Computer Fraud And Identity Theft

Computer Fraud And Identity Theft
Abstract
In today's world where computers, cellular phones, wireless internet connections and electronic
transactions are common place norms, maintaining ones identity can be a challenge. In 2012 the
United States population was 314.1 million people, in the same year, 75.6 percent of households
reported having a computer. (Government Census, 2012) With this high population and electronic
use, one could extrapolate that there is high risk for computer fraud and identity theft. For example
consider these statistics in 2013, identity theft complaints accounted for 14% of all complaints. The
most common form of reported identity theft was government documents/benefits fraud, 34%,
followed by credit card fraud, 17%, phone or utilities fraud, 14%, and bank fraud, 8%. Forty–one
percent of identity theft complainants reported whether they contacted law enforcement. Of those
victims, 74% notified a police department and 61% indicated a report was taken. (Government
Census, 2012) There are many ways to counter identity theft, some being not to give out personal
data or to make sure to properly destroy/secure all important documentation. These methods of
protection seem quite feasible and often time practical, however with the rate at which identity theft
occurs the validity of these protections might come into question. Therefore this research proposal
begs the questions of how effective are these counter measures, to what degree are the counter
measures followed by the victims, and
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Nt1310 Unit 4 Assignment 1
mu_I} (R_I(widetilde{S}_I) – T_I^*) ge V_I(S_I^*)^{{1/mu_I}} (R_I(S_I^*) – T_I^*)
end{equation*} Since $R_I(S_I^*) ge T_H^*$, according to Equation (ref{Equ: DefTi}), we
have: $T_I^* = mu_I T_H^* +(1–mu_I) R_I(S_I^*)$. After plugging $T_I^*$ in the above
inequality, it follows that: begin{eqnarray}label{Equ: l2Equ3} &V_I(widetilde{S}_I)
^{1/mu_I}& (R_I(widetilde{S}_I) – mu_I T_H^* – (1–mu_I) R_I(S_I^*)) ge V_I(S_I^*)
^{{1/mu_I}} (R_I(S_I^*) – mu_I T_H^* –(1–mu_I) R_I(S_I^*)) nonumber Rightarrow
&V_I(widetilde{S}_I) ^{1/mu_I}& (R_I(widetilde{S}_I) –T_H^*) ge (mu_I
V_I(S_I^*)^{{1/mu_I}}+ (1–mu_I) V_I(widetilde{S}_I)^{1/mu_I}) (R_I(S_I^*) – T_H^*)
end{eqnarray} Multiply inequality (ref{Equ: l2Equ3}) by $V_I(widetilde{S}_I)^{1 ... Show more
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$square$ end{proof} One key observation is that: the newly defined local assortment optimization
problem at lowest level nests is same as constrained assortment optimization problem under
multinomial logit model, which is extensively studied in cite{rusmevichientong2010dynamic}. By
using the polynomial –time algorithm that is proposed in cite{rusmevichientong2010dynamic}, we
can solve this local assortment optimization by only searching $O(N)$ assortments, where $N$ is
total number of products within that nest. section{Candidate Assortment Construction}label{sec:
Construction} Denote total number of products as $n$, and $C = max C_I$ . begin{theorem}
$forall I in V$, we can construct the collection $mathscr{A}_I subseteq Im_I$ such that
$|mathscr{A}_I| le Cn$, which needs $O(n log n)$ operations. end{theorem}
section{Constrained Assortment Optimization Algorithm} label{sec: Alg} We use $mathscr{A}_I
subseteq Im_I$ to denote the collection that contains an optimal solution at node

Informal Sector Essay
Since the informal sector is believed to make a great contribution to an economy, there are a number
of research papers which have been done in this sector. Some research has been done in relation to
small–business participation in the informal sector. A prime example is from Trinidad and Tobago,
considered as an emerging economy, whereby people have the perception of avoiding tax while
performing their business and is the reason why people engage in the informal sector. The focus is
on socioeconomic, demographic, and attitudinal characteristics that influence people to run their
small business (Sookran & Watson, 2008).
Moreover, Sookram & Watson (2008) in their research on 'Small–business participation in the
informal sector of an emerging economy' explain that the word "informal sector" refers to the
production of goods and services for market orientation, which is not captured in the estimation of a
country's GDP whether these activities are legal or illegal. The contribution of the informal sector to
the national economy in the third world economies ranges from 20 to 70 %. It has been commonly
thought that the informal sector is the sector linked with the poor and marginalized. However, in
reality this sector attracts many people regardless of their social status and educational background.
Thus, clearly policy makers need to look at this sector as it offers great economic advantages to both
poor people and the country.
The purpose of the study conducted by Sookram &

Multivariate Statistical Analysis : Natural And Physical...
Multivariate Statistical Analysis
Statistical methodology designed to obtain information from data sets that include simultaneous
measurements on many variables is called multivariate statistical analysis (1). Multivariate statistics
helps to study how the variables are related to one another, and also how they work in combination
to differentiate between the cases on which the observations are made. Several research disciplines
such as biology, medicine, environmental Science, Psychology, Sociology, Economics, Education,
Archaeology, Anthropology have broad applications of Multivariate statistical analysis (2).
Numerous interesting research questions about natural and physical processes are so complex that
they require multivariate ... Show more content on Helpwriting.net ...
The usual regression method does not work when we are given a binary response variable. In these
situations we should think about using the logistic regression (4).
Considering the following model estimated regression equation (equation 1) It is called as simple
Logistic regression, because there is only one predictor and also the exponential function is never
"0" or negative.
There are some other models available for dichotomous and non–dichotomous categorical
outcomes. Probit regression: A model used for binary outcomes, but instead of the logit
specification, the probit uses the cumulative distribution function for a standard normal distribution.
Multinomial Logistic Regression: A model used for outcomes that are nominal, e.g., blood type (A,
B, AB, O). Ordinal Logistic Regression: A model used for outcomes that are ordinal, e.g., Likert
scale questionnaire (excellent, very good, good, fair, poor).
Simple logistic regression application involves one dichotomous variable and one independent
variable. Multiple logistic regression application involves when there is a single dichotomous
outcome and more than one independent variables (4) (5).
Applications in Bio–Medical Research:
Logistic regression is one of the widely used tool in fields such as bio–medical research, medical,
epidemiology, social sciences, engineering, ecology, psychology and marketing. For instance
logistic regression can be used to

