Hypothesis Testing
A hypothesis test is a tool to test the validity of a scientific/statistical
hypothesis.
As before, imagine that we are studying a random variable following a
distribution of known form with some unknown parameter .
Furthermore, suppose
Homework 7 - Pstat 120B Winter 2017
Problem 1
When it comes to advertising tweens are not ready for the hard-line messages that advertisers often use
to reach teenagers. The Geppeto Group study found that 78% of tweens understand and enjoy adds that
are s
Homework 6 Solution - Pstat 120B Winter 2017
Problem 1
Let X1 ,X2 ,.,Xn denote a random sample of size n from a normal distribution with mean and variance
2 .
a) If is unknown and 2 is known, find the MLE M LE for estimation of .
b) Find the CRLB for esti
Homework 9 Solution - Pstat 120B Winter 2017
Problem 1
Two sets of elementary school children were taught to read by using different methods, 50 by each method.
At the conclusion of the instructional period, a reading test yielded the results x1 = 74 and
Confidence Intervals
Definition
A confidence interval for a confidence level is an interval inside which
the true but unknown parameter is with probability 1 . There are 3
types of confidence intervals:
Lower Confidence Interval
A lower CI L , is an inter
Homework 8 - Pstat 120B Winter 2017
Problem 1
An experimenter has prepared a drug dosage level that she claims will induce sleep for 80% of people
suffering from insomnia. After examining the dosage, we feel that the claim regarding the effectiveness
are
Chapter 3 Stats
Chapter 3 Fundamental tools for statistics
Descriptive Statistics: summarize or describe relevant characteristics of data
Inferential Statistics: make inferences or generalizations about a population
Measures of Center
o Measure of Center:
Formulas:
P(Ac) = 1P(A)
P(A or B) = P(A) +P(B)P(A and B)
P(A | B) = P(A and B) P(B)
P(A | B) = P(A), if A is independent of B
P(A and B) = 0, if A and B are mutually exclusive
E(X) =Pall k k P(X = k)
E(X + ) = E(X) +
E( X) = E(X)
E(X + Y ) = E(X
PSTAT 120A
Winter 2016
Midterm 1
1/28/16
Time Limit: 75 Minutes
Name (Print):
Instructor:
Teaching Assistant:
Wade Herndon
This exam contains 6 pages (including this cover page) and 7 problems. Check to see if any pages
are missing. Enter all requested in
PSTAT 120A
More Counting Problems
Winter 2016
Problem 1: Each year starts on 1 of 7 days and each year is either a leap year or not a leap
year. How many possible calendars are there?
Multiplication rule for counting:
7(2) = 14.
Problem 2: Three different
PSTAT 120A
Midterm 2 Formulas
Binomial distribution
n x
f (x) =
p (1 p)nx , x = 0, 1, . . . , n
x
E [X] = np
Poisson distribution
f (x) =
e x
, x = 0, 1, 2, 3 . . .
x!
E [X] =
Geometric distribution
f (x) = (1 p)x1 p, x = 1, 2, 3, . . .
E [X] =
1
p
Exp
Transformations of Random Variables
Order Statistics
Sampling Distributions Related to the Normal Distribution
n m transformation
What do we mean by a transformation of a random variable?
Suppose:
I Y1 , Y2 , ., Yn
are n random variables.
I
The joint dist
Introduction
Review of Pstat 120A
Pstat 120B - Fall 2016
Jacob Lundbeck Serup
Department of Statistics and Applied Probability, UCSB
September 26. 2016
Jacob Lundbeck Serup
Pstat 120B - Fall 2016
Introduction
Review of Pstat 120A
Practical Information
My
Confidence Intervals
Definition
A confidence interval for a confidence level is an interval inside which
the true but unknown parameter is with probability 1 . There are 3
types of confidence intervals:
Lower Confidence Interval
A lower CI L , is an inter
Statistics
22/09/2016
An ideal world given by probability;
A real world with data;
The Statisticians Objectives
1. Ask the right questions
2. Collect useful data
3. Summarize the data
4. Make decisions and generalizations based on the data
5. Turn the dat
-title: "STA 100 R Handout 5 - Categorical"
author: "Erin K. Melcon"
output: html_document
-*Note, the following is adding data to R, you do not need to do this step.
