Elexis Gaines
World History I Ch. 4 Greece Review
2/20/17
2nd Russell
1. Name the 2 peninsulas of Greece
a. Northern = Attica
Southern= Peloponnese
2. Who were the Mycenaeans? Where did they live? What happened during the dark age?
What are tholos?
a. Anc
AP English Language and Composition
2002 Free-Response Questions
The materials included in these files are intended for use by AP teachers for course
and exam preparation in the classroom; permission for any other use must be
sought from the Advanced Plac
AP English Language and Composition
2006 Free-Response Questions
Form B
The College Board: Connecting Students to College Success
The College Board is a not-for-profit membership association whose mission is to connect students to college success and
oppo
CEE 101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2013
Lecture 15
1
CEE 101S/201S
Lecture 15
More on solving ODEs
Review and continuation of solving IVPs in
Matlab
Example: The spring vibration problem
Formulation and solution in Ma
CEE 101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2013
Lecture 12
CEE 101S/201S
Lecture 12
Differentiation and Integration (Chapter 23). To
compute:
Rates of change
Lengths, areas, and volumes
We will focus on
diff for computing
CEE101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2013
Lecture 11
CEE 101S/201S
Lecture 11
More Array Manipulation (Chapter 5 Please go
through it!)
Matrix (or Linear) Algebra (Chapter 16)
1
CEE 101S/201S
Some useful info on the web
7/18/13
Image Processing with
MATLAB
CEE 101S/201S
Summer 2013
Tracy Mandel
Todays plan
Working with images
Reading, showing, wriEng
Grayscale + color (RGB)
Specic examples:
Edge detecEon and cell counEng
CEE101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2013
Lecture 9
CEE 101S/201S
Lecture 9: Visualization
Introduction to plotting 3-D graphs (Chapter 26)
Plot a line in 3-D space, using plot3
Plot a surface in 3-D space, h=f(x,y), us
CEE101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2013
Lecture 7
CEE 101S/201S
LAST TIME
Functions
Via m-file
Anonymous function at command line
Function handles (ease readability)
TODAY and Thursday
More on functions
Organizing
CEE101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2013
Lecture 6
CEE 101S/201S
Lecture 6
More on Anonymous functions
More on defining and using functions
In-class exercise
Using eval (Sec. 9.3)
For self study: Using ASCII files (Y
CEE101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2012
Lecture 5
CEE 101S/201S
Lecture 5
TOPICS and READING ASSIGNMENTS:
Function via M-files
Function handles and anonymous functions
Old methods inline functions and feval we
wont di
CEE101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2013
Lecture 4
CEE 101S/201S
Last time
Matrices: 2d matrices, vectors, scalars
Matrix math and element-by-element math
Matrix manipulation
Special matrices (eye,zeros,ones)
Relatio
CEE101S/201S
Science & Engineering
Problem-solving with
Matlab
Summer 2013
Lecture 3
CEE 101S/201S
Lecture 3
Arrays: A primer.
Some special matrices
The Basic Relational and Logical Operators.
2
1
CEE 101S/201S
Matrices are
rectangular arrangements o
CEE 101S/201S
Science & Engineering Problemsolving with Matlab
EWSS Announcements
Pizza social this Friday afternoon at 4pm, 3rd floor
terrace (near Red Atrium)
Sign up for summer announcements:http:/
www.stanford.edu/group/ees/summer/
Please sign in
Stat S100
Useful Stata Commands
Inference
Tests/CIs for Quantitative Data:
1) One sample t-test for a mean
ttest var1 = mu0
2) Two-sample t-test for a difference in means (1 - 2)
pooled: ttest var1, by(var2)
unpooled: ttest var1, by(var2) unequal
3) Pair
Stat S-100 Summer 2011 Syllabus
June 26th, 2012
Maxwell Dworkin G115
Instructor: Kevin Rader, [email protected],
Office Hours: Tues, Thurs 5-6pm, Science Center SC-602
Text: Intro to the Practice of Statistics (IPS); Moore, McCabe, and Craig; 7th edi
19 June 2012
Page 1 of 10
Getting Started with Stata
Stat S100 Summer 2012
The purpose of this tutorial is to learn how to download, install, and use Stata for data manipulation, visualization, and simple analysis.
1. Downloading and Installing onto your
One sample inference for a mean () ttest. H0: =
3 and HA: 3.
Two sample inference for means (1 - 2) t-test. H0: 1 - 2 = 0 and HA: 1 - 2 0.
Binary predictors regression. H0: 1 = 2 = 3 = 0 and HA: At least one 0. This is a
two-sided f-test. The formula is (
Statistics Midterm
When calculating variance, make sure to subtract the mean and square each number then
divide by n - 1.
IQR is Q3 - Q1 To find outliers, multiply IQR by 1.5 and calculated Q1 - ans and Q3 + ans.
Anything below or above those numbers are
Unit X: Final Exam Review
1
General Recap
So lets take a breathe. Where do we stand?
Weve been looking at LOTS of different inferential
analysis procedures.
Whats the main difference between them?
The type of data we have!
Is the outcome data quantit
Stat S100 Summer 2012
Exam Review Problem Solutions
1. For each of the situations described below, select the inference technique that you believe is the
most applicable, and whether its a hypo test or CI. If it is a statistical hypothesis test, state the
Unit 10: More Regression
1
Unit 10 Outline
More Multiple Regression Topics
Binary Predictors to compare 3 or more group means
Contrast Testing
Multiple comparisons (& the Bonferroni correction)
Transformation of Variables
2
Example: Inference for 3+ Mean
Unit 9: Inference for Regression
Chapters 10 & 11 in IPS
1
Lecture Outline
Inference for Simple Linear Regression
Inference for the slope and general association
Inference for predictions at a particular x*
Multiple Regression
General concepts
Inferen
Unit 8: Inference for Proportions
Chapters 8 & 9 in IPS
1
Lecture Outline
Inference for a Proportion (one sample)
Inference for Two Proportions (two samples)
Contingency Tables and the 2 test
2
Inference for Proportions
IPS, Chapter 8
Inference for pop
Unit 7: Inference for Means
Chapter 7 in IPS
1
Lecture Outline
The t-distribution
One-Sample Inference for a Mean ()
Two-Sample Inference for Means (1-2)
Matched Pairs Inference (Diff = 1-2)
2
Remainder of the Course:
Inference
The rest of the course