British Actuarial Journal, Vol. 21, part 3, pp. 458475.
doi:10.1017/S1357321716000143
Institute and Faculty of Actuaries 2016
Mis-estimation risk: measurement and impact
Abstract of the Edinburgh Discussion
[Institute and Faculty of Actuaries, Sessional
STAT 647 Spatial Statistics HW4
Sean Tolle
The data provide for Homework 4 was not provided with any units of length for the coordinates.
Since the coordinates were between 0 and 1, the coordinate system was assumed to be set in a two
dimensional plane. T
The Phase retrieval problem
The aim of this paper is to build up the theoretical framework for the recovery of
sparse signals from the magnitude of the measurement. We first investigate the
minimal number of measurements for the success of the recovery of
Question 1: A die is rolled, find the probability that an even number is obtained.
Solution to Question 1:
Let us first write the sample space S of the experiment.
S = cfw_1,2,3,4,5,6
Let E be the "an even number is obtained" and write it down.
E = cfw_2,
http:/www.sec.gov/cgi-bin/viewer?action=view&cik=52988&accession_number=000005298814-000173&xbrl_type=v#
JACOBS ENGINEERING GROUP INC.
COMMON SIZE STATEMENT OF INCOME
Years 2012, 2013, and 2014
Consolidated Statements of Comprehensive Income
12 Months End
ACCT2006 CORPORATE ACCOUNTING
BUSINESS COMBINATIONS
QUIZ QUESTIONS and SOLUTIONS
1.
On 1 December 2013, Grapefruit Ltd took over the operation of Lime Ltd.
At that date the assets and liabilities of Lime Ltd were:
Carrying Amount
Fair Value
Cash
20 000
20
Fluor Ratio Analysis
Ratio
Current Ratio
Acid Test Ratio
Accounts Receivable Turnover
Inventory Turnover
Assset Turnover
Profit Margin on Sales
Return on Assets
Return on Common Stock Equity
Earnings per Share
Payout Ratio
Debt to Assets Ratio
Times Inter
Q1 A study at Ulster University considered the correlation in fifteen SMEs between their
abilities to carry out Continuous Improvement (CI) and their cultures of Innovation. For each
of the fifteen firms a score was developed to indicate their capability
[u06a1] Unit 6 Assignment 1
Computer Lab: Test Hypothesis With Independent t Test
Resources
Computer Lab: Test Hypothesis With Independent t Test Scoring Guide.
Writing Feedback Tool.
Comprehensive Exam Rubric Feedback.
HollisSumGenderSAQ (Item 3 Reverse
Sampling Survey Project Report
Alcohol Consumption:
AUDIT, CAGE & beyond
Aditi Vijay
Akshat Raj
Aman Dayal
Artee Yadav
M.Sc. Statistics (Ist Year)
Page |2
Acknowledgements
This is to ascertain that the concerned group members have successfully completed t
Backpropagation Neural Network Training Algorithm
Input:
D : Dataset of training tuples with associated output classes
N : The neural network
Output:
N1 : The trained neural network ready to make classification
Method:
Initialize weights and biases (typic
Bobs Retirement Planning1
The Problem
Bob Davidson is a 46-year-old tenured professor of marketing at a small New England business school. He has a daughter,
Sue, age 6, and a wife, Margaret, age 40. Margaret is a potter, a vocation from which she earns
THE RACQUETBALL RACKET
It is early in 2014, and a friend of yours has invented a new manufacturing process for producing racquetballs. The resulting highquality ball has more bounce, but slightly less durability, than the currently popular high-qualit
The Joka Shoe Company
Joka Shoe Company (JSC) makes womens running shoes. Introduced 20 years ago, JSC has been manufacturing
and selling three styles of shoes. Management is considering whether the product line can be trimmed to reduce
administrative cos
Time Series Models for Business
EPBA Time Series Lecture 1
1 Introduction
1.
A time series is a set of observations, denoted
by xt, each one being recorded at a specific time
t.
Discrete Time Series: The set of times, T0, at
which observations are made
Time Series Models for
B i
Business
TSMB Lecture 3
1
3. Nonstationary
y Models
and Regression
In this chapter we will examine
the problem of finding
an appropriate model for data
that does not seem to be
generated by
a stationary
t ti
time
ti
series.
i
2
Time Series Models for
Business
TSMB Lecture 2
Models for Stationary
Processes
Time Series Model Building
2.1 Basic Properties of
St ti
Stationary
Processes
P
Autocovariance function (ACVF):
(h) = Cov(Xt+h, Xt ) for h = 1, 2,
A
Autocorrelation
t
l ti F
Gangopadhyay
EPBATSMBAssignment3
1. Identifytheorders(pandq)offollowingAPMA(p,q)processes.Determineiftheseprocesses
arecausaland/orinvertible.
a. Xt0.3Xt1=Zt
b. Xt2Xt1=Zt+0.8Zt1
c. Xt2.5Xt1+Xt2=Zt
d. Xt0.3Xt10.54Xt2=Zt1.2Zt2+0.2Zt2
2. Identifythefollowing
Gangopadhyay
EPBA TSMB Assignment 2
1.
For each of the following time series, state if the process is stationary or nonstationary. If
nonstationary, identify the features of the realizations that make it nonstationary.
a. Simulated data
Series
3.
2.
1.
0.
EPBA TSMB (Gangopadhyay)
Assignment 1
Problem 1: Below is the life expectancy for an individual born in the United States in
certain years. (Source: National Center for Health Statistics)
Life
Year of Birth
Expectancy
1930
59.7
1940
62.9
1950
70.2
1965
69
If the data is not normalized, or if there is presence of outliers, then correlation
Spearman Rank is a non-parametric test that can be used in place of the correlation coefficient of
Pearson. The Spearman Rank Correlation (also known as Spearman rho) is
a) 10 correct
There are 20 questions with 4 options each.
Probability of guessing a right answer each time is = 0.25
So, probability of guessing 10 correct answers is P(X=10)
(2010)( 0.25 )
10
( 0.75 )
10
= 0.0099
b) Probability of guessing at least 5 cor
CURVEFITTINGPROJECTLINEARMODEL
(LR -1): Purpose: To analyse the winning times for the Olympic Men's Shot
Put using a linear model.
Data: The winning times were retrieved from
http:/www.databaseolympics.com/sport/sportevent.htm?
sp=ATH&enum=300
OLYMPICS
SH
A normal 6 sided die is slightly weighted so that a 6 comes up 20% of the time, and other values
(1, 2, 3, 4, 5) come up 16% of the time each.
The die has probability 0.16, 0.16, 0.16, 0.16,0.16 and 0.2 of showing 1,2,3,4,5 and 6
respectively.
1. If I rol