A Strategy For Modeling Salton Sea Basin Future Climate...
Results: A Strategy For Modeling Salton Sea Basin Future Climate Scenarios Based On
Relationships Between Evapotranspiration And Precipitation
A comparison of the averaged weather station datasets versus the historic individual weather station
datasets was made for both precipitation and Eto. The averaged monthly dataset preserved
seasonality for both precipitation and Eto as illustrated in the figures. Notably, for the months of
February, March, and April, the average monthly precipitation volume was lower than the actual
weather station historic data. This occurred for two reasons: 1) the disparity in the number of
observations between the two weather station datasets and the average resulting in the largest
number of observations ... Show more content on Helpwriting.net ...
The results of the two test statistics differed at times, i.e., listing two different curves as providing
the "best" fit. In the fore–mentioned situation, a final decision pertaining to the "best" fit was made
based on a visual assessment of the figures.
Precipitation Events and Eto Levels
The importance of using monthly data instead of annual data for the Salton Sea Basin. Further, the
two models: (1) (Logit Y1,..........12) Month = Constant + X1 Prcp, and (2) (Logit Y1,..........12)
Month = Constant + X1 Eto, established that some months were significantly different than others
concerning the amounts of precipitation and Eto, respectively. The relationships between the
duration of precipitation events ('CatEvent') on the volume of precipitation ('PrcpAmt' and 'CatVol'),
and also on Eto volumes. A plot of the precipitation and Eto observations, percentage or percentage
of observations of a given magnitude, respectively, by month was also made.
The negative relationship between precipitation and Eto was tested statistically using two
multinomial logistic regression models and one binomial logistic regression model, respectively: (3)
(Logit Y0,...4) PrcpAmt = Constant + X1 Eto, (4) (Logit Y0,....5) CatEvent = Constant + X1 Eto,
and (5) (Logit Y0,1) RainEvent = Constant + X1 Eto. The

Everglades Restoration
Considering spatial variability of public's preference for the Everglades restoration Everglades, the
largest subtropical wetland of North America, has encountered anthropogenic perturbation since the
last quarter of 19th century when canals were built and peatlands were drained for economic gain
(Godfrey and Catton, 2011). Since then, the system has been exploited, drained, polluted and
changed from its natural setup to escalate and widen the potential services from it. The present state
is a highly regulated system to buttress economic productivity and fulfill several regional demands.
The Comprehensive Everglades Restoration Plan, one of the world's largest restoration initiative,
aims to restore, protect and preserve the water resources of central and southern Florida (National
Research Council, 2014). While the restoration program is built on a foundation of retrospective
science backed by several years of sophisticated research on understanding the Everglades and
similar ecosystem (Estenoz and Bush, 2015), the human dimension of restoration was not studied
adequately(Clarke and Dalrymple, 2003; Kranzer, 2002; National Research Council, 2014).
Particularly, the spatial extent of residents' preference or the heterogeneity of their opinion is
important for CERP as the plan aims to restore ecosystem without compromising the present
services (e.g. flood control, water for agricultural, urban and industrial uses etc.), which are also
spatially related. Milon et al., (1999) conducted a survey to ... Show more content on
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Proper formation of the spatial variables for the choice model considering the scale, extent and
characteristics will provide realistic and useful insight about local or regional preferences. Similarly,
MAU technique that can incorporate spatial data maintaining its distinct characteristic will ensure
reliability of the

Description of Conjoint Analysis
Conjoint Analysis Like qualitative researchers, quantitative researchers also have a number of
approaches available to them today. The selection of the research approach will depend on what type
of information is being sought, what type of information is available, and the goals of the researcher.
One research methodology that is gaining increasing popularity is conjoint analysis, a quantitative
methodology that is discussed further below, followed by a summary of the research and important
findings in the conclusion. Review and Discussion Description of Conjoint Analysis and Examples
of Business Applications Conjoint analysis is a quantitative methodology that measures the
perceived values of various possible product designs (Calantone & Di Benedetto, 1990).
Respondents participating in conjoint analyses view several variations in product concepts and then
assign ranks with respect to their individual preferences (Calantone & Di Benedetto, 1990). The
analysis of these responses can be used to identify the respective utility that is associated with each
of the attributes ranked by the respondents, and these findings can then be used to identify the
combination of attributes that consumers would likely most prefer (Calantone & Di Benedetto,
1990). According to Orme (2009), "Conjoint analysis has become one of the most widely–used
quantitative methods in marketing research. When used properly, it provides reliable and useful
results" (p. 1). Although there are a number

Foreign Investment And Expanding Trade Relations
In today 's developing economies the competition to attract foreign investment and expanding trade
relations has become the foremost economic strategy to satisfy the quest of the society for rapid
economic growth. The failure of inward–looking economic policies to change the trajectory of
decades long stagnated economies forced countries to adopt outward–looking trade policies and
market economy. As a result, attracting foreign investment and promoting exports emerge to be the
core economic and trade strategies. Foreign investment is believed to provide multidimensional
benefits to the host economy both directly and indirectly. The main direct benefit is the capital
inflow that fills the finance gap between the required investment and ... Show more content on
Helpwriting.net ...
The rapid industrialization of developing countries sought to bring about economic convergence
among economies depends on the possibility of free flow production knowledge and information. At
the center of this argument is the externalities that emanate from foreign invested as well as
exporting firms.
The spillover effects that arise from foreign direct investment (FDI) has amassed an extensive body
of literature in the past two decades. Most of these studies focused on the productivity and
knowledge gains towards domestic firms. Such spillovers are thought to arise as a result of
horizontal and vertical linkages between foreign and domestic firms. The early studies
citep{blomstrom, Kokko, sjoholm, haddad, aitken} who follow the pioneering work of cite{caves}
focuses on externalities that affect the productivity of firms within the same industry. A review of
such studies by cite{gorg} pointed out that the evidence for intra–industry productivity spillover is
weak or at best mixed.
Unsatisfied with the lack of empirical evidence to support horizontal spillovers the research started
to emphasize vertical linkages between domestic and foreign firms. Amongst cite{javorcik} argues
that previous studies may have been looking for spillovers in the wrong place where foreign
investors have the incentive to prevent information leakage that would enhance the performance of
their local competitors. The tendency to prevent diffusion of knowledge is probably minimal or

Comparing Logit And Probit Models Essay
In Logit and Probit models, a dependent variable takes only two values that represent the occurrence
of an event (yes or no) or a choice between two alternatives. In the current case, to model choice
status of each individual WTP for improved solid waste management respondents differed in age,
educational attainment, income, sex and other observable characteristics. These are denoted by S. In
the dichotomous choice method, individuals are assumed to have utility function, U, income (I), and
a set of conditioning factors (S): U(I; S)
Each respondent was confronted with a specified bid value, BID, which she or he may contribute
towards the management initiative. It is assumed that the individual would accept a suggested BID
to maximize his or her utility under the following condition and reject it otherwise (Hanemann,
1984):
U(1, I –BID; S)+ ε1 ≥U(0, I; S) + ε0
In the current case, ε1 and ε0 are considered as independently distributed random variables with
zero means. Therefore, the probability that a household would decide to pay for the proposed
improved solid waste management for Delhi is the probability that the conditional indirect utility
function for proposed intervention is greater than the conditional indirect utility function for the
status quo. The dependent variable is dichotomous and equals 1, if the ith household is willing to
pay a bid and 0, otherwise. The general form of the estimation can be written as:
〖

Multivariate Statistical Analysis : Natural And Physical...
Multivariate Statistical Analysis
Statistical methodology designed to obtain information from data sets that include simultaneous
measurements on many variables is called multivariate statistical analysis (1). Multivariate statistics
help to study how the variables are related to one another, and also how they work in combination to
differentiate between the cases on which the observations are made. Several research disciplines
such as biology, medicine, environmental Science, Psychology, Sociology, Economics, Education,
Archaeology, Anthropology have broad applications of Multivariate statistical analysis (2).
Numerous interesting research questions about natural and physical processes are so complex that
they require multivariate models and multivariate statistics. There are several types of multivariate
models such as Multidimensional Scaling, Principal Components Analysis, Cluster Analysis, Linear
Mixed–Effects Modeling, Canonical Correlation, Multivariate Factor Analysis, Logistic regression
and so on, each with its own type of analysis (3).
Logistic Regression
Introduction:
Logistic regression is also called Logit regression or Logit mode. It is developed by David Cox in
1958. Logistic regression is an analogous method for the multiple linear regression. Unlike multiple
linear regression, here the outcome or response variable (categorical) is all or none that is the
dependent variable is dichotomous or binary. Here the response is defined as an indicator (dummy)