will read in the data from a .csv or .txt as usual*
`cfw_r,echo = FALSE
gender = rep(c("
-title: "STA 100 R Handout 4 - ANOVA"
author: "Erin K. Melcon"
date: "February 10, 2016"
output: html_document
-# 1. The data
For this handout, I will use a built in dataset that is already in R (so you do
not have to load a dataset to use this handout).
PSTAT 5A:
Week 2
Class Worksheet
Conditional Probability
A social science researcher went to a elementary school and asked every fourth and fth grader
what they thought was their most important goal: Get good grades, Be popular, or Do well
in sports. The
S. Konda
Department of Statistics and Applied Probability
UCSB
PSTAT 130 - Summer 2015 - Konda
Recap:
PROC TABULATE vs PROC REPORT
PSTAT 130 - Summer 2015 - Konda
Lecture Outline
Producing HTML output using the Output Deliver System
Summaring data with
PSTAT 130 - Summer 2015 - Practice Midterm2
Important notes: (i) This practice test will be updated Monday July 27th night. (ii) Answer key will be provided
same night. (iii) The real midterm2 will be combination of this practice test, homework 3 to 5, le
S. Konda
Department of Statistics and Applied Probability
UCSB
PSTAT 130 Summer 2015 - Konda
Lecture Outline
Combining Datasets
Concatenating Datasets (Appending)
The SET statement
Merging Datasets
The MERGE and BY statements
Types of Merging
Parent-Ch
S. Konda
Department of Statistics and Applied Probability
UCSB
PSTAT 130 Summer 2015 - Konda
2
Lecture Overview
Reading Data into SAS
List input
Formatted List input
Column input
More on INPUT statements: Pointer control
Informats, Formats and Labels
Sreenivas KONDA
Department of Statistics and Applied Probability
UCSB
Note: Slides are courtesy of several UCSB and UCB lecture notes
PSTAT 130 - Summer 2015 - Konda
1
PSTAT 130 - Summer 2015 - Konda
2
Objectives
Navigate the SAS programming environment
S. Konda
Department of Statistics and Applied Probability
UCSB
PSTAT 130 Winter 2015- Konda
2
Lecture Outline
Summarizing Your Data cont
PROC MEANS
PROC FREQ
PROC TABULATE
PROC REPORT
PSTAT 130 Winter 2015- Konda
3
Procedures for Summarizing Data
PR
S. Konda
Department of Statistics and Applied Probability
UCSB
PSTAT 130 Summer 2015 - Konda
Lecture Outline
Variable Lists
Using SAS functions
Parse text data
Truncate numeric data
Converting data
numeric to character
character to numeric
Do loop
Q1. Using the HEART data in SASHELP directory, for the subset of data with
condition WHERE STATUS=Dead and Sex=Male, answer the following questions.
Display contents of the SASHELP.HEART file first and check the variables.
a. Create a simple VBAR plot for
PSTAT 130 Summer 2015, Midterm1 Practice Test
Closed book and notes; No cheat sheet
(Regular time: 70mins without computer and last 10mins with computer)
(Answer key will be provided Monday; 80% of test will be similar to the practice test and rest comes
S. Konda
Department of Statistics and Applied Probability
UCSB
PSTAT 130 - summer 2015 - Konda
Lecture Outline
Learn another way to create a running total
Sum statement
Clarify First.Obs and Last.Obs variables
With Single and Multiple BY variables
Writi
1(5pts). Write a working SAS code to read the state.txt into
state.sas7bdat. The text data is space delimited form with the variables
STATE(postal code), RANK, POPULATION in sequence. Your SAS code
must have three variables STATE, RANK, and POP and datali