Perfectionism As A Multidimensional Personality...

Perfectionism As A Multidimensional Personality...
To be perfect is impossible. But the ability to achieve the impossible is the temptress. Perfectionism has been described as a multidimensional
personality disposition. Indicating that the multiple dimensions can show either different or opposite correlations with maladaptive or adaptive
psychological processes (Stoeber, Corr, Smith, & Saklofske, 2016). It is a personality disposition that can be characterized by a striving for
flawlessness and setting exceedingly high standards for oneself. These standards can pertain to performances that are subsequently accompanied
by self–critical evaluations and the perception that others expect one to be perfect (Stoeber, 2016; Stoeber, Edbrooke–Childs, & Damian, 2016).
Perfectionism is a disposition that pervades all areas of life including but not limited to work, school, personal appearance, and social
relationships (Stoeber, Edbrooke–Childs, & Damian, 2016). Some define perfectionism into two categories, perfectionistic strivings, and
perfectionistic concerns. Perfectionistic strivings reflect perfectionistic personal standards and a self–oriented strive for perfection.
Perfectionistic concerns on the other hand, reflect concerns over mistakes, fear of judgment from others, and doubt about actions (Stoeber,
2016). Clinical psychologists regard perfectionism as a "personality disposition associated with psychopathology and mental health problems"
(Stoeber, 2016). With that being said, perfectionism is defined as multidimensional,
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A Correlation Between Emotion-Focused Coping With Test...
A Correlation Between Emotion–Focused Coping With Test Anxiety And Age Motivation can come from a variety of factors in an individual's
life, stress is one of those factors that can have either a positive or a negative effect (Deckers, 2014; Heiman, 2004). Stress can appear in an
individual through physiological, psychological and behavioural symptoms (Deckers, 2014). Deckers (2014) conveys that when an individual
has a physiological response to stress, it is the product of hormones creating the symptom in the body, for example, nausea or sweating. In
addition the psychological symptoms representing stress are identified through the level of stability of an individual's mind and feelings, and can
be rated through measures of anxiousness, nervousness, self–confidence, irritability or negativity of emotions (Deckers, 2014). Behavioural
symptoms of stress can be enacted out by an individual through excessive or dysfunctional conduct, for example, through an increase in
consumption of alcohol or caffeine, an intake of drugs, or poor sleeping habits (Deckers, 2014). Although the symptoms mentioned have an
attached negative stigma, it does not necessarily follow that all encounters with it will result in negativity. Deckers (2014) explains that stress
can be a motivator to a goal: if a problem arises in the pursuit of the goal, stress can occur, then an individual could be encouraged to overcome
the situation to achieve their goal through coping. Lazarus and Folkman (cited in

Purpose And Hypothesis Of The Pediatric Pain Management Of...
Purpose and Hypothesis of Study The study conducted by Stanley and Pollard (2013) had two components. The first was to assess the amount
knowledge concerning pediatric pain management of nurses then gauge their attitudes and level of self–efficacy concerning acute pediatric pain
care. The second was an examination of the relationship between years of experience, amount of knowledge, attitude, and levels of self–efficacy.
According to the authors, studies have previously indicated that care may be affected by the level of knowledge and attitude of the nurse,
however no research existed between each component and self–efficacy. Stanley and Pollard predicted that a nurses job performance concerning
adequate pain management of pediatric patients would be affected by the two components examined. (Review of literature ) They presented the
problem by citing previously conducted peer–reviewed studies indicating that proper pain management of pediatric patients was lacking and
which emphasized the importance of knowledge of the topic [cite]. Examples were given of barriers to proper pain management which included:
ignoring patient self–report, lack of education about pain assessment, misunderstanding pharmacological effect on the respiratory system, lack
of a universally applied pain management system, work security concerns, perceived inferiority, and time constraints. ( Stanley et al., 2013)
Sample
Participants of this convenience, non–probability sample were 25 nurses from 2

The Effect Of Computer Assisted Language Learning
Amber Scott Amber.Scott@matsuk12.us EDFN A621–201601– Instructor: Ira Ortega Spring 2016 Article 5 Khoshnoud, K., & Karbalaei, A.
(2015). The effect of computer assisted language learning (CALL) program on learning vocabulary among EFL left and right hemispheric
dominant learners.?European Online Journal of Natural and Social Sciences,?4(4), 761–777. The purpose of this study was to explore the use of
Computer Assisted Language Learning (CALL) in the field of teaching and learning of a foreign language in Iran. This study examines two
methods of vocabulary teaching/learning (CALL–based versus non–CALL based). CALL refers to the use of computer in the teaching and
learning of a second or foreign language. CALL programs aims to teach students in aspects of the language learning process via the medium of
computers. The article also explores the difference between using your left and right hemispheric domains for learning vocabulary using CALL
instruction. Research Questions: 1. Does CALL program enhance learning English vocabulary in elementary EFL learners or not? 2. Is there any
difference between left hemispheric and right hemispheric dominant learners in learning vocabulary using CALL instruction? Conclusions:
Teaching vocabulary based on Computer–Assisted Language Learning (CALL) was found to be significantly effective in improving learners '
vocabulary knowledge. CALL was more effective in terms of right brained learners. Also, right brained experimental group who

