i gh a bove t he r u s h in gw a t e rs a n d m is t o f N ia g a raF a lls ,
hu ndredso f t ouristsf rom a ro u n d t h e w o rld r e t u rn t o t h e 5 1 2 -ro o m
Embassy uitest o e njoy a c omplim
FIXED-INCOME SECURITIES: CHARACTERISTICS AND VALUATION
1(84). Rick bought a bond when it was issued by Macroflex Corporation 14 years
ago. The bond, which has a $1,000 face value and a coupon rate equ
ASEAN Corporate Governance Scorecard
Country Reports and Assessments 20122013
Corporate governance principles provide guidance on how corporations should operate
and can be useful to attract foreign i
An Alternative Three-Factor Model
Long Chen
Washington University in St. Louis
Robert Novy-Marx
University of Rochester
and NBER
Lu Zhang
The Ohio State University
and NBER
April 2011
Abstract
A new f
ch13
Student: _
1.
A corporation is a legal entity separate from its owners.
True False
2.
Corporations are subject to substantially fewer regulations and laws than are proprietorships and
partnership
Assessing
Normality and Data
Transformations
Role of Normality
Many statistical methods require that
the numeric variables we are
working with have an approximate
normal distribution.
For example, t-t
Cluster Analysis
Chapter 12
Statistics for Marketing & Consumer Research
Copyright 2008 - Mario Mazzocchi
1
Cluster analysis
It is a class of techniques used to
classify cases into groups that are
r
Logistic Regression
for binary outcomes
In Linear Regression, Y is continuous
In Logistic, Y is binary (0,1). Average Y is P.
Cant use linear regression since:
1. Y cant be linearly related to Xs.
2.
C8057 (Research Methods 2): One Way Repeated Measures ANOVA using SPSS
One-Way Repeated Measures
ANOVA using SPSS
Introduction
Repeated measures is a term used when the same participants participate i
Logistic Regression
Chapter 8
Aims
When and Why do we Use Logistic
Regression?
Binary
Multinomial
Theory Behind Logistic Regression
Assessing the Model
Assessing predictors
Things that can go W
Discriminant Analysis
Database Marketing
Instructor:Nanda Kumar
Multiple Regression
Y = b0 + b1 X1 + b2 X2 + + bn Xn
Same as Simple Regression in principle
New Issues:
Each Xi must represent somet
Discriminant Analysis (DA)
1. Basic Concept
a) Dependent Variable: Categorical (nominal). If the dependent variable is ordinal or
metric, convert it to mutually exclusive and exhaustive categories.
I
Cluster Analysis (CLA)
also known as Q analysis, typology construction,
classification analysis, or numerical taxonomy
The primary objective of CLA is to classify objects into relatively homogeneous
Factor Analysis: Example Questions and Outline Model Answers
Question 1
People have been rated on their suitability for an advanced training
course in computer programming on the basis of six ratings
Introduction to SPSS
Johan Smits
Senior lecturer Statistics, Research
and SPSS
Saxion Market Research
About SPSS Inc.
SPSS Inc. is a leading worldwide provider
of predictive analytics software and
so
1. Evaluating the Normality of Metric Variables
The histogram shows us the relative frequency of different
ranges of values for the variable. If the variable is normally
distributed, we expect the gre
Common Factor Analysis
World View of PC vs. CF
Choosing between PC and CF
PAF - most common kind of CF
Communality & Communality Estimation
Common Factor Scores
World View of PC Analyses
PC analy
SW388R7
Data Analysis
& Computers
II
Slide 1
Principal Component Analysis: Additional
Topics
Split Sample Validation
Detecting Outliers
Reliability of Summated Scales
Sample Problems
Compu
ters II
Spl
MANOVA: Multivariate
Analysis of Variance
Review of ANOVA: Univariate
Analysis of Variance
An univariate analysis of variance looks for the causal
impact of a nominal level independent variable (facto
Correspondence
Analysis
Correspondence analysis is a
descriptive/exploratory technique designed to
analyse simple two-way and multi-way tables
containing some measure of correspondence
between the row
Logistic Regression
Logistic Regression - Dichotomous Response
variable and numeric and/or categorical
explanatory variable(s)
Goal: Model the probability of a particular as a function
of the predic
Factor Analysis
1.
2.
3.
4.
The purpose of factor analysis is to reduce the initial number of variables into a smaller and therefore
more manageable (easier to analyze and interpret) set of underlying
Logistic Regression
Multivariate Analysis
What is a log and an exponent?
Log is the power to which a base of 10 must
be raised to produce a given number. The log
of 1000 is 3 as 103=1000.
The log of a
Postgraduate Statistics: Cluster Analysis
Cluster Analysis
Aims and Objectives
By the end of this seminar you should:
Have a working knowledge of the ways in which similarity between cases can be
quan
Factor Analysis
1.
2.
3.
4.
The purpose of factor analysis is to reduce the initial number of variables into a smaller and therefore
more manageable (easier to analyze and interpret) set of underlying
SW318
Social
Work
Statistics
Slide 1
Logistic Regression and Odds Ratios
Example of Odds Ratio
Using Relationship between
Death Penalty and Race
tics
Slide
2
Probability and Odds
We begin with a frequ
Ordinal Measures of Association
for Survey-type Data
Christoph Maier
Coordinator of the ARL
December 6, 2007
Stats For Lunch
Please visit our ARL website: www.arl.iup.edu
Slide 1
References
Discoverin
Structural Equation Modelling (SEM)
Aims and Objectives
By the end of this seminar you should:
Have a working knowledge of the principles behind causality.
Understand the basic steps to building a Mod
stics
Slide
1
Practice Problem: Lambda (1)
This question asks whether the value of lambda
(i.e., lambda of .006) is correct and, if it is, the in
terpretation of the value (i.e., a very weak relatio
n
4. How would you go about doing a literature review in the area corporate social responsibility?
Bc 1: Xc nh mc tiu tng quan v trch nhim x hi doanh nghip.
Bc 2: Phc tho ni dung ca vn cn nghin cu.
Bc 3
PHNG GD&T
THCS
K THI HSG VNG HUYN LP 7
MN THI: NG VN
Thi gian lm bi: 150 pht (khng k thi gian giao )
Cu 1: Nu tc dng ca cu c bit. Cho v d?
Cu 2: Chp 2 cu ca dao- dn ca bt u bng ch Thn em. Trong 2 cu ,