Measures of
Dispersion
n
Which student is more consistent in his
scores?
Exam 1 Exam 2 Exam 3 Exam 4 Exam 5 Average
Student
A
Student
B
90
91
89
91
89
90
95
85
90
92
88
90
n
Consider the following mea
NOTES
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Definition. Statistical inference comprises
those methods concerned with the analysis of
a portion of a set of observations under study in
order to draw generalizations,
Propositional Logic
CSE 191, Class Note 01
Propositional Logic
Computer Sci & Eng Dept
SUNY Buffalo
c Xin He (University at Buffalo)
CSE 191 Discrete Structures
1 / 37
Discrete Mathematics
What is Dis
Stat101 Sample Long Exam No. 3 Questions
GENERAL INSTRUCTIONS: (Please read carefully. Every infraction of these rules will merit a
five-point deduction on your raw score, except where a different pen
Stat101 Homework
To be solved by pairs (you and your homework partner)
Due Date: during class time on Wednesday, September 26, 2012
Homework submitted after the deadline will be accepted but only unti
Stat101 Sample Long Exam No. 2 Questions
GENERAL INSTRUCTIONS: (Please read carefully. Every infraction of these rules will merit a
five-point deduction on your raw score, except where a different pen
Chapter 6
Measures of Central
Tendency
Definition of a Summary Measure
(page 185)
A summary measure is a single value
that we compute from a collection of
measurements in order to describe one
off th
Supplementary Lecture
The Engineers Transit
Engr. Jeark A. Principe, MSc.
Department of Geodetic Engineering (DGE)
Training Center for Applied Geodesy and Photogrammetry (TCAGP)
Engineers Transit
Cre
GE 10 Lecture 12A:
INTRODUCTION TO CARTOGRAPHY
ENGR. JEARK A. PRINCIPE, MSc.
Department of Geodetic Engineering (DGE)
Training Center for Applied Geodesy and Photogrammetry (TCAGP)
TRAINING CENTER FOR
Chapter 2
Collection of Data
Definition of Measurement (page 21)
Definition 2.1.
M easurem ent is the process of determining
the value or label of the variable based on
what has been observed.
Chapter
Chapter 9
Measures of Skewness
And Kurtosis
Symmetric vs Skewed Distribution
(page 260)
Definition 9.1
If it is possible to divide the histogram at the center into two
identical halves, wherein each h
Chapter 7
Measures of Location
Definition of
Measures of Location (page 219)
A measure of location provides information
on the percentage of observations in the
collection whose values are less than o
Chapter 3
Sampling and
Sampling Techniques
Complete Enumeration versus Sampling
In com plete enum eration or a
census , we measure the variable/s of
interest from all the elements of the
population.
I
Section 6.1
Summation
The Summation Notation (page 186)
n
X X X
i
1
2
. Xn
i1
where (capital
p
Greek letter sigma)
g ) is the summation notation
X i is the value of the variable for the ith observatio
Chapter 10
Exploratory Data Analysis
Definition of
Exploratory Data Analysis (page 410)
Definition 12.1.
Exploratory data analysis (EDA) is a subfield of applied
statistics that is concerned with the
Chapter 8
Measures of Dispersion
Definition of
Measures of Dispersion (page 231)
A measure of dispersion is a descriptive summary measure
that helps us characterize the data set in terms of how varied
Chapter 5
Organization of Data
Definition of Raw Data (page 164)
Definition 5.1.
Raw data are data in their original form.
* Raw data have not been organized in any
manner and
d observations
b
are rec
Chapter 4
Presentation of Data
Methods of Data Presentation
Textual presentation (page 117): incorporates
important figures in a paragraph of text
Tabular presentation (page 120): arranges figures
in
Least Squares
Adjustment of
GPS Networks
GE 129 Lecture 8
JEARK A. PRINCIPE
GPS Networks: Errors
(1) orbital errors in the satellite
(2) signal transmission timing errors due to
atmospheric condition
THEORY OF MEASUREMENT & ERRORS:
Errors and Statistics
GE10 LECTURE 2
Engr. Jeark A. Principe, MSc.
Department of Geodetic Engineering (DGE)
Training Center for Applied Geodesy and Photogrammetry (TCAG
Lecture 5:
ANGLE & DIRECTION
MEASUREMENTS
Engr. Jeark A. Principe, MSc.
Department of Geodetic Engineering (DGE)
Training Center for Applied Geodesy and Photogrammetry (TCAGP)
OUTLINE
I. Definition an
Engr. Jeark A. Principe, MSc.
Department of Geodetic Engineering (DGE)
Training Center for Applied Geodesy and Photogrammetry (TCAGP)
SURVEYING AND MAPPING:
AN INTRODUCTION
Objectives
At the end of th
GE 129 LECTURE 2A:
GLS Application to Coordinate
Transformation (Case of 2D)
COORDINATE TRANSFORMATION
EQUATION DEVELOPMENT
GLS FOR 2D CONFORMAL COORDINATE TRANSFORMATION
OUTLINE
I. Coordinate Transfo
GE10 Lecture 9:
OMITTED MEASUREMENTS
Engr. Jeark A. Principe, MSc.
Department of Geodetic Engineering (DGE)
Training Center for Applied Geodesy and Photogrammetry (TCAGP)
Omitted Measurements
When it
GE10 Lecture 4
1
Engr. Jeark A. Principe, MSc.
Department of Geodetic Engineering (DGE)
Training Center for Applied Geodesy and Photogrammetry (TCAGP)
At the end of the lecture, the student should be
PLOTTING GUIDELINES
Supplement to GE10 Lab Exercise 6
GE 10 LECTURE 12B
Engr. Jeark A. Principe, MSc.
Department of Geodetic Engineering (DGE)
Training Center for Applied Geodesy and Photogrammetry (T
GE 129 Lecture 5A:
Adjustment of Resection
(Adjustment of Indirect Observations)
Department of Geodetic Engineering
University of the Philippines
Diliman, Quezon City
Resection
Operation of determini
GE 129 Lecture 3:
Position Fixing By Distance
Position Fixing by Distance
A typical plane coordinate survey procedure
Distances between a set of known control
points and a point with unknown positio
Statistics 132
Handout 11
5.
The Case of k Related Samples
5.1
Inferences about Population Proportions
Cochran Q Test
Data: The data consist of nk observations, with one observation from each of k tre
UP School of Statistics Student Council
Education and Research
w erho.weebly.com | 0 [email protected] | f /erhoismyhero | t @erhomyhero
S132_Exer_002
Nonparametric Statistical Inference
Statistics
UP School of Statistics Student Council
Education and Research
w erho.weebly.com | 0 [email protected] | f /erhoismyhero | t @erhomyhero
S132_Exer_003
Nonparametric Statistical Inference
2nd Semest
S132 LE1 001
Nonparametric Statistical Inference
Statistics 132
Sample First Long Exam
Be sure to follow the steps in testing a statistical hypothesis. Define the parameter/s to be used in solving eac
UP School of Statistics Student Council
Education and Research
w erho.weebly.com | 0 [email protected] | f /erhoismyhero | t @erhomyhero
S132_LE1_002
Nonparametric Statistical Inference
Statistics