Employee Engagement : Measuring Retention
Employee Engagement
An additional factor to be considered is when measuring retention is employee engagement. Employee engagement is the degree to which a
worker believes in, or is committed to their work, field, and place of employment (Maslach, C. 2003; Harter, J., et al. 2006). The higher degree
to which an employee is engaged, the more likely they are to retain their position.
There are three levels of engagement in which an employee can be measured at (Catado, P. 2011); fully engaged, disengaged, and actively
disengaged. A fully engaged worker takes it upon themselves to stay relevant and up–to–date in company's and their professional field and take
on additional responsibilities as the opportunities arise. They also show respect towards their fellow colleagues, are willing to put in more effort
than is expected, and exhibit high levels of enthusiasm.
One who is disengaged see their work as time exchanged for a paycheck. These employees fulfill their essential duties but contribute nothing
more. They come on time and leave on time, and rarely if ever volunteer for extra responsibility. The third level at which How actively
disengaged employees differentiate themselves is they regularly voice their dissatisfaction with their positions and undermine their fellow
colleagues. While the Institute for Employment Studies found actively disengaged employees make up only about 15–18% of the work force
(Catado, P. 2011), the negativity they bring to the environment can affect

Analyzing The Strengths Of Qualitative And Quantitative...
Q–methodology was first introduced by psychologist William Stephenson (1902–1989). "Q–methodology combines the strengths of both
qualitative and quantitative methods" (Brown, 1996). The method is one that studies subjectivity and can be used on various researches.
Subjectivity can be defined as "a person's communication of his or her point of view" and it is always stems from a person's "internal frame of
reference" (McKeown & Thomas, 1988). An internal frame of reference can refer to the personal viewpoint of the respondent; in this research, it
is the viewpoint of several people for reasons why project are delayed. This frame of reference has been established through the experience of
working on or being in other ways involved in ... Show more content on Helpwriting.net ...
Hence, this reference provides much more information than a 'yes, no' question ever did (McKeown & Thomas 1988). Q–methodology uses the
concept of ranking as simplified in Table 4.2. By asking multiple people from SHTC to rank the 40 statements, the prioritization of these criteria
comes forth. All statements are based on people's opinion on why project delay, yet the comparison with other people's opinions and ranking the
statements will bring about the real subjectivity (Brown, 1993). 4.1.2 The Q–analysis process As the method revolves around the ranking of
statements, the process starts by defining these statements. This set of statements, also referred to as the Q–sample, should comprehensively
represent the concourse: the sum of all things people say or think about the issue being investigated. The concourse is most typically collected
through interviews and focus group discussions. In addition, sources such as publications, essays, or any other sources related to the issue may
be used. The collection of the concourse and the Q–sample is described in the previous chapter. What is in fact investigated is not just the
concourse itself, but the inherent "operant structure" that exists in the concourse or the Q–sample (Dryzek, Clark, & McKenzie, 1989). The Q–
sample often exists of statements, however, it can be created from basically anything: from words to paintings or even songs (Brown, 1996).
With the Q–sample, the respondents can participate in the

Samsung Essay
FINAL REPORT ON COMPARATIVE MARKET ANALYSIS OF SAMSUNG ELECTRONICS VIS– A– VIS ITS COMPETITORS
SAMSUNG INDIA ELECTRONICS PVT LTD. REPORT ON COMPARATIVE MARKET ANALYSIS OF SAMSUNG ELECTRONICS VIS–
A– VIS ITS COMPETITORS A report submitted in partial fulfillment of the requirements of MBA Program of Jaipuria Institute of Management
TABLE OF CONTENTS Acknowledgement....................................................................................4 1. Abstract
................................................................................. .........5 2. Introduction ...................................................................................6 a. Overview of
the Consumer durable sector......................................7–8 b. Company ... Show more content on Helpwriting.net ...
Doubt is often better than overconfidence, for it leads to inquiry and inquiry leads to investigation" Research inculcates scientific and inductive
thinking and it promotes the development of logical habits of thinking and organization. Research is a common parlance refers to a search of
knowledge. The advanced learner's Dictionary of current English lays down the meaning of research as a careful investigation or inquiry
especially through search for new facts in any branch of Knowledge What is comparative Marketing study? In comparative marketing research
we take our competitor's products and make comparison through consumer with our own products. Why Comparative Marketing study?
Comparative marketing study/research comprise one of the most important and fascinating task of marketing. It provides information for
marketing decision making, any problem that are identified and investigated further by using problem solving techniques with the objective of
arriving at solution. The most important innovation in the new approach is to study simultaneously different organizational forms of business
interest representation. The aim of the study is to point out the best (in this respect) among the alternatives that are being studied. The final aim
perhaps is not only to find the best, but also to improve it or

