MA 214
Applied Statistics
Group Projects
The motivation behind the statistics project is to give you an opportunity to put into practice what
we will study in lectures, studio sessions, and problem se
A few notes about the relationship between the
Chi-squared distribution, and the Z, t, and F
distributions.
Lets take a short break from regression
and discuss the chi-squared distribution!
Whats so s
MA 214: Applied Statistics
Instructor: Ian Johnston
Regression Analysis
Part III
Where Weve Been
We were discussing.
How to fit a linear regression model with one
covariate.
How to quantify the goodne
Using JMP
A few side notes.
If you dont know how to interpret a particular part
of a JMP output, read the documentation about
the procedure you are using on the JMP website.
As a shortcut, you can t
MA 214: Applied Statistics
Instructor: Ashis Gangopadhyay
Categorical Data Analysis
MA 214
Where Weve Been
We were discussing.
How to model a response variable that is
continuous, while the covariates
MA 214: Applied Statistics
Instructor: Ashis Gangopadhyay
ANOVA
Part I
MA 214
Where Weve Been
We were discussing.
How to develop statistical models where the
response variable Y is continuous and
cova
Solutions to Homework 1
Prakash Balachandran
Department of Mathematics & Statistics
Boston University
Monday, September 19, 2011
1. (DAgostino, # 6) According to the Empirical Rule, approximately:
68%
Solutions to Homework 2
MA115, Chapter 2
2. For histograms, all bins have to be touching each other. If not, all points taken off.
(a) 3 points
Frequency
Relative
MA 214: Applied Statistics
Instructor: Prakash Balachandran
ANOVA
Part I
MA 214
MA 213 Thursday 10/31/2013
Last Time: Chapter 10: One-way ANOVA
This Time: Chapter 10: One-way ANOVA continued
Reading:
A regression analysis is inappropriate
when
A. You have two variables that
are measured on an interval
or ra8o scale
B. You want to make predic8ons
for one variable ba
MA 214 Midterm 2 Review
Here we go again!
For a given x, a confidence interval for
E(y) will always be wider than a
prediction interval for y.
1. True
2. False
Recall: standard error for E(y)
Recall
MA 214: Applied Statistics
Instructor: Prakash Balachandran
Regression Analysis
Part II
MA 214
MA 213 Thursday 10/17/2013
Last Time: Chapter 11: Simple Linear Regression
This Time: Chapter 11 Review +
Department of Mathematics and Statistics
Fall 2014
MA 214
Applied Statistics
TIME & LOCATION: Lecture: TR 12:30 - 2:00 PM, CAS226
Lab/Studio: 1 hour/week, Wednesdays Check your schedule
Discussion: 1
MA 214: Applied Statistics
Instructor: Ashis Gangopadhyay
Hypothesis Testing
MA 214
Where Weve Been
Discussing inferential methods for one
sample data and to describe the true
value of a population pa
MA 214: Applied Statistics
Instructor: Ashis Gangopadhyay
Regression Analysis
Part III
MA 214
Where Weve Been
We were discussing.
How to fit a linear regression model with one
covariate.
How to quanti
Homework 10 solution 1. a) H0: 1 = 2 = 3 = 4 H1: Not all means are equal. Control X .j SSb 16.2 T15 20.4
= 0.05 T40 17.2 T50 12.8 Overall X .=16.7
= nj ( X .j - X .)2 = 5{(16.2-16.7)2 + (20.4
Homework 11 Solution Solutions to SAS Problems
1. The ANOVA Procedure Class Level Information Class Levels Values trt 4 control t15 t40 t50 Number of observations 20 The ANOVA Procedure Dependent Vari
MA 214
Applied Statistics
Group Projects
The motivation behind the statistics project is to give you an opportunity to put into practice what
we will study in lectures, studio/lab sessions and problem
Department of Mathematics and Statistics
Fall 2017
MA 214
Applied Statistics
TIME & LOCATION: Lecture: TR 12:30 - 2:00 PM, CAS226
Mandatory Lab/Studio: 1 hour/week, Wednesdays Check your schedule
Mand
Department of Mathematics and Statistics
Spring 2017
MA 214
Applied Statistics
TIME & LOCATION: Lecture: TR 12:30 - 1:45 PM, CAS 316
Lab/Studio: 1 hour / week, Tuesdays Check your schedule
Discussion:
Introduction to the Philosophy of History
G.W.F. Hegel
Introduction
The subject of this course of Lectures is the Philosophical History of the World. And by this
must be understood, not a collection o
MA 214: Applied Statistics
Instructor: Ashis Gangopadhyay
ANOVA
Part II
MA 214
Where Weve Been
We were discussing
.
how to develop a model for a continuous
response variable based on one categorical
c
MA 214: Applied Statistics
Instructor: Ashis Gangopadhyay
Logistic Regression
MA 214
Where we have been.
We were discussing how to analyze a
categorical response variable based
on one categorical cov