Concept And Measurement Of Poverty
2.0: Introduction:
This part reviews some of the available literature on concepts, theories and previous research
findings pertaining to the research problem so as to establish the theoretical and empirical base of
the study. Literature review is used by the researcher to bring the reader update with current
literature on a topic and forms the base for another goal, such as future research that may be needed
in the area. It is also used to provide solid background information under the study. The literature
reviews aims at finding the gap between what other authors have explained theoretically and
empirically and what has not been explained. The knowledge gap needs to be established and fitted
by the researcher.
2.1: Concept and Measurement of poverty
2.1.1: Definition of poverty
Poverty of an individual or household is defined as a state of having an income or consumption
expenditure which is below a certain level/standard known as the poverty line (Bigsten ; Abebe,
2003). Townsend (1985) defined poverty as not only a failure to meet minimum nutrition levels but
also as a failure to keep with a standard of living prevailing in the society. Thus according to
Townsend a household is considered as being poor if and only if its standard of living is below that
of the society. Poverty on the other hand can be observed as the condition of a household being
unable to meet basic needs including food, shelter, education etc. (World Bank, 1996).
According to the economist a household

Bus Transit And Mass Transit
1 INTRODUCTION
1.1General
In urban areas due to expansion of cities and population growth the major problems which arise are
more travel time and more travel cost. For Developing countries like India, China, Brazil etc. taking
affordability and mobility into account the policy makers induced public transport system for
movements like inter–urban or intra–urban. Various examples are Bus Transit & Mass Transit. Due
to bigger city size and fixed routes of these systems its accessibility varies for different user. These
predefined fixed routes do not take into account the whole catchment area from where the users are
using. Among these users there are some users which use daily bases are known as commuters. Such
commuters access/egress the transit system by a variety of modes such as by walking, bicycle,
manual tricycle, motorized 2–3 wheeler, feeder bus services and cars. Each mode has its utility
within certain distance range (Khistey and Sriraj 1996) . Increase in city size has reflected in the
utility of various modes, utility of motorized vehicles have increased whereas the utility of non–
motorized have decreased. From socio–economic point, these include loss of employment, slow
elimination of environment friendly modes like bicycles, manual tricycles and walk and increase in
population levels. The mode choice for access and egress varies for various users but for policy
makers it is very important to identify the factors which are influencing these mode

Regression Analysis For A Dependence Method
Regarding the testing of the hypotheses of this research, regression analysis or structural equation
modelling techniques is best suited for a dependence method (Hair et al., 2014). We employed
regression analysis to specify the extent to which the independent variables predicted the dependent
variable. The analysis conducted in this study was therefore intended to test the hypotheses of the
study. The regression output provided some measures which allow assessment of the hypotheses.
Following from the hypotheses, Brand Engagement was used as the dependent variable while the
independent variables consisted of Monetary Savings, Exploration, Entertainment, Recognition, and
Social Benefit. Results from the model assessment are presented in the Table VI. Insert table VI
Results from the model assessment indicate strong and significant reliabilities among the constructs
used in the study (F = 87.362, Prob.F–stats < 0.001). This was followed by Exploration (β = 0.102, t
= 2.271, P = 0.024 < 0.05), as well as Entertainment (β = 0.081, t = 1.712, P = 0.068 < 0.10).
Although Recognition was positively related to Brand Engagement, it was not statistically
significant (β = 0.051, t = 1.084, P = 0.279 > 0.05). It was however discovered that Monetary
savings was inversely related to Brand Engagement (β = –.009, t = –0.194) as well as statistically
not significant in the current study (P = 0.846 > 0.05). In consequence, hypotheses one and four (H1
and H4) were rejected in our study

Gender Wage Discrimination in Pakistan
| Gender Wage Discrimination in Pakistan | Evidence from Pakistan 2008/09 and 2010/11 | | | |
Table of Contents Introduction 2 Literature Review 2 Methodology 3 Variables Used –
Characteristics of Workers 5 Results 7 Discussion 7 Bibliography 8 Appendix A 9 Selectivity Bias
Logit Regression Results: 9
Introduction
This paper explores the dynamics of gender wage discrimination in Pakistan for two data sets;
Labour Force Survey for the year 2008/09 and 2010/11. We will explore whether or not women are
discriminated against, as it has been suggested for a predominantly Islamic country like Pakistan.
Labour theory addresses many reasons for wage discrimination. For the purposes of this research we
will ... Show more content on Helpwriting.net ...
The signs of education are expected. For the data set of 2008/09, signs for education are positive
which does not support theory. Even after efforts to remove multi–colinearity, they still show
positive signs. Most of the variables in the regression are also insignificant.
However, when we take the data for LFS 2010/11, and correct it for selectivity bias, we get much
better results. Most of the variables are significant as well as show the correct signs. (The same
algorithm was applied to both the data sets, and the same variables have been taken).
Results of Logit models for correcting selectivity bias are attached in Appendix A.
Variables Used – Characteristics of Workers Summary tables from LFS 2010/11 1. Age * Theory
suggests that this is one of the most important determinants of people's decision to work.
2. Marital Status * This variable was taken as a dummy variable in the regression. * It is a
significant variable in the decision to work, especially in developing economies like Pakistan. 3.
Province * This is also taken as a dummy. The Baluchistan province was omitted from this analysis.
However, the calculations of the Oaxaca Blinder method take this omitted variable into account.
This is because the method takes the vectors of the estimated regression equation.
4. Region * Whether a person is from a Rural or urban background has impact on the

Literature Review On 3p Service
2. Literature Review
In recent years, Third Party Logistics (3PL) service providers play a very important role in a supply
chain of an organization. A brief literature review is given in this section of the paper. Tate (1996)
identified seven factors (compatibility, deep understanding of a partner's business needs, open
communications, commitment, fairness, flexibility, and trust) that improved long– term relationship
between 3PL and their customers. Logan (2000) used agency theory to help in bonding
3PL/customers relationships. It is postulated that, cost reduction and services improvement criteria
are most expected by clients to avoid conflicts with their 3PL. Fawcett and Smith (1995) identified
five criteria's to evaluate the 3PL performance, ... Show more content on Helpwriting.net ...
This research paper investigated and quantitatively modeled an approach of selecting 3PL service
providers for Indian cement manufacturing industries. The results of the research show that, the
compatibility with the users & cost of service are the top two criteria's, whereas, geographical
spread and range of services provided & flexibility in operation and delivery are the criteria's having
very low rank (19 &20). It is also found that, an AHP approach gives logical results & helps the
managers of the industry to visualize and analyze the affect of various selection criteria's on the final
decision to be taken. This is how it directs the 3PL service providers selection towards a logical
decision making process, which can be advantageous to all the cement manufacturers wanting to
hire third party for providing logistics services in the cement