Effect of Accounting Information on Share Prices
www.ccsenet.org/ijef
International Journal of Economics and Finance
Vol. 4, No. 2; February 2012
The Impact of Accounting Information on Stock Prices: Evidence from the Athens Stock Exchange
Michalis Glezakos University of Piraeus, Department of Insurance and Statistics 80 Karaoli & Dimitriou, 185 34, Piraeus, Greece E–mail:
migl@unipi.gr John Mylonakis (Corresponding author) 10, Nikiforou str., Glyfada, 166 75, Athens, Greece E–mail:
imylonakis@vodafone.net.gr Charalampos Kafouros M.A. University of Piraeus, Greece E–mail: bkafouros@gmail.com Received: November
23, 2011 doi:10.5539/ijef.v4n2p56 Abstract Past empirical research indicates that, in an increasing number of countries, certain accounting
parameters affect the course ... Show more content on Helpwriting.net ...
Canibao, Garcia–Ayuso and Rueda (1999) examined accounting data taken from Spanish companies, showing that the joint explanatory power
of earnings and book values has not declined in the latest decades. However, their results demonstrated a slight decline in the marginal
explanatory power of book values in relation to earnings. The usefulness of accounting data in business evaluation was, also, evidenced by Ou
and Penman (1989), Ohlson (1989, 1995) and Penman (1996). They explained a company 's internal value by using accounting parameters and
concluded that they can be used to identify stocks that have not been properly evaluated. Τhey, also, expressed the view that the book value and
earnings form the primary accounting variables which are used to interpret stock prices. Their findings are, also, supported by the empirical
studies conducted by Lev (1996) and Francis and Schipper (1996), who examined data from the US market during the latest decades. They have,
also, found that the explanatory power of accounting variables has declined. On the other hand, Collins, Maydew and Weiss (1997) have
expressed the opinion that the combined relevance of earnings and book values is progressively increasing over time. On the contrary, the
relevance of extraordinary

Amount of Sleep and Gpa in Graduate Students at Ohio
E720 Notebook Assignment: Correlation
Kandell 1
Amount of Sleep and GPA in Graduate Students at Ohio University Many graduate students may not be receiving enough sleep at night. With
increased workloads and responsibilities many students are forced to sacrifice their sleep hours to keep up with the work. This means that
students are forced to stay up later and get up earlier. It has been found that lack of sleep can reduce ones mental capabilities like a lack of focus.
With graduate students getting less sleep it may be possible that they suffer mentally and see a decline in GPA when compared with someone
who receives more sleep. I plan to research whether there is a relationship between the hours of sleep a student gets and his or ... Show more
content on Helpwriting.net ...
CORRELATIONS /VARIABLES=Sleep_Hrs GPA /PRINT=TWOTAIL NOSIG /STATISTICS DESCRIPTIVES XPROD
/MISSING=PAIRWISE .
Kandell 5
Explore
Case Processing Summary Cases Missing N Percent 0 .0% 0 .0%
GPA Sleep_Hrs
Valid N Percent 40 100.0% 40 100.0%
Total N Percent 40 100.0% 40 100.0%
Descriptives Statistic 2.8588 2.7371 2.9805 2.8634 2.8900 .145 .38060 2.1 3.6 1.53 .59 –.259 –.773 5.9281 5.8037 6.0525 5.9281 5.9950 .151
.38895 5.16 6.62 1.46 .56 –.072 –.869 Std. Error .06018
GPA
Sleep_Hrs
Mean 95% Lower Bound Confidence Upper Bound Interval for Mean 5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum
Range Interquartile Range Skewness Kurtosis Mean 95% Lower Bound Confidence Upper Bound Interval for Mean 5% Trimmed Mean Median
Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis
.374 .733 .06150
.374 .733
Kandell 6
Tests of Normality Kolmogorov–Smirnov(a) Shapiro–Wilk Statistic df Sig. Statistic df Sig. .092 40 .200(*) .966 40 .265 .088 40 .200(*) .972 40
.417 * This is a lower bound of the true significance. a Lilliefors Significance Correction
GPA Sleep_H rs
Sleep_Hrs Stem–and–Leaf Plot Frequency 1.00 3.00 5.00 7.00 4.00 10.00 4.00 4.00 2.00 Stem width: Each leaf: Stem & 5 5 5 5 5 6 6 6 6 . . . . . .
. . . Leaf 1 333

