L28 - Inference about the Comparison of Two Populations with
EQUAL Variances
Introduction
This chapter presents a variety of techniques whose objective is to compare two
populations.
We deal with qua
Study Guide 17 Sampling Distribution Quantitative Data
1. A stationery store wants to estimate the total retail value of the 5,000 greeting cards it has in its
inventory.
a. Construct a 95% confidence
Study Guide 54 MLR Cross Section Data, Multi-collinearity
When we transition from simple linear regression to multiple linear regression, several new situations
(problems) must be faced.
1. The use of
Study Guide for Midterm
1. Define the following terms:
a. Population
b. P-value
c. Statistic
d. alpha
e. Parameter
f. Standard deviation
2. According to the American Lung Association, 90% of adult smo
L22 SLR Simple Examples
Problem 1: Pizza Restaurant
You are interested in opening a pizza restaurant in your town, which has a community college with 10,000
students. But, before you do, you want to k
SG29 Two Independent Populations with Unequal Variances
1. The marketing managers at a major credit card company are planning to create a new marketing
campaign addressed at increasing bank card use.
L40 MLR Basic Models
Multiple linear regression has some fundamental differences from simple linear regression.
1. We report adjusted R-square rather than R-square
2. We must contend with multi-collin
L26 - TWO POPULATIONS
INFERENCE ABOUT THE RATIO OF TWO VARIANCES
I do not find the book helpful with this topic.
I present this chapter such that there is only an upper tail
test.
The question becomes
L25 Demand Functions (Eggs and Milk)
1. Demand Function for Eggs
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.579
R Square
0.335
Adjusted R Square
0.284
Standard Error
7.193
Observations
15
ANOVA
L24 Introduction to Residual Analysis
PROPERTIES OF RESIDUALS
The regression line summarizes the relationship between x and y.
The residuals, the deviations from the fitted line, show variation that r
L45 How to test hypotheses with linear regression using dummy variables?
Suppose you teach three sections of the same class.
You are curious if there is a difference in grades between any two section
L26 Dummy Variable Compared with Two Populations
We revisit the situation with a small retail business BEFORE and AFTER the advertising campaign.
BEFORE Advertising Campaign
Descriptive
Statistics
Mea
L25 Estimating Trends in Time Series Data
Time-series forecasting assumes that the factors that have influenced activities in the past and present will
continue to do so in approximately the same way
L46 MLR Selection Best Model with House Data (cross-section)
Glencove
Problem 1:
Nassau County is located 25 miles east of New York City. The data includes
the appraised value of houses ($1,000)
Lan
L44 Finding the BEST MODEL
SUMMARY OUTPUT
Regression Statistics
Model 1: Full Model
Y = weight of single Eastern European
Multiple R
0.695
women (lbs)
R Square
Adjusted R
Square
0.483
Standard Error
O
L50 Modeling U.S. Annual Corn Yields from 1960 to 2012
Model 1: where t is an annual counter = year -1959.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.936
R Square
Adjusted R
Square
0.876
Standa
Frequency
Form of Payment by Cust omers
at Applebee's in July 2013
500
4 00
300
200
100
0
4 32
224
120
24
Check
Elect ronic /online
Cash
Ot her/dont know
Form of Payment
Form of Payment
432
224
120
24
L04 Histograms
Organizing Quantitative Data
The first step in the construction of the frequency (relative frequency) distribution is to select the number of
classes desired.
o Choosing the number of c
L03 Numerical Descriptive Measures
We continue to examine how to summarize a large set of raw data so that meaningful essentials can be
extracted from it.
Measures of Central Location
When computing n
L06 - PROBABILITIES FROM CONTINGENCY TABLES
THE INTUITIVE APPROACH
Examples: Using data from a statistics class survey (population data) on gender and year in school, we have
the following table.
Figu
L08 Binomial Distribution
Chapter 5 Some Important Discrete Probability Distributions
Pg179
5.1 The Probability Distribution for a Discrete Random Variable
5.3 Binomial Distribution
Pg 189
Binomial Di
L17 - Critical values and p-values
Critical X-values
These values indicate the door that separates values
o That could have reasonably been generated by the process represented by the
null hypothesis
L07 - Probability and Discrete Probability Distributions
Expected Value and Correlation
Assigning Probabilities to Events
Random Experiment
A random experiment is a process that results in one of a nu
L12 - Introduction to Estimation
Chapter 8 Confidence Interval Estimation
Page 283
8.2 Confidence Interval Estimation for the mean when the population standard deviation is
UNKNOWN
8.3 Confidence Inte
L16 - Hypothesis Testing Part II
Example 1:
A small store owner wants to establish a benchmark for a store that she has recently purchased. She has not yet
taken possession of the store and obtains pe
L11 Chapter 7 Sampling and Sampling Distributions
Based on the book Statistics for Managers Using Microsoft Excel
Fifth Edition, 2008, written by Levine, Stephan, Krehbiel, and Berenson and
published
Southern Illinois University Edwardsville
MS 251: Statistical Analysis for Business Decisions
Excel Project
Problem:
A land developer is trying to determine how to price parcels of land in a
developme