Case Study On Brand Equity
CHAPTER 1
INTRODUCTION
1.1 Introduction to Internship:
Brand Equity is the added value endowed by the brand to the Product. Although the idea of using a
name or a symbol to enhance a product's value has been known to marketers for a long time, brand
equity has gained renewed interest in recent years. Brand managers realize that after years of look–
alike advertising and over copying with me–too brands, they now live in a world of product parity.
The ensuing price competition through short term price promotions reduces the profitability of
brands leading manufactures to examine ways to enhance loyalty toward their brands. In addition,
facing with the increasing power of retailers, manufacturers of consumer products realize that
having the ... Show more content on Helpwriting.net ...
The probability of the choice is estimated in a multinomial logit model by using market level
scanner data
10) Ferjani (2009):Built a conjoint based brand attribute interaction model, and tested its fit while
analyzing five other specifications.
11) Goldfarb (2009): Brand equity is conceptualized as the unobserved utility component opposed to
kamakura and russel (1993) who measures brand equity with the intercept term of the utility
function.
12) Boulding (1994): A company's protection against competitive attacks increases as the more
differentiated brands results in lower price elasticity can achieve a more successful brand extension.
13) Chintagunta (2005): Intrinsic brand value is also measured with the intercept term of the utility
function are also measuring brand equity with the intercept term.
14) Kapferer (2008): The concept brand equity has become a central marketing concept due to the
increasing scientific and business interest in brands.
15) Berry(1995): Brand equity is conceptualized as the unobserved component of utility of

Methodology and Models for Residential Self Selection
METHODOLGY AND MODELS FOR RESIDENTIAL SELF SELECTION: IMPACT ON
TRAVEL BEHAVIOR Introduction: Self–selection in this context refers to "the tendency of people
to choose locations based on their travel abilities, needs and preferences" (Litman, 2005 p. 6).
Sources for Residential selection are: attitudes and social demographic traits. With residential to the
latter, an example of self–selection is that low–income and zero–vehicle households may choose to
live in neighborhoods with ample transit service and hence use transit more. In this case, it is not
good transit facilities, but the households' economic constraints that have a true and direct influence
on their choice of transit model. Today urbanization is increasing rapidly with global opportunities
and economic development of the country. So, there are more number of people are migrating from
other areas to Urban. The density of the population increases, but the infrastructure like
transportation facilities have not improved that much. Then there is a cause of Traffic congestion as
well as increasing the fuel consumption. Urban areas are developing very fast and sprawl all over
the sub– urban areas. Already central areas of the cities are overcrowded, So, then the people are
moving to suburban areas for living. Then the term Residential Self selection plays an important role
on the travel behavior of the individual. Travel behavior of the person depends on the so many
factors including the income level of the

The Dependent Variable, Perception Of Safety On Campus Essay
The dependent variable, perception of safety on campus, was measured by an item on the
questionnaire asking students to indicate their level of satisfaction on feeling safe on campus.
Respondents rated their satisfaction on a scale from 1 (Very satisfied) to 5 (Very dissatisfied).
Responses to this item were recoded into three categories. Very satisfied and satisfied were
combined and recoded 0 (Satisfied). Undecided was recoded 1 (Undecided). Very dissatisfied and
dissatisfied together were recoded 2 (Dissatisfied). Recoding was deemed necessary for easier
interpretation of findings (See Table 1). Independent Variables The variables, perception of officers'
fairness and impartiality, fear at night, and violence in residence halls, were operationalized by an
item on the questionnaire asking students to indicate their satisfaction or agreement. Responses to
this item ranged from 1 (Very satisfied) to 5 (Very dissatisfied). Similarly, responses were recoded
into three categories 1 (Satisfied – a combination of both satisfied and very satisfied responses), 2
(Undecided) or 3 (Dissatisfied – a combination of both dissatisfied and very dissatisfied responses).
Gender was a dichotomous variable, with male surveyees coded 1 and female surveyees coded 0.
Race or ethnicity was indicated by an item on the questionnaire that asked respondents to specify
which group they considered themselves a member of Caucasian/White, African American/Black,
Hispanic (Mexican, Puerto Rican, etc.),

Does Spousal Income Affects Women's Labor Force...
Literature does not agree upon how spousal income effects a women's labor force participation, but
the effect on women's work choice is constant. In the years 1960 to 1977 a total of 8.7 million
women entered the labor force, 58.5% had spouses with above average incomes (Ryscavage 1979).
This data supports the argument that high spousal income positively affects the woman's labor force
participation. In contrast Shaw (1992) argues that it is possible that a wealthy husband negatively
affects the wife's participation in the labor force. She states that because of spousal income being
above average it gives the woman economic stability to not join the labor force. Using the Current
Population Survey March Supplement, Park (2010) finds that as

Mexican Non-Citizen Destination: A Case Study
To study the destinations of Mexican non–citizen destination, we can suggest using the Synthetic
Control Method, the methodology proposed by Abadie (2010). This method relies on the probability
that a Mexican non–citizen moves to a different state – and their predictors in order to generate a
convex combination of states that serves as a better control group.
A pooled sample data can be obtained from the ACS (American Community Service), from 2000–
2012. This is a time frame where tough interior immigration enforcement is seen. The ACS contains
data on migration status during the last year, present state of residence and country/state of residence
in the last year.
To disentangle the effects of LAWA and SB 1070, we can focus to look at time frames of pre–
LAWA, post– LAWA, pre–SB 1070 and post–SB 1070. ... Show more content on Helpwriting.net ...
We can ignore the states not having passed immigration policies – an outcome much like the next
point. We then identify a convex combination of states from that donor pool that most closely
resembles Arizona in terms of pre– intervention outflows of Mexican non–citizens and a number of
predictors. We compare Arizona to states that exhibited similar labor market trends, including a
thriving construction sector (as seen before), prior to LAWA and SB 1070. These can be Nevada,
California, New Mexico and Texas.
The main destinations of non–citizen Mexicans are: California, Texas, New Mexico, Nevada, Utah
and Colorado. Setting up a probability of movement of such non–citizen Mexicans across these 6
destinations, we set another broad destination: rest of the US. It is important to note here that a
multinomial logit assumes that adding another destination does not affect the relative odds of
choosing any of the US destinations. Our estimates should provide a set of probabilities for the 8
mobility choices as discussed

Demand Estimation Has Been At The Heart Of Many Studies
Literature Review Demand estimation has been at the heart of many studies that focus on questions
regarding market power, merger and acquisition, research and innovation and valuation of new
brands in differentiated–products industries. Under the framework of demand estimation, Bresnahan
(1987) constructs equilibrium models of oligopoly under product differentiation and studies the
competition and collusion in the 1995 price war in the American automobile industry. Gasmi,
Laffont and Vuong (1992) study the collusive behavior on price and advertising in the U.S. soft–
drink market， which is dominated by Coca–Cola and Pepsi–Cola, after obtaining a full information
maximum likelihood estimation of demand functions. Hausman, Leonard and Zona ... Show more
Firstly, there would be a large number of parameters to be estimated. For example, in a log–log
demand system, where logarithms of quantities are linear functions of logarithms of all prices,
without additional restrictions, we would have 10,000 parameters if there were 100 differentiated
products in the market. The second concern introduced when doing demand estimation for
differentiated product is the heterogeneity in consumer tastes. Dixit and Stiglizt (1997) suggest a
representative consumer approach to deal with this. They assume that consumer preferences are of
the right form so that an average consumer exists; there exists a demand system that lends itself to
the level of differentiation observed in the marketplace. However, the required assumptions are
strong and empirically false for many applications (Nevo, 2000). The above two problems are
addressed by logit demand model (McFadden, 1973). The logit model solves dimensionality
problem by projecting the products onto a space of characteristics; in this way, the dimension of the
attribute space instead of the square of the number of products becomes the relevant size. However,
due to the restrictive way of modeling heterogeneity and the property of independence from
irrelevant alternatives (IIA property) in the logit model, substitution pattern between products is
driven completely by

