The University of the South Pacific
Tutorial 2 Data Collection Sampling (Chapter 6)
EC203 Economic Statistics
Semester 1, 2013
Learning Outcomes
Different techniques of Probability (or Random) Sampling; including simple random, stratified, and
cluster .
K
The University of the South Pacific
Tutorial 2 ANSWERS Data Collection Sampling (Chapter 6)
EC203 Economic Statistics
Semester 1, 2013
Learning Outcomes
Different techniques of Probability (or Random) Sampling; including simple random, stratified, and
clu
The University of the South Pacific
Tutorial 3 ANS Graphical and Tabular Descriptive Methods (Text Ref. :Ch.2)
EC203 Economic Statistics
Semester 1, 2013
1. For following data entries identify:
I.
The level of measurement for each (i.e. whether the possib
Once that has been achieved, we with
the help of your
process engineers usually find that
there are possibilities to
further optimize process behavior.
For instance, we might start by assessing
the performance of
your DCS PID controllers, monitoring
how t
Actual constraint
MPC provides multivariable control
and is able to reduce variance
MPC provides optimal
control and automatically
shifts the target
Economic
optimum
Constraint 2
Constraint 3
Constraint 1
Operators
preferred
operating region
space models to accurately account for
complex process
dynamics with a reduced number of
parameters. Additionally,
this technology makes it possible to
implement explicit
state estimation by using the Kalman
filter to achieve early
and accurate disturbanc
Stepwise optimization and continuous
collaboration
Process optimization is a longterm
undertaking based on a
relationship of collaboration between the
customer and ABB.
If the customer has a process problem or
simply wishes to
enhance the performance of
prices, the complexity of the plant, and
the high reliability
requirements
for
steam
and
power
supply. To improve
operational stability and flexibility and
reduce energy costs,
ABB Predict & Control can be used to
coordinate control and
optimization.
The
trip causes other equipment to trip,
thereby reducing plant
outages and production losses. Verified
savings of 2% in
powerhouse energy costs have been
achieved, equating to
a payback time of less than six months.
Savings come from
the maximization of back
extra
measurements
that
provide
supplemental information
about the internal state of the process.
Better process
state estimation means better control and
superior plant
performance.
Maximum flexibility at all times
ABBs control algorithm is designed to
p
track record in achieving major and
measurable improvements
in plant and business performance:
 Increased throughput
 Minimal quality giveaway
 Increased profitability

Enforcement
of
safety
environmental operating
constraints
 Reduced energy consump
 Userdefined trajectories for setpoints,
feedforwards and
constraints
 Native representation of integral models
(like level) makes
it easy to control levels
 Online update of models and tuning
parameters based on
process conditions
The
Kalman
filter
primary energy such as gas or external
power supply.
APC
design
for
powerhousewww.abb.com/oilandgas
Rev 11503
the
Table of Contents for the 2nd Edition of
Process Dynamics & Control
By
cuttingedge
ABB
technology
that
replaces the typical MPC
collection of singleinput/singleoutput
(SISO) step response
models
with
a
true
multiple
input/multipleoutput (MIMO) state
space model.
Traditional MPC uses finite impulse
response models, which
statistical
process
control
and
multivariate statistical
process control.
IMP is a native Windows clientserver
software
package
for
the
offline
development (IMP Model Builder) and
online deployment
(IMP Online) of inferential models.
IMP Model Builder
Th
nonlinear
dynamic
processes.
This
approach utilizes the
simplicity and robustness of linear
models to improve the
performance of model predictive control.
Offline and online capabilities
Predict & Control is a native Windows
clientserver
package
compris
unrivaled success rate in improving
productivity in
a wide variety of industrial processes.
ABB
Advanced Process Control
5
Inferential Modeling Platform
Creates nonlinear inferential models
from process data
Inferential Modeling Platform (IMP) is a
softw
for application configuration, data preprocessing, model
building,
controller
tuning,
offline
simulation and analysis.
The online package comprises P&C
Builtin Client Operator
Interface, and P&C Engine the
computational core of Predict
and Control. P&C O
optimization with prioritized control
targets and timedomain
tuning parameters. Multiple levels of
constraints are difficult
to
tune
without
a
sequential optimization
multiobjective,
algorithm
like
P&Cs.
Where
competitors controllers use a
gain scheduli
ABBs Advanced Process Control (APC)
is a set of worldclass
control and optimization products, which
are fully integrated
into a uniquely powerful suite that meets
the requirements of
every process application, from a smallscale singleunit plant
to a lar
installation, and easy diagnostics and
programming. The APC
suite is based on a set of common
components, which give
the products a uniform look and feel and
provide a familiar
interface for engineers and operators.
ABBs advanced solutions encompass
the f
statistical regressions, statistical process
control (SPC) and
multivariate SPC (MvSPC)
 APC Performance Manager  allows
seamless continuous
optimization
by
tracing
performance and presenting
APC
further possibilities for improvements
Connectivity throu
The University of the South Pacific
Test 2
EC203 Economic Statistics
Semester I, 2014(b)
Name
ID
Tutorial day & Time
Test 2 (15%) Probability and Probability distributions
Instructions
1.
2.
3.
4.
5.
6.
7.
Permitted Materials: Calculator
Provided Material
EC203 [Semester 1, 2015] Solution Test 1 Version B
MC
1.A
2.A
3.B
4.D
5.D
6.D
7.C
8.D
9.C
Section B Q1
a) Laptops imported from USA.
b.
c) (any one)
1. Some clearly identifiable groups of interest may be underrepresented.
2. May increase sampling error d
Wlw
CHAPTER 1: The Pacific Ocean
Aithough the fine oceans have
an average depth of about two
and onewhalf to three mites, the
Pacific Ocean has the deepest
point of ah the oceans. This is
the Challenger Deep, which is
about seven rhites
DESCRIPTIVE REPORT
The figures below show a descriptive statistics summary on the overall performance of the EC203
students.
Grand Total (100%)
Mean
48.68292683
Standard Error
1.055179543
Median
50
Mode
50
Standard Deviation
13.51289141
Sample Variance
18
The University Of The South
Pacific
EC203 Economics Statistics
Semester 1, 2017
Assignment 1
Group members
Diviyashna Dut
s11133415
Monesh Deepak Lal
s11133383
Section A
Part 1
a) 2.88.1 children per women
b) 1.17.5 children per women
c) Fewest children
Section 1 : Introduction
Country
Variables
China
CO2 emissions from gaseous fuel consumption
Total Greenhouse gas emission
Variable measurement
units
Variable Simplified
Measurement units
Dependent variable
(Y)
Independent Variable
(X)
Time Period (N)
I
The University of the South Pacific
Tutorial 8 ANS
EC 203 Economic Statistics
Chapter 11: Estimation: Describing a single population
Coverage
Properties of estimator.
Interval estimation for mean when known.
Interval estimation for mean when unknown.
Inte
Country N
Australia
Australia
China
China
Country CoSeries Name
AUS
CO2 emissions from gaseous fuel consumption (kt)
AUS
Total greenhouse gas emissions (kt of CO2 equivalent)
CHN
CO2 emissions from gaseous fuel consumption (kt)
CHN
Total greenhouse gas em