W1211 Introduction to Statistics Midterm Exam Oct 20, 2006
Name (write clearly!):
1. Please print your name in the above space. 2. This is a 2 hr examination. Plan your time accordingly. 3. This is a closed book examination. You are allowed to have
Continuous Random Variables and
Probability Distributions
4.1 PDFs, 4.2 CDFs and Expected Values 4.3 Normal Distribution
4.4 Exponential Distribution, 4.6 Normal Probability Plots
Continuous Random Variables
Recall the definition of pmf for a discrete ran
Homework 11 Exercises with R 20. > x<-c(.05,.10,.11,.12,.31,.37,.42,.58,.68,.68,.73,.85,.92) > y<-c(.48,.55,.48,.50,.58,.52,1.02,.86,.86,1.00,.88,1.04,1.70) > z<-lm(y~x) > summary(z) Call: lm(formula = y ~ x) Residuals: Min 1Q Median 3Q Max -0.20283
STATW1211.005 TR 02:40P-03:55P
Prof. Zhang
Homework 8 Solutions Textbook: Probability and statistics for engineering and the sciences (7th edition) by Jay L. Devore Chapter 9: Question 49
Parameter of interest: p1 p2 = true difference in proportions of th
BIOLOGY 446
STATISTICS FOR BIOLOGISTS (FALL 2015)
Instructor:
Dr. Joshua B. Plotkin
Office Hours: Thursdays from 9a-10a in Lynch Labs room 219
TA's:
Kevin Hong ([email protected]), Yang Ding ([email protected]), Tanya
Singh ([email protected]),
STATW1211.005 TR 02:40P-03:55P
Prof. Zhang
Homework 7 Solutions Textbook: Probability and statistics for engineering and the sciences (7th edition) by Jay L. Devore Chapter 8: Question 9
a. R1 is most appropriate, because x either too large or too small c
Probability
2.1 Sample Spaces and Events, 2.2 Properties, 2.4 Conditional
Probability, 2.5 Independence
Note: Study Section 2.3: Counting Techniques
What is chance? - Excerpt from War and
Peace by Leo Tolstoy
But what is chance ? What is genius ?
The word
Reading SAS Data Sets
Introduction to Reading Data
Using SAS Data as Input
Subsetting Observations and Variables
Adding Permanent Attributes
1
Reading SAS Data Sets
Introduction to Reading Data
Using SAS Data as Input
Subsetting Observations and Variables
Discrete Random Variables and
Probability Models
3.1 Random Variables 3.2 Probability Distributions for Discrete Random Variables 3.3
Expected Values 3.4 The Binomial Probability Distribution 3.5 Hypergeometric
Distribution 3.6 The Poisson Probability Dis
Working with SAS Syntax
Mastering Fundamental Concepts
Diagnosing and Correcting Syntax Errors
1
Working with SAS Syntax
Mastering Fundamental Concepts
Diagnosing and Correcting Syntax Errors
2
Objectives
Identify the characteristics of SAS statements.
Ex
Joint Probability Distributions and
Random Samples
5.1 Jointly Distributed Random Variables, 5.2 Expected Values, Covariance and Correlation, 5.3
Statistics and Their Distributions, 5.4 The Distribution of the Sample Mean, 5.5 The Distribution
of Linear C
Getting Started with SAS
Introduction to SAS Programs
Submitting a SAS Program
1
Getting Started with SAS
Introduction to SAS Programs
Submitting a SAS Program
2
Objectives
List the components of a SAS program.
State the modes in which you can run a SAS p
Reading Excel Worksheets
Using Excel Data as Input
Doing More with Excel Worksheets (Self-Study)
1
Reading Excel Worksheets
Using Excel Data as Input
Doing More with Excel Worksheets (Self-Study)
2
Objectives
Use the DATA step to create a SAS data set fro
Chapter 2: Probability
Study of randomness and uncertainty
Quantifies chance/likelihood associated with various outcomes
Branch of Mathematics, over 300 years old
There are entire books/courses focused on Probability, but in
this course (and Chapter), we
Displaying and Describing Quantitative
Data
1.2 Histograms in Descriptive Statistics, 1.3 Measures of
Location, 1.4 Measures of Variability
Thought Question
1. If you were to read the results of a study showing
that daily use of a certain exercise machine
Statistics W1211 (Section 004) Fall 2016
Instructor:
Sheela Kolluri, Ph.D.
Time/ Place: Fri 11:40 AM -2:25 PM, 207 Mathematics Building.
Prerequisite: Calculus I
Textbook: Probability and Statistics for Engineering and the
Sciences (9th Edition), by Jay L
- Sample: subset of a population
- Variable: any characteristic whose value may change from
one object to another in population
- Univariate data set consists of observations on a single
variable; Bivariate -> 2 variables, multivariate -> many
- Descripti
- t-distribution (unknown , )
=
&'(
)/ +
Upper-tailed: 1 (z), Lower-tailed: (z), Two-tailed: 2[1 ( z )]
Two Population Means
, df() = n 1
t-critical value: 0,1
- Properties of t-distribution
1 is bell-shaped, centered 0
More spread out than z curve
incre
Introduction
Course Logistics
An Overview of Foundation SAS
1
Introduction
Course Logistics
An Overview of Foundation SAS
2
The SAS Help Facility
3
4
Setup for the Poll
Start your SAS session.
Open the Help facility.
5
Poll
Were you able to open the Help
Point Estimation
6.1 General Concepts, 6.2 Methods of Point Estimation:
Maximum Likelihood Estimators
Point Estimation
A point estimate of a parameter is a single number that can be
regarded as a sensible value for .
A point estimate is obtained by select
Introduction to Statistics
A Little History, Types of Studies, Misuses of Statistics
Overview of the course
Introduction to Statistics
First half
semester
Descriptive Statistics
(Chapter 1)
Probability Theory
Estimation and T
esting
(Chapter 2-5)
(Chapter
Getting Familiar with
SAS Data Sets
Examining Descriptor and Data Portions
Accessing SAS Data Libraries
Accessing Relational Databases (Self-Study)
1
Getting Familiar with
SAS Data Sets
Examining Descriptor and Data Portions
Accessing SAS Data Libraries
A
STATW1211
HW1 Solutions
Problem 10 page 24:
a)
7.5 appears to be a representative strength value. Most values appear to be near the
representative value.
b) The display does not appear to be symmetric around the representative value, there
are more point
STATW1211
HW3 Solutions
Problem 74 page 86:
The probability that both phenotypes are O is 0.452 = 0.2025. The probability that
both phenotypes are the same is 0.42 + 0.112 + 0.042 + 0.452 = 0.3762.
Problem 84 page 87:
a) P (3 pass) = 0.73 = 0.343
b) P (
W1211_003 HW Solutions
Last problem
(1) Customers subscribing to B and C but not A: BCAC
(2) Customers subscribing to A only: ABCCC
(3) Customers subscribing to B only or A&B only: B(BC)C = B- BC
means intersect
C
means complement