Essay about Case Study
1. Table 8.1 shows results of an eight–center clinical trial to compare a drug to placebo for curing an
infection. At each center, subjects were randomly assigned to two groups. Table 8.1 Clinical Trial
Data for Problem 1 a. Perform two different tests (Breslow–Day, and likelihood ratio test) for
whether the drug effect on curing an infection is the same over eight centers. i) Breslow–Day test:
The B–D test of homogeneity tests for whether the drug effect on curing an infection is the same
over eight centers gave a chi2 = 8.0 with df=7 and p–value = 0.333. Therefore since the p–value is
> 0.05, we fail to reject the null that the drug effect on curing an infection is the same over the
eight centers. The drug effect ... Show more content on Helpwriting.net ...
What is your conclusion with regard to the effect of the drug on curing the infection? What is the
odds ratio using the CMH method? The OR for curing the infection comparing drug with placebo,
adjusting for the centers is 2.175, with a p–value of 0.011 which is less than 0.05 and therefore
significant. We can conclude that the drug is 2.175 times better at curing the infections after
adjusting for centers compared to the placebo. Using the CHM Method: From the CMH method
above, the combined OR=2.13, with a p–value of 0.0115 which is significant at the 0.05 level.
Therefore the drug is 2.13 times more effective at curing the infection after adjusting for centers
compared to the placebo d. Perform a new logistic regression to find the odds ratio for curing the
infection without adjusting for the centers. Which measure, adjusted, or unadjusted odds ratio, do
you prefer to use when you investigate the drug effect on curing the infection? From the output
above, the OR without adjusting for centers is 1.5 with a p–value of 0.108 which is not significant at
the 0.05 level. Therefore, I will prefer to use the adjusted measure when investigating the drug effect
on curing the infection. e. (Extra Credit) Perform a likelihood ratio test on whether the treatment is
different among the centers, using the deviance measure. data medtreatment; input center drug
treatment count; datalines; 1 1 1 11 1 1 0 25 1 0 1 10 1 0 0 27 2 1 1 16 2 1 0 4

Analyzation of Attendance Policy in Higher Education Essay
Various universities and individual faculty members frequently differ in terms of attendance policy.
The frequent absence of explicit university wide policy enables instructors to implement a wide
range of attendance requirements and subsequent penalties for absences. Even professors with a lax
attendance policy encourage regular class attendance, deeming it a critical element of student
success. The classroom has traditionally played a central role in educational institutions. Relentless
innovation in the field of information technology has significantly reduced the importance of the
physical classroom in the modern education environment. Most educators have embraced the newly
available technology but remain steadfast in their loyalty to ... Show more content on
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Students in there freshmen year are a large part of the excessively absent trouble area, on average
33% of first year student are typically absent from class. Absenteeism is not limited to the young;
reports claim that absenteeism from an average class in a small school is 25%. On a similarly typical
day a medium sized school would experience a 34% average, while a large institutions reports a
shocking 40 % average (Romer 168). Excessive absenteeism has been reported in connection with
particular classes. The most obvious of which are large first year introduction courses as their
patrons were the leading absentee student group. Interestingly the absenteeism was most
pronounced in courses dealing with the natural sciences (Friedman, Rodriguez, and McComb 124).
Students may choose to miss class for a variety of reasons, both legitimate and otherwise. In regards
to first year students an emerging pattern may be key in explaining their excessive levels of absence.
Along with the traditional challenges of freshmen year, recently admitted freshmen do not view
attendance and effort as integral for academic success. Their warped point of view stems from their
undemanding high school experience, one that left them utterly unprepared for the rigors of higher
education. The recently entering freshmen class on average spent less time studying while achieving
higher grades then any previous class. Recently entering freshmen are not an isolated group; they
represent the

Hypertension Medication Paper
Modeling the Determinant of Access to Hypertension Medication: Using a Multinomial Logistic
Regression
In the fourth reviewed on the impact of hypertension treatment to low
income groups, and the
challenges this medical cost posed to them. A federal qualified health center (FQHC) in Michigan
provides care to the medically underserved and people in the low
income group. This center sampled
212 of their patients and looked at their history of having hypertension or currently has
hypertension. It shows that the FQHC had a high percentage of patients who had an uncontrolled
blood pressure. The high percentage of patients with uncontrolled high blood pressure at the FQHC
could be attributed to the fact that the patients cannot afford the treatment ... Show more content on
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The uninsured patients of hypertension are less likely to report having hypertension because they
cannot afford to seek a healthcare provider and if they access the doctor then they were not able to
meet the drug prescription cost. This situation makes the uninsured patients to be more prone to
unawareness of their health condition. Despite the benefits that accompany the treatment of
hypertension, the overall cost of treatment is overwhelming. The cost of the treatment and the cost
of the pharmaceutical products needed are relatively high. Improving policies that encourage cost
effectiveness may improve treatment of these disorders. Additionally it may maintain equity as the
costs of medication and medication can be predetermined. Several measures may improve better
health to individuals. They include insuring with privately run and public medical insurance
institutions. They include Medicare and Medicaid. Insured non
elderly individuals, compared with
uninsured individuals showed a greater potential of receiving drug therapy. This is the case in the
elder insured and uninsured. Age and gender had a significant impact on one's ability to access
medical cost and care if they were diagnosed with

A Critique Of Service Quality Models
Regarding the various service quality models discussed in section 2.3.1 to 2.3.9 the gap model
considers the perceptions and expectations of the customers, the gap being the difference between
expectations and perceptions (P–E). The model resulted in five dimensions that are generic in
nature. However, other models such as 'Technical and Functional Quality Model', 'Perception–only
Model' and 'Evaluated Performance and Normed Quality Model' consider only the perceptions of the
customers. Technical and Functional Quality Model describes three components such as technical
quality (the quality received by the customer), functional quality (how the quality is received by the
customer) and corporate quality (how quality is delivered by the organization). In the
Perceptiononly ... Show more content on Helpwriting.net ...
The EFQM Excellence Model helps for benchmarking and improvement of overall performance of
organizations focusing on key factors of TQM and assures quality service to its customers in turn.
2.5 A Critique on Service Quality Measurement and Evaluation SERVQUAL is a widely used
instrument to measure customer evaluations of service quality [48]. Despite a leading instrument in
measuring service quality, a number of studies have raised concern about it [156,168–171]. These
criticisms relates to conceptual, methodological and analytical issues in SERVQUAL. The primary
issue raised in the literature is the conceptualization of service quality as the difference between
perception and expectation [159]. Cronin and Taylor, reiterate their views against the
disconfirmation based SERVQUAL scale of measuring service quality and continued to be
proponents of their perception–only approach to service quality measurement. Further, the use of the
perception and expectation gap measure of service also raises related analytical concerns about its
low reliability, poor discriminant validity and spurious correlations [168–170]. Parasuraman et al.
indicate that on the issue

