Regression Analysis
1
Business Decisions
l
Whole Food Supermarket: Who should be our target
customers?
l
Fund manager: how shall I construct a market neutral
portfolio?
l
Are higher income consumers willing to pay more for organic
products?
How is this st
Application in Quality Management
Quality Management
l
Quality:
l
Continuous quality improvement starts at the source
l
Manufacturing Quality: e.g. performance, reliability, durability
Service Quality: e.g. responsiveness, waiting time, consistency
Early
Chapter 9
Multiple Linear Regression Analysis
In Chapter 8, we studied simple linear regression. In simple regression we deal with one independent
variable and one dependent variable. In this chapter, we will study multiple regression in which we deal wit
AVERY SPORTING GOODS CATALOG BUYING APPENDICES
STUDY BACKGROUND
The primary purpose of the study was to gain insight into people who are likely to buy
from catalogs. Averys management was stimulated to conduct the study by published research
investigating
2/18/2017 Review Test Submission: M2 Random Variables and Probability
Review Test Submission: M2 Random Variables and
Probability Practice
User DYLAN J OUTTRIM
Course BU.510.601.36.SP17 Statistical Analysis
Test M2 Random Variables and Probability Pract
2/18/2017 Review Test Submission: M3 Sampling and Condence Interval
Review Test Submission: M3 Sampling and Confidence
Interval Quiz
User DYLAN J OUTTRIM
Course BU.510.601.36.SP17 Statistical Analysis
Test M3 Sampling and Confidence Interval Quiz
Starte
2/18/2017 Review Test Submission: M2 Random Variables and Probability
Review Test Submission: M2 Random Variables and
Probability Quiz
User DYLAN J OUTTRIM
Course BU.510.601.36.SP17 Statistical Analysis
Test M2 Random Variables and Probability Quiz
Star
2/18/2017 Review Test Submission: M3 Sampling and Condence Intervals
Review Test Submission: M3 Sampling and Confidence
Intervals Practice
User DYLAN J OUTTRIM
Course BU.510.601.36.SP17 Statistical Analysis
Test M3 Sampling and Confidence Intervals Prac
Statistical Analysis
BU.510.610
Confidence Intervals
1.
2.
3.
4.
5.
z-Based Confidence Intervals for a Population Mean:
Known
t-Based Confidence Intervals for a Population Mean:
Unknown
Sample Size Determination
Confidence Intervals for a Population Pro
Hi, welcome to Lecture One Section B for
Statistical Reasoning II.
In this lecture section, we'll make things
a little bit more concrete by talking
about specific type of progression,
simple linear regression, and we'll
consider situations where our predi
All right, welcome back.
Now we're going to get into
some totally new territory, and
we're not going to replicate
the results of analyses we
did in Statistical Reasoning 1
using simple linear regression.
We're going to expand our toolbox now to
allow our
So the term correlation gets used
a lot not just in statistics, but
in everyday life.
Well, in this section we're actually
going to show how to use the results from
linear regression to measure correlation.
It's something we get in the output
from a compu
So just allow me to jump in quickly and
say, welcome back to
Statistical Reasoning.
This is part two, and in this first
lecture set of three lectures we're
going to discuss the basis for something
that will permeate the entire course,
something called Reg
Business Communication
2 Credits
120.620.K1
Thursday, 1:30-4:30 pm
8/25/16-10/13/16
Fall 1 2016
Harbor East
Instructor
Josie Ganzermiller, ABD
Contact Information
[email protected]
OfficeHours:Tuesday&Thursday12:301:30pm;andbyappointment
Office:1340Ch
Business Communication
Reading Discussion/ Basic Writing
Discussion Questions: Bring 3
Memo Editing Activity
Memo is due Saturday on BB
Bring at least one potential crisis
communication project topic to class next
time
Exercise: Evaluation of a Memo
Read
Business Communication
Welcome!
Business Communication
Welcome!
On a note card write:
Your name
Your occupation/department/specialty
What you hope to get out of this class
An interesting or unique fact about yourself
that you do not mind sharing (bu
11/14/16
STATISTICAL ANALYSIS
1
Week 3
AGENDA & LEARNING OBJECTIVES
Sampling
Types of Sampling
Sampling Error
Sampling Bias
Sampling Distribution of the Sample Means
Central Limit Theorem
Sampling Distribution of the Sample Proportion
Estimation of Pr
QUALITY MANAGEMENT
Week 7
Statistical Analysis
WHAT IS QUALITY?
Quality
Fitness for use
Extent to which customer
expectations are met
Types of quality
Quality of design
Quality of conformance
Quality of performance
WHY ARE WE STUDYING QUALITY
CONTR
Information Tab
Unit Price
$240.00
Unit Cost
$160.00
Reduced Price
$50.00
Mean
20000
Standard Deviation
5102
Regular profit/Unit
$80.00
Loss/Unit
$110.00
Worst Case Demand
10000
Most Case Demand
20000
Best Case Demand
30000
Order Quantity
15000
18000
2400
Question 1
Linear Regression:
Consider the following data for a multiple regression model relating housing prices (in
thousands of dollars) to the number of bedrooms in the house, the size of the lot and
the size of the house in square feet.
Explaining t
M2d: Bayes Theorem Scenario Assignment
Scenario Script
Caption: Bonnie needs you to investigate some quality control issues at the Burlington factory.
Bonnie: Thanks for coming in. Were working through a problem at our Burlington factory.
During a recent
M2a: Random Variable Distributions Scenario Assignment
Scenario Script
Caption: Princess Foods Corporation purchases glass containers from China for the packaging of their highend soups. These shipments come to Princess Foods Corporation in skids that wer
Course
Test
Started
Submitted
Due Date
Status
Attempt
Score
Time
Elapsed
Instruction
s
BU.510.601.33.FA16 Statistical Analysis
M2 Random Variables and Probability Quiz
8/31/16 2:36 PM
8/31/16 2:41 PM
9/4/16 11:59 PM
Completed
100 out of 100 points
4 minut
M2b: Normal Distribution Using the Z Formula Scenario Assignment
Scenario Script:
Caption: Princes Foods Corporation is going through their annual labor negotiation with their unionized
employees. Bonnie and Liwei are doing their due diligence and would l
TO:
FROM:
DATE:
SUBJECT:
Bonnie
Ehsanuddin S Ahmed
September 04, 2016
Recommendation to train day/morning shift
During analysis between day and night shift I noticed the day shift produces 65% of the
product and the night shift produces 35% of the product