Normal Appoximation to the Binomial
Example - Airline booking
An airline knows that over the long run, 90% of passengers who reserve
seats show up for ight. On a particular ight with 300 seats, the airline
accepts 324 reservations.
Lecture 7 - Sampling Di
Probability
Objective and Subjective Probability
Classical and relative frequency probabilities are categories of objective probability. Classical
probability is illustrated by a roll of the die. For example, the probability of rolling a 3 is 1 / 6.
In ge
Probability Distributions
Probability Distributions of Discrete Variables
The probability distribution of a discrete random variable specifies the respective probabilities
for all values of a discrete random variable.
Example: Data was collected on the us
Sampling Distributions
Sampling distributions can be used to answer probability questions about sampling statistics
and they provide the theoretical framework necessary to draw statistical inferences. The
sampling distribution is generated from samples of
Estimation
A point estimate is a value used to estimate a population parameter. An interval estimate is a range
which likely includes the parameter being estimated with a specified degree of confidence. One
criterion for a desirable estimator is unbiasedn
Hypothesis Testing
A hypothesis is a statement about 1 or more populations.
Statistical hypotheses evaluate hypotheses by appropriate statistical techniques.
Hypothesis testing can be subdivided into ten steps as follows:
1. Data. The nature of the data m
Analysis of Variance
A linear model can be represented generically as
Yj = 0 + 1X1j + 2X2j + + kXkj + j
whereby j represents the coefficients, j represents random error, the algebraic order is 1 and
the coefficients are constants.
Analysis of variance (AN
Simple Linear Regression and Correlation
Regression analysis is often utilized to predict or estimate the value of one variable
corresponding to a given value of another variable. Correlation analysis measures the strength
of the relationship between vari
Lesson 1: Descriptive Statistics
Introduction
Statistics Terminology
Variable: A characteristic which assumes different values in different people, places or things.
Examples include heart rate, weights of middle-school children and diastolic blood pressu
Connecting Mean, Median and Mode.
Mean, Median and Mode
We start with a set of 21 numbers,
Lecture 2 - Introduction to Probability
# [1] -2.2 -1.6 -1.0 -0.5 -0.4 -0.3 -0.2
# [12] 0.4 0.5 0.6 0.7 0.7 0.9 1.2
0.1
1.2
0.1
1.7
0.2
1.8
0.4
Statistics 102
mean(
Review
Arbuthnot
Lab 1 - Extra Credit
Lecture 3 - More Conditional Probability
Statistics 102
Colin Rundel
January 22, 2013
Statistics 102 (Colin Rundel)
Review
Lecture 3 - More Conditional Probability
Probability
Review
Basic Probability Review
January 2
Announcements
Announcements
Homework 1 - Out 1/15, due 1/22
Lecture 1 - Data and Data Summaries
Lab 1 - Tomorrow
Statistics 102
RStudio accounts created this evening
Try logging in at http:/ beta.rstudio.org
Colin Rundel
January 13, 2013
Practice Quiz - I
Dierence of two means
Condence intervals for dierences of means
Example - GSS
The General Social Survey (GSS) conducted by the Census Bureau
contains a standard core of demographic, behavioral, and attitudinal
questions, plus topics of special interest. M
Bootstrapping and Randomization Testing
Example - Rent in Durham
20 apartments here in Durham were randomly sampled and their rents
obtained. The dot plot below shows the distribution of the rents of these
apartments. Can we apply the methods we have lear
Lecture 8 - Hypothesis Testing
Sta102/BME102
Colin Rundel
February 12, 2014
Hypothesis testing
Hypothesis testing framework
Hypothesis testing framework
We start with a null hypothesis (H0 ) that represents the status quo.
We develop an alternative hypoth
Random Variables
Random variables
Lecture 4 - Random Variables and Discrete Distributions
A random variable is a numeric quantity whose value depends on the
outcome of a random event
We use a capital letter, like X , to denote a random variables
The value
Evaluating nearly normalness
Normal probability plot
Lecture 6 - Assessing Normality, Normal Approximation
to Binomial
A histogram and normal probability plot of a sample of 100 male heights.
q
q
male heights (in.)
qq q q
Sta102/BME102
Colin Rundel
Februa
Announcements
Announcements
HW1 and Lab 1 have been graded and your scores are posted in Gradebook
on Sakai (it is good practice to always double check your scores).
Lecture 5 - Continuous Distributions
You should have picked up Lab 1 last week, HW1 will
Multiple Regression
The Multiple Linear Regression Model
It is assumed in the multiple regression model that there is a linear relationship between a
dependent variable (Y) and independent variables (X1, X2, etc).
Assumptions
1. The Xi are nonrandom.
2. F