The San Diego Quick Assessment
At the middle school level, it is difficult to administer extensive interminable assessments, when you are trying to determine readability for over
100 students. Many middle school teachers rely on the NWEA/MAP assessment and "Standard of Learning" to provide them with their student's
Lexile levels and readability. The problem with using data from the NWEA/MAP assessment and SOL scores is that teachers only have data
from the previous year and are unable to assess the factors that contributed to the students testing scores. A quick and easy assessment that can
be given the first week of school, which takes 10 minutes or less and shows word recognition as well as readability is the San Diego Quick
Assessment. The San Diego quick assessment was originally devised by Margaret La pray and Ramon Ross and published in the "Journal of
Reading" in 1969, as a quick way to gauge a student's readability. Words were selected for 13–grade level, Pre–Primer through 11th grade by
drawing words randomly from basal reader glossaries. (Blackley) Words were also drawn from the glossaries of basic readers and from 1931
"Teacher's Word Book of 20,000 Words by E.L. Thorndike. According, to Margaret La Pray and Ross the San Diego Quick Assessment has two
uses, to determine a reading level and to detect errors in word analysis. The test can also be used to group students for corrective practice or to
select appropriate reading materials for those students. The San Diego Assessment should be

Children Versus Adults: Comparing Diet and Exercise Results
Children Versus Adults: Comparing Diet and Exercise Results
In an attempt to look at the different results of diet and exercise among children and adults, a study was conducted, in which the subjects self–
monitored their progress over a span of twelve months. During this period, different variables were measured, to include urinary Na/K ratio,
systolic blood pressure, diastolic blood pressure, cholesterol levels, and body mass index, to name a few. The outcome of this study shows
opposite conclusions for adults and children. Results were found in adults to have positive correlation between diet and the measured variables,
whereas children showed no direct correlation. In contrast, adults showed little correlation with exercise, ... Show more content on
Helpwriting.net ...
This shows an importance placed more heavily on the diet part of the program than on the exercise. This could have directly affected the results.
In relation to the diet, the adults experienced a decrease in their urinary Na/K, their blood pressure, and their total cholesterol when they
monitored the intake of healthy foods. Changes were also seen as an increase in their body mass index when they monitored the intake of
unhealthy foods. These changes were not as obvious when monitoring exercise results. In regards to exercise, there were no significant
correlations between the measured variables and the adults in the study.
In contrast to the adults in the study, the children showed quite opposite results. According to their monitoring, they experienced more changes
in their physiological variables when looking at exercise benefits than diet benefits. Although both groups were lower overall in monitoring their
exercise, the percentage was higher in children, which was not seen in the monitoring of the diet. The study showed that 84.1% of adults
monitored their exercise, while 85% of children did the same. Although this is not a large margin, the difference can be seen as a greater
importance being placed on exercise for the children. This could be because the results showed a more significant physiological difference in the
children due to exercise than in the adults. During the self–monitoring of the healthy diet, the

The Dass-21 Had A Good Internal Consistency. For Depression,
The DASS–21 had a good internal consistency. For depression, anxiety and stress subscales, Cronbach's alpha values were 0.94, 0.87 and 0.91;
respectively (Antony et al., 1998). In our study, we utilized the Malaysian version of the DASS–21, which was translated and validated by Musa
et al., 2007 and showed a good internal consistency; i.e., Cronbach's alpha for depression subscale = 0.84, for anxiety subscale = 0.74 and for
stress subscale = 0.79 (Musa et al., 2007). Statistical Analysis All analyses were performed using the Statistical Package for Social Sciences
version 22.0 (SPSS Inc., Chicago, IL, USA). To address our research objectives, we ran either descriptive or inferential analyses. Categorical
variables were described ... Show more content on Helpwriting.net ...
Only 36% were current smokers, whereas 37% of the patients were current alcohol consumers. Presence and Severities of Depression, Anxiety
and Stress Symptoms Based on the presence or absence of the assessed disorders symptoms, it was found that 58.9%, 68.2% and 41.1% of the
study subjects had the symptoms of depression, anxiety and stress; respectively. Table 3 presents participants' frequencies and percentages based
on the presence of the symptoms and its severity of each measured disorder. Only 23.4% of the patients were totally free of any of these
symptoms, whereas 35.5% of the patients had the three disorders symptoms. For depression and anxiety, the majority of symptoms were
moderate in severity, while the majority of stress symptoms were mild in severity. Table 3 Frequencies and Percentages of the Intensity of
Depression, Anxiety and Stress Symptomatology among the Study Participants (N = 107) Psychological disorder Frequency % Depression 63
58.9 Mild 15 14.0 Moderate 25 23.4 Severe 15 14.0 Extremely Severe 8 7.5 Anxiety 73 68.2 Mild 16 15.0 Moderate 30 28.0 Severe 13 12.1
Extremely Severe 14 13.1 Stress 44 41.1 Mild 19 17.8 Moderate 11 10.3 Severe 11 10.3 Extremely Severe 3 2.8 Morbidity Three disorders
symptoms 38 35.5 Two disorders symptoms 22 20.6 One disorder symptoms 22 20.6 Free of symptomsa 25 23.4 Total 107 100 Note. The sum
of frequencies and