The Effects Of Smoking On The United States
Smoking is established as a recognized cause of cancer, lung disease, coronary heart disease, and
stroke(US Public Health Service,1964,Doll R 1976,1994, US Department of Health and Human
Services,1989).it is considered to be the single most important avoidable cause of premature
morbidity and mortality in the world. WHO has estimated that there are about 1100 million smokers
worldwide; this represents about one–third of the global population aged over 15 years
(WHO,1997). About 73% of these smokers (700 million males, 100 million females) are in
developing countries; in industrialized countries there are 200 million male smokers and 100 million
female smokers. In the over 15–year–old population of developing countries, it is estimated that
about 48% of males and 7% of females are smokers. The corresponding figures for industrialized
countries are 42% for males and 24% for females (WHO,1997).
Logistic Regression Model: The logistic regression models has wide ranging applications from
determining the population growth and its determinants to applications for predicting and analyzing
qualitative data and in epidemiological studies. Logistic regression model postulates relationship
between the log odds of a disease and the risk factors. A regression predicts the probability that an
observation falls into one of two categories of a dichotomous dependent variable based on one or
more independent variables that can be either continuous or categorical.
As in univariate logistic

Abb Case
ABB Electric Segmentation – Group Case Analysis
Team Members:
Emeka Ejika
John Marceaux
Brandon McNabb
Todd Teepell
Brandon Woods
Suppose you are the regional sales manager for ABB Electric, and you have been given a budget for
a supplementary direct marketing campaign aimed at 20% of the companies in your region 1. At
present, you have information on the Descriptor Data Tab of the ABB Electric Data (Customer
Choice).xls spreadsheet about the location of customers (districts 1, 2, and 3) and the sales potential
of each account of prospect. Based on this information alone, to what companies would you direct
the new direct marketing program? Specify the accounts and customer or prospect types.
In order to determine which ... Show more content on Helpwriting.net ...
If ABB is able to convert Customer 35 from Edison to its customer base, the conversion would
expand ABB's total annual revenue in the three Districts by over sixty–five percent. The final step of
our analysis was to narrow those results to the top eighteen Customers using APV as the
measurement (twenty percent of eighty–eight companies equals eighteen). The results of the ABB
District analysis and the eighteen potential marketing targets are illustrated in the tables below.
Firm Abbreviations:
A = ABB B = GE C = Westinghouse D = Edison
| | Ann. Purchase | | Firm | | | | Customer | Volume ($ K) | District | Chosen | | | 1 | 24 | $322 | 1 | A | | |
2 | 41 | $444 | 1 | A | | | 3 | 42 | $752 | 1 | A | | | 4 | 45 | $415 | 1 | A | | | 5 | 54 | $660 | 1 | A | | | 6 | 57 |
$736 | 1 | A | | | 7 | 69 | $528 | 1 | A | Total in D1 | $3,857 | 8 | 3 | $643 | 2 | A | | | 9 | 13 | $466 | 2 | A | | |
10 | 37 | $767 | 2 | A | | | 11 | 38 | $182 | 2 | A | | | 12 | 44 | $10,997 | 2 | A | | | 13 | 87 | $395 | 2 | A |
Total in D2 | $13,450 | 14 | 11 | $1,722 | 3 | A | | | 15 | 21 | $749 | 3 | A | | | 16 | 50 | $584 | 3 | A | | | 17 |
58 | $700 | 3 | A | | | 18 | 61 | $462 | 3 | A | Total in D3 | $4,217 |
Customer | Volume ($ K) Annual Purchase | District | Chosen Firm

Fair Value or Cost Mode Drivers of Choice for Ias 40
European Accounting Review
Vol. 19, No. 3, 461– 493, 2010
Fair Value or Cost Model? Drivers of Choice for IAS 40 in the Real
Estate Industry
A. QUAGLI∗ and F. AVALLONE∗∗
∗
Department of Accounting and Business Studies (DITEA), University of Genova, Genova, Italy and
∗ ∗ Department of Computer and Management Science (DISA), University of Trento,
Trento, Italy
(Received September 2008; accepted February 2010)
ABSTRACT The IFRS mandatory adoption in European countries is an excellent context from
which to assess the validity of accounting choice theory, which postulates that information
asymmetry, contractual efficiency (agency costs) and managerial opportunism reasons could drive
the choice. With this aim, we test the impact ... Show more content on Helpwriting.net ...
Our findings suggest that all the rationales described by accounting choice theory (information
asymmetry, contractual efficiency and managerial opportunism) drive the decision to adopt fair
value. Indeed, regarding contractual efficiency reasons in particular, we find that the larger the size
(proxy of political costs), the less likely fair value is to be chosen, while leverage and consequent
lenders' protection seems to be insignificant for the choice.
Furthermore, our results show that market–to–book ratio (MTBV) (proxy of information
asymmetry) is negatively related to the fair value choice. This finding, that conflicts with existing
literature, could be accounted for in the real estate industry due to the fact that high levels of MTBV
in this context reveal growth opportunities associated with a fair estimation of investment properties
and therefore with a low information asymmetry. Managerial opportunism behaviour, measured by a
dummy variable for earnings smoothing, seems to have an influence on fair value choice.
While all these variables seem to have an influence on the fair value choice, the same variables do
not explain the choice of historical cost with the IFRS1 revaluation option in preference to the cost
maintenance approach.
This paper offers various contributions to current

Parental Divorce Article Analysis
Lawton, L. E., & Bures, R. (2001). Parental Divorce and the "Switching" of Religious Identity.
Journal For The Scientific Study Of Religion, 40(1), 99. Purpose: This' article examines' the impact
of parental divorce on the likelihood that an individual has' changed their religious' identity.
Methods: We use the nationally representative 1987 National Survey of Families and Households
(NSFH). This data set contains information on 13,017 respondents, including information on their
current and childhood religious affiliation and family structure. Our sample consists of the 11,372
respondents who reported that they were raised as either Catholics or as mainline Protestants (see
Mueller 1971). Of this sample, 3,461 respondents were raised as Catholics and 7, 911 were raised as
Protestants. Among Protestants, we further distinguish between liberal and moderate Protestants
(n=4,129) and conservative Protestants (n=3,782). We exclude Mormons and Jehovah's Witnesses
because these two groups do not fit into the Protestant denomination structure as outlined by
Mueller. For the analysis of switching versus staying, we use logistic regression. The dependent
variable in this analysis is dichotomous, so logistic ... Show more content on Helpwriting.net ...
Since joining another religious group requires the formation and maintenance of new social ties, it is
consistent that women are more likely to switch to another denomination. Divorce increases the
likelihood of apostasy, leading to an increased likelihood of switching from Catholic to None,
moderate Protestant to None, and conservative Protestant to None (although the latter is not
significant). Apparently, for some divorced adults, the ties to religious ideology and community
become so frayed that divorce may overwhelm the need or desire to remain in the

