A CLOSER LOOK AT STRAIGHTENING DATA
When we observe in an x-y plot that the relationship between two variables ap-
pears to bend or bulge, for example, as in Figure 22—3, every effort should be
made to straighten the bulge. The importance of “straight” da

Two-sample t-test, Paired t-test, CrossTabs and Correlations
Dr. Goutam Chakraborty
Demonstrations
Some of the slides and notes are adapted from SAS Education Course notes. These are
Copyrighted by SAS and used with permission. All reproduction and redist

Continuous RV, Normal Distribution,
Skewness, Kurtosis, Outliers, etc.
Dr. Goutam Chakraborty
Session 4 (Lecture)
Session Agenda
Part 1:
Part 2
Continuous random variable, properties of Normal
distributions, standard normal distribution
Summarizing quanti

Two-Sample t-tests, Paired t-Tests,
Cross-Tabs and Correlation
Dr. Goutam Chakraborty
Lecture Slides
Some of the slides and notes are adapted from SAS Education Course notes. These are
Copyrighted by SAS and used with permission. All reproduction and redi

Sampling, CLT, Confidence Intervals
(CI) and Hypothesis Testing
Dr. Goutam Chakraborty
Lecture 5, Part 1
Session Agenda
Types of estimators, the problem of inference, sampling
issues, sampling distribution of sample means, confidence
intervals, sampling e

I. STEVEN KELLY
SU AN K. JONES I 12
Testing Techniques
DR. GOUTAM CHAKRABORTY
Oklahoma State University
introduction
Testing or experimentation is one of the most important integrated marketing tech—
niques. Direct marketers typically communicate and/or t

Demonstrations of Summarizing
Quantitative and Qualitative Variables
Dr. Goutam Chakraborty
(Demonstrations)
Data : Customer Survey
Explore quantitative variables via the distribution platform
Age and Tenure as Analysis Variables
Workspace menu: Describ

Dr. Goutam Chakraborty
Basics of Marketing and STP Strategy
Dr. Goutam Chakraborty
Lecture 2 Slides, Part 1
Session Agenda
Part 1:
Dr. Goutam Chakraborty
Basics of marketing
An overview of market segmentation and STP strategy
1
Dr. Goutam Chakraborty
Defi

Dr. Goutam Chakraborty
Software (Demonstrations)
Session Agenda
Base SAS for
Opening an Excel file in SAS
Adding (creating) new columns to data
Sorting data and creating subsets of data
Doing some basic descriptive and exploratory analyses
Use SAS EG for

NETWORKING:
FROM CONTACTS TO CONNECTIONS
Jeretta Horn Nord
Professor
Management Science and Information Systems
NETWORKING:
FROM CONTACTS TO CONNECTIONS
I. Introduction
II.Story about the Impact of Networking
III. our Cs of Networking
F
IV. ace to Face vs

9/15/2015 Custom Flash Who Wants to be a Millionaire
How to Make a Flash Millionaire Game
Question #1:
A(n) ‘3 main function is to help you understand the complexities of the real-world environment.
Ch01ce A. constraint Check the
010108 B! entity

SAS Copyrighted materials used with permission. Do not redistribute
Dr. Goutam Chakraborty
1
SAS Copyrighted materials used with permission. Do not redistribute
Dr. Goutam Chakraborty
2
SAS Copyrighted materials used with permission. Do not redistribute
D

Dr. Goutam Chakraborty
1
Dr. Goutam Chakraborty
2
Dr. Goutam Chakraborty
3
When you analyze the differences between naturally occurring groups,
you are not actually manipulating a treatment. There is no true independent variable.
Many public health and bu

SAS Copyrighted materials. Do not redistribute.
Dr. Goutam Chakraborty
1
SAS Copyrighted materials. Do not redistribute.
Dr. Goutam Chakraborty
2
SAS Copyrighted materials. Do not redistribute.
Thedatausedtodevelopapredictivemodelconsistofasetofcases (obs

SAS Copyrighted document used with permission. Do not redistribute
Predictive Modeling Demonstrations
Handout
Variable Annuity Data Set
1= yes
0= no
Did customer
purchase variable
annuity product?
Other product
usage in a three
month period
Demographics
7

MKTG5983, Exercise 9 (10 Points)
Use the ex9 data set for this exercise. Below table contains description of the variables in the
dataset (Use 5% level of significance unless stated otherwise in the problem).
To identify risk factors associated with givin

Individual Exercise 8 (10 Points)
Please use 5% level of significance, unless mentioned otherwise.
Data Set Description:
You will work with the data file (exercise8_Data). I have posted an Excel version of the same
data set for your convenience. The data

MKTG 5983 Assignment 10
Dataset: Adult dataset
Abstract: Predict whether income exceeds $50K/yr based on census data.
Variable Description:
Part 1: Fitting the Logistic Regression Model
Q1. Create a library to access the dataset. Set the input dataset int

STUDENT PROJECTS: Drawing an EER diagram and creating an object-
relational database for the Student Projects .
Step 8.1: Modify the ER diagram and draw an EER diagram to represent the enterprise.
Be sure to identify relationship participation and cardina

STUDENT PROJECTS: Drawing a UML Diagram and Creating an ObjectOriented Database for the Student Project
Read the sample project steps for this chapter and apply the same techniques to the student
project that you are developing.
7.1 Create a UML diagram f

STUDENT PROJECTS Chapter 6: Normalizing the Relational Model for the
Student Project and Creating a Normalized Oracle Database
Read the sample project steps for this chapter and apply the same techniques to the student
project that you are developing.
Ste

Databases: Design, Implementation, and Management: Chapter 6
11/11/2015
STUDENT PROJECTS: Creating and Manipulating a Relational Database for
the Student Project
Read the sample project steps for this chapter and apply the same techniques to the student p

Introduction to Structured Query Language
This page is a introductory tutorial of the Structured Query Language (also known as SQL) and is a
pioneering effort on the World Wide Web, as this is the first comprehensive SQL tutorial available on the
Internet

Chapter 7
125
Chapter 7 SQL
Chapter Objectives
This chapter describes in detail what has become the standard query language for
relational database management systems, SQL. Although SQL is illustrated in this
chapter through primarily the Oracle7 SQL*Plus

Note that the ASSIGNMENT table in Figure P7.1 stores the JOB_CHG_HOUR values as
an attribute (ASSIGN_CHG_HR) to maintain historical accuracy of the data. The
JOB_CHG_HOUR values are likely to change over time. In fact, a JOB_CHG_HOUR
change will be reflec

SOCIAL TECHNOLOGIES IN
BUSINESS AND ACADEMIA
MSIS 4003 and 5623
Demographics
The total number of usable questionnaires
numbered 178.
80 from Oklahoma, 19 from Texas, 9 from
Colorado and the remaining 70 from 32
additional states throughout the United
St

1. Look at any common receipt from a grocery store or a restaurant. List all the potential data
elements on the receipt. What abbreviations of terms dont you understand? Make a list of questions
you would ask someone if you were going to make a database t

Chapter 5
The Relational Database
Operators
1
Example:
COURSE
Course# C-H LOC
MA330 2 HH220
CIS720 5 BS321
STUDENT
S#
Name
200
John
335
Mary
200
John
Course#
MA330
MA330
CIS720
2
Relation database operators
1. SELECT: creates a new relation by selecting o

Chapter1
Introduction to Databases
1
DatabaseApplications
Examples of Database Applications
Purchases from the supermarket
Purchases using your credit card
Booking a holiday at the travel agents
Using the local library
Taking out insurance
Renting a video