The Contribution Of Drug Abuse On Domestic Violence Essay
The Contribution of Drug Abuse on Domestic Violence
Substance abuse and domestic violence are closely interlinked on various grounds both in people 's mind and scientifically. It is a common belief
that substance abuse plays a significant role in the escalating numbers of domestic violence in the current society. Different studies conducted
have shown that there is a correlation between substance abuse and the current emerging domestic violence issues. High rates of substance abuse
by various individuals have resulted in the increased levels of domestic violence. This is a more clear indication that substance abuse and
domestic violence are interrelated actions which should be addressed together. Therefore this research paper will aim at creating an
understanding of drug addiction and domestic violence levels.
It is important to choose an effective statistical method in order to obtain reliable and valid statistical data. Since the study hopes to understand
the contribution of substance abuse on domestic, the most appropriate statistical method to employ should be able to effectively provide a clear
picture on how the two variables are related. Therefore the study will use linear regression and the Pearson product moment correlation
coefficient. Linear regression analysis is the commonly used statistical tool in obtaining a predictive analysis of a given set of variables. The
regression estimates obtained can describe a given set of data and proved a valid interpretation of

The Pearson Product Moment Correlation
The Pearson product moment correlation is the most frequently utilized measure of relationships (Salkind, 2012). The symbol for this
relationship is the letter r which represents the variables being correlated. Furthermore, the symbol rxy characterizes a correlation between two
variables,X and Y. When computing a correlation, one requires a pair of scores, for example, reading scores and math scores for each group the
researcher is working with. In the case of computing the correlation between the hours a group studies and test scores, one should measure the
number of hours spent and the results of test for each individual. A good way to represent the findings is the use of scattergram, also known as
scatter plot. Scattergrams provide a visual depiction of the correlation coefficient of the relationship between two variables, X and Y. They are
very beneficial for researchers to determine correlation coefficients. Essentially, a correlation is a measure of how two different variables relate
to one another, how they co–relate. A scattergram shows that co–relation on a diagram. The scattergram is like a graph or a bar chart, having a x
and y at right angles to one another. In this case, the x axis represents one variable, while the y axis represents the second variable. The points on
the scattergram are obtained by taking related measurements of the two variables. They might be related by being taken at the same time, or by
coming from the same research participant,

Priming Effects : An Experimental Investigation Into...
Priming Effects: An Experimental Investigation Into Question Order Effects on a Self–Esteem and Life Satisfaction Questionnaire Krishia
Desabelle–Mulligan University of East Anglia Abstract This study aims to examine whether the answer to one question can prime the answer to
another question; specifically, researchers wish to investigate whether order effects occur in questionnaires. An experiment was conducted to test
the hypothesis that when positive self–esteem statements are asked first (Condition 1), participants would subsequently rate their critical
question on life satisfaction higher compared to if participants are asked to rate their life satisfaction first (Condition 2). A correlational analysis
was used to obtain a Pearson's r value for each condition which serves as the dependent variable. The questionnaire used in the study was
adapted from Rosenberg's (1965) Self–Esteem Scale (RSES). Self–esteem was selected as whilst it is a logical link to life satisfaction, they are
not causally related, demonstrating that results are caused by question order effect and not a fundamental association between the answers to the
questions. Baumeister, Campbell, Krueger and Vohs (2003) found that high self–esteem does not prevent children from risky behaviours and
may alternatively fosters experimentation. Thus, general effects of self–esteem are negligible in relation to life satisfaction (Baumeister et al.,
2003). A difference was found between Condition 1