Analysis Of The Association Of Obesity And Overweight With...
Multivariate analysis is tested using logistic regression analysis to investigate the association of
obesity/overweight with frequent mental distress (FMD) and other covariates such as age, sex, race,
employment status, regular exercise, cigarette smoking, general health, physical health, unable to do
activities, depressive disorder and diabetes. Each of the independent variables was separately used
to predict FMD. This was followed by a multivariable model, where all the variables were
simultaneously introduced. Finally, separate multivariable analyses were performed after stratifying
for the significant covariates and interaction variables to get parsimonious model. All the
independent variables were binary or categorical with two or three categories.
Full Model Logistic Interpretation: The logistic regression of full model indicates that after
controlling for covariates, such as age, sex, race, employment status, regular exercise, cigarette
smoking, general health, physical health, unable to do activities, depressive disorder and diabetes
the odds of obesity among participants having FMD is 0.99 times the odds of obesity among those
who do not have FMD interval (95%CI: 0.43, 2.29).Race, regular exercise, cigarette smoking,
physical activities, unable to do activities, depressive disorder are not significantly associated with
BMI. Covariates such age, sex, employment status, general health and diabetes are statistically
significant in the model with p0.005 or p>0.05, thus

Statistical Package For Social Sciences Essay
Statistical Package for Social Sciences (SPSS version 20) was used for editing, coding, scoring and
tabulation of collected data. Statistical tools like Mean, Standard Deviation, and Chi–square Test
have applied for analysis and interpretation of data. One–sample Wilcoxon test was carried out to
see the significance level to reject or accept the hypothesis. In addition, Logistic Regression model
was used to identify the factors determining the participation of women in SACCOs with 19
independent variables.
Model specification: Hosemer and Lemshew (1989) pointed out that a logistic regression has got
advantage over others in the analysis of dichotomous outcome variables. Therefore, binary logistic
regression model is used to study the participation decision behavior of sampled women. In this
study, the dependent variable "Participation" has two possible outcomes – probabilities of a woman
to be a cooperative member and probability of women to be non–member. Such variables are
characterized as dichotomous and outcomes are coded as 1 and 0 respectively.
Binary logistic regression makes no assumption about the distribution of the independent variables.
The relationship between the predictor and response variables is not a linear function in logistic
regression; instead, the logistic regression function is used, which is the logit transformation of p:
................................................. (1)
Here is the "intercept" and β1, β2, β3, and so on, are the "regression coefficients" of , , and so on

Where Does Turnout Decline Come From?
Where does turnout decline come from?
ANDRE BLAIS, ELISABETH GIDENGIL, NEIL NEVITTE & RICHARD NADEAU
Background
Blais 2000 and Gray & Caul 2000 said that in the most recent democracies the number of people
who use their voice in election is declining. As what the journal claimed, this is also occurred in
Canada. The journal reported that the turnout in small period of elections tends to decline slightly by
only three per cent, and this is claimed important.
Based on that, this research was trying to investigate the causes of the decline using data from the
Canada election conducted from 1968 to 2000. The researchers concentrated in age and education
factor as classic socio–demographic factors that associated with voting. In addition, ... Show more
In the education factor, it is claimed that the fact happened in Canada, the decrease in turnout has
occurred most significantly among the better educated who may have gotten to be more inclined to
refrain from time to time. This result is surprising as we know that people with better education have
higher willingness to vote that those with lower education. The research tries to find why did this
happen, and seek any other factors that affects.
Data
Based on the journal, here are some points they used:
Resource : Canadian Election Studies (CES)
Details : Nine years elections 1968
1974
1979 1980
1984
1988 1993
1997
2000 *No election study for 1972 election because it is missing
Data set : 25,000 individuals (about 3,000 per survey)
Dependent variable : Reported vote in the post–election survey
Independent variable : Age and Education
The journal also mentions some problem in the research, they are:

1. Over–estimated voting
Based on Blais & Young 1999 and Granberg & Holmberg 1992, the individuals who are more
intrigued by political issues and more slanted to vote are more inclined to answer surveys, and to
some degree (on account of board studies in which individuals are talked with in the campaign and
re–questioned after the decision) in light of the fact that taking part in a race study makes
individuals more slanted to vote.
2. Some misreporting due to social desirability
Based on Brady et al (1995:292), social desirability

In Addition To Saving And Bequest Channels, The Proposed
In addition to saving and bequest channels, the proposed model in this paper identifies two
additional channel of child labor. These are heterogeneity in child 's ability, which causes
heterogeneity in the cost of education, and differential future expectation of parents depending on
their socio–economic background. I attempt to capture these four channels using a number of
variables. For saving, I use income of household head and for bequest, I use whether the household
owns any house. Here income of household head may be under–reported or may have some types of
measurement errors, so, we use several other variables to instrument it. Ownership of a house is
used to capture bequest as housing price is very high almost across the country ... Show more
Secondly, the socio–economic group in which the household head belongs to is also crucial in
forming household head 's expectation. Thus, I use household head 's gender ($Head_female$),
Household head 's sector of employment ($Sector$), religion of household head ($Religion$), and
the location of household ($Urban$). Using these variables I estimate the following models: Where
$y$ is child 's working hours per day, $ extbf{X}={Urban, Sector, Female, Head_literacy, Religion,
House,$ $ Head_income, Head_female, Dropout_ability, Dropout_cost, Dropout_income}$, $
extbf{Z}={Urban, Head _sector,$ $ Female, Head _literacy, House, Land, Num _hhchld, Head
_literacy, Head_age, Dropout_ability,$ $Dropout_cost, Religion, Dropout_income, TV,
Head_female}$, $Q_{N}(eta) = g_{N}(eta) 'W_{N}g_{N}(eta)$, $g_{N}(eta)=frac{1}
{N} sum_{i=1}^{N}Z 'epsilon$, and $W$ is a $N imes N$ positive semi–definite matrix. In
addition, I also estimate logit and probit model of child labor, where I attempt to estimate the
probabilities of being a child labor with respect to the variables mentioned above. Results of these
models are shown in the following table:
In the above table second column reports the OLS estimates. Dummy $Urban$ has positive
coefficient, which indicates that child labor on an average work 0.4 hour more in

The Impact Of Retail Industry On The Retail Sector
I. Introduction The retail sector plays a pivotal role in the development of UK economy, contributing
£180 billion to GDP in 2014, 11% of the total. This industry employed about 4.4 million people in
2014, 15.8% of the UK labour, becoming the largest broad industrial group by the quantity and
proportion of employees. 539,000 enterprises operating in the retail industry in the UK makes
account for 10.3% of all UK businesses. Therefore, the failure of retail companies can lead to
adverse impact on not only shareholders, employees but also the whole economy. Those are the
reasons why the UK government has focused on the development of this industry and also made an
effort to prevent the bankruptcy in the retail sector. Figure 1. % change on the previous year of
economic output in retail sector and whole economy According to Niemira (1996), retail industry
tends to be more vulnerable to the ups and downs of the economy than other industries. To illustrate
by Figure 1, in 2007, the retail sector grew faster than the UK economy. Nevertheless, when the
recession began in late 2007, a quicker and deeper decline than the whole economy could be seen.
At the bottom in Q2 2009, output from the retail industry dropped by 9.3% compared with 2008
while the output from the whole economy decreased by 5.8% in that quarter (Rhodes, 2014) The
history witnessed many notable bankruptcy cases in the retail industry including Montgomery Ward,
Macy 's, Zale, Brooks Fashion, Revco, Hooker and Dart

