means P-values Two sample tests
Hypothesis testing
Sayan Mukherjee
Sta. 113 Chapter 8 and 9 of Devore
November 26, 2007
Sayan Mukherjee
Hypothesis testing
Hypotheses and test procedures Tests f
CONFIDENCE INTERVAL
x z
2
n
,x z
2
2
n
SAMPLE SIZE CALCULATION
n
2z
2
w
2
2
z ^ p
PROPORTION CI
2
2n
z
2
^ ^ p(1 p) n
2
z
2
4n 2
^ p
z
2
z 1
PROPORTION CI n CALCULATION
2 2
2
^ ^ p(1 p) n
n
4
2 z n
2
^ ^ p(1 p)
z
2
w2
4 z
2
Statistics 113 Lab 2: Central limit theorem Nigel Chou Lab Section 02D _
Problem 1: Commented code included at end of assignment. Discussion of part 1: For the Binomial distribution (drawb), holding n constant, when p is close to 0 and 1, the histogr
STAT113 HW3
For Quiz 09/18/09
1. (Chapter 4: 100 ) Let X denote the time to failure (in years) of a certain hydraulic component. Suppose the pdf of X is f (x) = 32/(x + 4)3 for x > 0. (a) (b) (c) (d) (e) Verify that f (x) is a legitimate pdf. Determine th