Efficient Frontier Analysis
The definition of the efficient frontier says that "the efficient frontier represents the set of portfolios that has the maximum rate of return for
every given level of risk, or the minimum risk for every level of return." I plotted standard deviation on x axes and Returns on y axes to interpret
efficient frontier. Exhibits also include these and the graphs you asked for as graph2:
In our study, we concentrated on the optimal portfolios, the one which has the lowest volatility or risk, for given level of return. The area below
the frontier shows the achievable risk–return combinations, there will be at least one portfolio constructible that has the risk and return
corresponding to that point. No portfolio on the efficient frontier can ... Show more content on Helpwriting.net ...
As seen in table below.
STD EX® NAME EX®)/STD
4.560897 –0.07629 WMT –0.01673
6.62584 0.4643 HD 0.070074
4.832779 0.618 C 0.127877
4.519264 0.705732 HSY 0.156161
7.630042 0.805847 MRK 0.105615
5.243063 0.836464 IBM 0.159537
2.851834 0.867592 EQUAL 0.304222
10.58777 2.719098 BBY 0.256815
As seen in exhibit 11 if we add MCD to our portfolio and solve for without short selling we can see that the efficient frontier moved to the left.
In other words it improved. This is due to diversification. By the same intuition, as seen in exhibit 12, if we add LMT to our portfolio efficient
frontier improved even further. To see the difference, we can check exhibit 12.The reason that adding LMT improved efficient frontier even
further is because of the fact that while MCD has positive correlation as seen in the correlation matrix ,in exhibit 1 whereas LMT is negatively
correlated leading to more reduction in the risk of the portfolio due to diversification. Due to the point where the curves intersect (the point when
expected return is between 1.5 and 1.75) the portfolios including LMT are more efficient until expected return is 1.75 whereas after the point the
portfolios with MCD become more efficient if expected return is equal to higher than 1.75.This may be due to the marginal diminishing returns
that reverse the marginal utility the portfolio gains by increasing expected return. Up to that point if we divide the expected

Interest Rates and Other Critical Determinants of...
Interest Rates and Other Critical Determinants of Investment Spending in Bangladesh
Background
Investment, which is a spending devoted to enhancing or maintaining the existing stock of capital in the economy provides goods and services
necessary for better standard of living. Moreover, it has greater importance as a policy tool. Policymakers often try to achieve target growth in
GDP by influencing the level of investment. They do so by undertaking policies that influence the rate of interests. The underlying assumption is
that investment is negatively related with the rate of investment.
Historically, economic theories have suggested negative relationship between investment and interest rates. Changes in either nominal or real ...
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To investigate the impact of interest rates on investment spending, we use a simple regression function for the two variables but add several
slightly different variables. The starting point of model formulation is;
I= f (LR, SR, S, Y, ER) (1)
Where, I = Investment LR = Interest rate on loans SR = Interest rate on savings S = Gross Domestic Savings Y = GDP ER = Exchange rate
Investment is not a function of interest rate alone. Factors like income, savings, and saving rate along with lending rate are important issues in
setting the level of investment. That is why we need to incorporate all of them in the regression function and test the marginal impact of each of
them on investment.
Accordingly, the estimating equation used in this study is;
where, the term e is the stochastic error term that captures the impact of all other variables not included in the model.
Model Validation
The coefficient , which gives the change in investment due to one unit change in lending rate is expected to be negative. Other slope coefficients
( are expected to have positive values since their associated variables, interest on savings, savings, and income respectively should influence
investment positively. The coefficient can take positive or negative values depending on how a rising trend in exchange rates influence the level
of domestic saving. The expected impact is determined by the

BSE Sensex and Foreign Institutional Investment Study
RESEARCH DESIGN
Descriptive research is undertaken for study. Data collection was done from the website of BSE & SEBI of last two years. SOUCRES OF
DATA:
SECONDARY DATA – Secondary data for the study.
 Internet site www.bseindia.com www.sebi.gov.in
 Book
Business statistics – By (S.P. Gupta)
– Help of faculty guide and friends.
RESEARCH INSTRUMENT:
 Statistical tools
–Coefficient of correlation
– Covariance
– Regression Analysis (R2 )
SAMPLE SIZE
Historical data from–
BSE – (01/01/2012 to 31/12/2013 year)
SEBI– (01/01/2012 to 31/12/2013 year)
CHAPTER– 4 DATAANALYSIS
DATE CLOSE FIIs Investment
31/01/12 17193.55 10357.7
29/02/12 17752.68 25212.1
30/03/12 17404.2 8381.1
30/04/12 17318.81 –1109.1
31/05/12 16218.53 –347.1
29/06/12 17429.98 –501.3
31/07/12 17236.18 10272.7
31/08/12 17429.56 10803.9
28/09/12 18762.74 19261.5
31/10/12 18505.38 11364
30/11/12 19339.9 9577.2
31/12/12 19426.71 24463.5
31/01/13 19894.98 22,059
28/02/13 18861.54 24,439
28/03/13 18835.77 9,124
30/04/13 19504.18 5,414
31/05/13 19760.3 22,169
28/06/13 19395.81 –11,027
31/07/13 19345.7 –6,086
30/08/13 18619.72 –5,923
30/09/13 19379.77 13,058
31/10/13 21164.52 15,706
29/11/13 20791.93 8116
31/12/13 21170.68 16,086
Coefficient of correlation– Karl Pearson's coefficient of correlation
Formula:–
The analysis of above data –
Coefficient of correlation 0.255260872