Robert Sternberg STAT Differences
In 2003, Robert Sternberg and his collaborators finished phase one of The Rainbow Project that
sought to validate the STAT as an alternative to the SAT. Sternberg cited two hypotheses that this
project attempted to validate. First, he expected his test would predict a significant proportion of
variance in college GPA, beyond that of the SAT (Sternberg, et al., 2006). Second, he expected that
the STAT would reduce racial and ethnic differences that are often present in the SAT, as well as in
other college entrance exams (Sternberg, et al., 2006).
Requirements for this study were completed by 777 participants, from 13 colleges and two high
schools. Participation began by collecting baseline measures, high school GPA and standardized test
... Show more content on Helpwriting.net ...
Of particular importance is the STAT's ability to decrease racial and ethnic effects that tests such as
the SAT have not been able to do. Sternberg et al., (2001) demonstrated that the inclusion of the
triarchic measures decreased the gap between ethnicities. They believed the triarchic measures were
able to do so because they accessed multiple areas of intelligence, including several that were
considered to be universal. Another strength is the predictive qualities of the test. Again, Sternberg
et al. (2001) demonstrated that with the addition of triarchic skills test they were able to increase the
predictability of college GPA for students who were entering college, in addition to that of the SAT.
While these figures are encouraging, there were multiple shortcomings that emerged over the course
of these

What Is The Impact Of The Great Recession On Payout Policy
This paper uses panel data analysis to assess the impact of the great recession on payout policy in
the USA. It uses three multivariate linear and nonlinear regression technics to study the relationship
between the payout variable, pre–identified payout determinants and the GR. The following
regression model is considered as used by Denis and Osbov (2008): 〖PV〗_(i,t)=β_(i,0)+β_(i,n)
〖X'〗_(i,t)+ε_(i,t) (1) 〖X'〗_(i,t) is a vector of explanatory variables and includes all the relevant
factors identified in section 3.2. Table 2 in the appendix provides a summary of these variables, their
measures, empirical evidence and expected sign. 〖PV〗_it is the payout variable analysed as only
dividends, only repurchases, both or total payout. The paper ... Show more content on
Helpwriting.net ...
Nonlinear Models The second analysis technique uses a probit and logit models with the payout
variable taking a value of 1 if the sample firm uses the respective payout category in year t, and 0
otherwise. This is used by Fama and French (2001) and DeAngelo et al. (2006) and allows to
measure the marginal propensity for the different payout categories while capturing the behaviour of
firms that omit or initiate payout payments. We estimate a fixed effect logit model where the log
likelihood of the probit model and the random effect logit model do not converge. Using fixed effect
logit limits our work because the analysis considers only the explanatory variables within the
subsample of firms that changed their payout policies during the sample period (Renneboog and
Trojanowski, 2005). This excludes 22.1% of the original sample from the estimation procedure. We
also use a multinomial logit estimation procedure to explain the likelihood that a firm decides on a
specific payout category during the GR because we were unable to apply a multinomial probit
estimation as used by Renneboog and Trajanowski (2011). As such, the independence of irrelevant
alternatives (IIA) assumption may be violated by our outcome categories. We test for this violation
using Hausman–McFadden test of IIA assumption. The dependent variable in these models takes
four possible

A Study On Mode Choice Modeling
CHAPTER II– LITERATURE STUDY
2.1 Mode choice
Mode choice is the willingness of a person to prefer one mode of transport over the other when
given various alternatives comprising different attribute values. Here, attributes are the factors
which impact the mode choice such as their socio–economic characteristics, trip characteristics and
available transport characteristics.
2.1.1 Theories for mode choice modeling
Mode choice modeling is conventionally done based on discrete choice model; here the discrete set
of alternatives is given and one must be chosen. This model is based on choosing an alternative with
maximum utilization or say choosing a mode which provided the maximum utility to the user. This
utility can be found out with the attributes having an impact on mode choice. The relationship
between the attributes and mode choice gives a value to each attribute which shows the dependency
of choosing a particular mode on that attribute. The utility equations are generally represented as
linear equations; the coefficients of each attribute is taken as its weight representing its relative
value or importance in the utility equation and hence, their contribution in mode choice.
Deterministic and Probabilistic Choice Theory: The user chooses a mode as per the utility function
but there can also be some unpredictable behavior which can influence the choice. If the choice of a
person in a modal is taken as rational and he chooses a mode with maximum utility; the model is

Nurses Attitudes Toward Euthanasia
These variables are very important to understanding the population and addressing trends, but do
these results still stand when compared to those who work in the field? Is there proper
generalizability for these variables? The article, The Diverse Influence of Religion and World View
on Palliative–Care Nurses' Attitudes towards Euthanasia, addresses how a nurse's religion and
worldview effect their mindset in their career. Specifically, the researchers are studying how
religious beliefs have an impact on nurses and if so, what specific factor is the most important in
influencing these opinions. To study this correlation, the researchers gathered information from a
previous quantitative study that was conducted in 2006. This study collected ... Show more content
on Helpwriting.net ...
However, another factor could be influencing that data. It is unclear when the data from each article
analyzed was published and it could be misleading trying to compare articles from different years;
so, it is important to understand how these opinions, along with religion, have developed over time
and how they respond to one another. The article, Attitudes towards legalising physician provided
euthanasia in Britain: The role of religion over time, aims to analyze the change in support for
euthanasia over time in comparison to the change in religion and religiosity among the population.
The researchers noted that previous studies have indicated the relationships between religiosity and
denomination with negative attitudes towards physician assisted suicide and euthanasia. To further
hypothesize, the researchers concluded that an individual's opinion on these two topics may also be
swayed by their personal satisfaction with the health care system. To gather data, the researchers
used the British Social Attitudes survey. In this study, they used the years 1983, 1984, 1989, 1994,
2005, and 2012 for their analysis due to the availability of relevant questions. A variety of question
types were chosen to gauge certain variables, such as nominal for attitudes toward physician assisted
and ordinal for religion, which were separated into the categories: no

The Effect Of Levying Taxes On Sales And Customer Purchase...
Effect of Levying Taxes on Sales and Customer Purchase Behavior Online (Difference–in–
differences estimation) Section 1: Statement of Policy/Research Question The advent of the internet
led to an alternative platform for buying and selling goods. If sales tax is applicable only to goods
sold outside of the internet, it would be interesting to see if that means people inclined to making
purchases online where they would not need to pay sales tax. We want to see if there is a causal
relationship between the tax levied and the change in customer behavior with respect to a purchase
(sensitivity), i.e., whether or not the customer will make that purchase or the change in the
probability of the customer making the purchase. Section 2: Background on the Policy/Research
Question One scenario to consider would be the one mentioned above wherein we try to analyze the
change in customer/buyer's behavior with respect to purchases online versus offline. Another would
be to see if, within the realm of online shopping, they prefer to or are more likely to buy from in–
state sellers compared to out–of–state sellers. Most of the online transactions occur across state
borders with widely varying sales tax rates. And the law mandates that sales tax be collected from
buyers if they make purchases online from sellers who happen to be from the same state. If the seller
is not from the same state as the buyer, he cannot be compelled to collect tax on the buyer's
purchase. Thus, this suggests

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