Questions On Analyzing Quantitative Data
Assignment Three: Analyzing Quantitative Data
List of Figures
Figure 1 Frequency per rank for the top 100 words 3
Figure 2 A histogram showing the distribution of token size across the "Doctored Dataset" Corpus 7
Figure 3 A boxplot showing the distribution of token size across the "Doctored Dataset" Corpus 7
Figure 4 A Q–Q plot of the distribution of token size across the "Doctored Dataset" Corpus 8
Figure 5 A boxplot showing the median length of research articles in each disciplinary domain 8
Figure 6 A boxplot showing the descriptive statistics in five academic domains 11
Figure 7 A scatter plot showing the correlation between the numbers of tokens and types across the five domains 12
List of Tables
Table 1 Descriptive ... Show more content on Helpwriting.net ...
This simply means that the majority of words occur only a few times. Another evidence of this conclusion is the median frequency which is
2.00.
Question 3 Figure 1 Frequency per rank for the top 100 words
Figure 1 is a line graph that shows the correlation between the frequency (y) and the rank (x) of the top 100 most frequent words in the pre–
mentioned academic corpus. As in Zipf's Law, the frequency of a word in a corpus of natural language is inversely proportional to its rank in the
frequency table. That is, the most frequent word occurs approximately twice as often as the second most frequent word, three times as often as
the third most frequent word, etc.
Question 5
The table below shows a Chi–square test of the use of the word 'lovely' in both COCA: spoken and BYU–BNC: spoken corpora Lovely All other
words Total words
COCA: spoken 1836 90063928 90 065 764
BYU–BNC: spoken 2397 9961266 9 963 663
Total 4233 100025194 100029427
Table 2 The use of

A Research Study On The Research Design
The research design was a quantitative with qualitative comparison using a mixed methodology as previously mentioned. This study is a
descriptive correlational study based on describing associations among variables rather than to conclude cause and effect relationships (Polit &
Beck, 2008, p. 556). The study also encompasses a prospective longitudinal component which demonstrates causality between study variables,
which produces improved quality of evidence. The sample participants consisted of only acute care clinical managers for data analysis.
Important to note The participants were mailed confidential surveys to their home addresses, with notification letters sent 2 weeks later.
The researchers conducted the study at the NL with ... Show more content on Helpwriting.net ...
In addition, to pinpointing movements required to influence those intentions and comportment an examination of the organizations current
philosophies (Belias & Koustelios, 2014).
Furthermore, Belias and Koustelios (2014) found that strategic leadership requirements need to encompass transformational models aimed to
serve the organization. In numerous cases, the kind of leadership essential to modify culture is transformational. In order to change culture
considerable energies and commitment to accomplish outcomes. The author emphasizes that leaders achieve change through the leader's
application of a visualization of the organization over personal individualities intended to modify internal structural cultural principles. In
addition, these leaders must function from an underpinning of great moral practices and hold a central appreciation of the multifaceted issues
that are conducive in collective exertions within the organization (Belias & Koustelios, 2014).
Encompassing redesign methodologies with the available population of acute care managers was moderately small. To attain larger sample
similarity, Way et al. (2007) used exclusively clinical service managers were used for data study. The analyst utilized the Employee Attitude
Survey, which comprised of "5 instruments measuring 7 variables (emotional climate, practice issues, empowerment, trust in employer, job
satisfaction, organizational commitment,

Business Problem Proposal Mba 510
Running head: BUSINESS PROBLEM PROPOSAL Business Problem Proposal University of Phoenix Business Problem Proposal Wal–Mart is
a worldwide retail company. In 2008, Wal–Mart operated 971 discount stores, 2,447 super centers, 132 neighborhood markets, and 591 Sam's
Clubs in the United States (MarketLine, 2008). The company is headquartered in Bentonville, Arkansas and employs about 2.1 million people
worldwide. The business problem to be illustrated is the high employee turnover that Wal–Mart experiences. A look into why employee retention
is so high and the associated costs of this high turnover will be explored. Illustrations will show Wal–Mart's problem of high turnover in
statistical terms and list a set of recommendations to reduce ... Show more content on Helpwriting.net ...
Coefficient of correlation measures the strength of linear relationships between two variables. The two variables must have an interval scale of
measurement. Relationships of –1.00 and +1.00 have strong respective positive or negative correlations. A relationship of zero identifies a weak
relationship between the two variables being analyzed. Primary and Secondary Data Sources The retention of Wal–Mart employees has been a
problem. A quantitative correlational study to access job pay satisfaction, turnover intentions, and leadership styles will be discussed. The
primary data consisted of questionnaire surveys. If required, informal interviews can be included. The primary data research was to determine
whether satisfaction with supervisor or overall job pay satisfaction is more significantly related to turnover intentions. The primary data was
coded for a quick analysis and was verifiable by re–questioning. Secondary data was extracted from published statistics such as census, housing
and social security data. Other secondary data was retrieved from similar industry models, internal databases, and library databases. The
secondary data research was to recommend leadership styles associated with job satisfaction as a means to increase retention. Data was collected
from a sample of employees using on–line and paper–and–pencil questionnaires. The survey incorporated demographic items and instruments
that measured perceived transformational, transactional,

Grip and Arm Strength Essay examples
Term Project Proposal
Week 5
Grip and Arm Strength
Purpose Statement
Occupational health professionals consistently document the need for physical testing upon application for physically–demanding jobs. Decades
of studies suggest that physical fitness screening prior to job selection decreases workplace injuries. Many of these studies prove specifically
that a direct correlation exists between one's strength and job performance. This case study examines such a claim. It is an analysis of the impact
arm strength (ARM) and hand grip (GRIP) have on workers' performance on the job (SIMS). So, can job performance be predicted linearly by a
combination of grip strength and arm strength? Therefore, the dependent ... Show more content on Helpwriting.net ...
Also, you risk injury to applicants who are not strong enough to do the job. A solution to this problem is to develop a measure of physical ability
that is easy and quick to administer, does not risk injury, and is related to how well a person performs the actual job. A study by Blakely,
Quiñones, and Jago (1995) published in the journal Personnel Psychology reports on the research results of just such a measure. That study, and
this case study, looks at methods for determining if these strength tests are related to performance on the job. The principles and methods
associated with this case study also apply to any number of variables other than strength and job performance.
Definition of Variables
The dependent variable will be work/job performance and the two independent variables are grip (GRIP) and arm (ARM) strength and two
measures of strength were gathered from each participant. A piece of equipment known as the Jackson Evaluation System (JES) was used to
collect the strength data. The JES can be configured to measure the strength of a number of muscle groups. In this study, grip strength and arm
strength were measured. For each of the tests, the participant was asked to exert as much force as they could for a period of 2 seconds. The
equipment then measured the maximum force exerted in pounds (lbs.). Since there is little to no

Statistical Test For Your Data Analysis
Data Analysis and Interpretation In selecting the appropriate statistical test for your data analysis, you need to identify the question or hypothesis
for the study. Are you trying to compare groups, interested in finding out if there is a relationship between two or more variables, or are you
trying to predict. Some factors to consider as well are the following: (1) Research design, (2) Level of measurement: nominal, ordinal, interval,
ratio, (3) Number of groups, and if they are correlated (dependent) or independent, (4) Number of variables, and know which is the dependent
and independent variable, and (5) Know when to choose a parametric versus a non–parametric test. The flowchart and the Appendix E section of
the book on How to Use SPSS eighth edition of Brian Cronk (2014), was used as a guide to answer the questions below. Answer this question
for the four studies below: Which statistical test you would use to analyze the data collected for these variables? Study A* Variable 1 is
psychiatric patients' gender; and Variable 2 is whether or not the patient has attempted suicide in the past 12 months. Answer Chi–square test of
independence tests whether or not two variables are independent of each other (Cronk, 2014). The question here is, is there a relationship
between gender and whether or not the patient has attempted suicide in the past 12 months? Does the relationship differ for males and females?
The independent variable is gender and the dependent variable

Mental And Physical Health Of College Students
Literature Review: Mental and Physical Health of College Students
Jackie Brocious
Misericordia University
Literature Review: Mental and Physical Health of College Students
This paper is focused on the sub–topic of mental and physical health of college students, either within healthcare–related fields or general
graduate programs. This sub–topic is a branch of our group's research purpose of identifying the occupational therapy (OT) student's perception
and confidence with an OT program and their preparedness within the field.
A study done by Pfeifer, Kranz, and Scoggin (2008) at Texas University focused on the perceived stress of OT students in an entry level master's
program. The results from the interview revealed that ... Show more content on Helpwriting.net ...
It was found that much of the cause of psychological distress came from the lack of clarity and transparency within the structure of the programs
and study plans, and not with the quality of the teachers (Nerdrum et al., 2009).
Jacob, Itzchak, and Raz (2013) stated that many healthcare students perceive themselves as working under a lot of pressure due to the demands
of their programs. The students rated time demands of courses and the amount of material covered the highest indicators of stress within the
academic factor (Jacob et al., 2013).
In Norway, a survey reported that college students were at a greater risk of developing mental health problems than the general population
(Bonsaksen, 2015). Female students were also twice as likely to report mental health problems compared to their male counterparts (Bonsaksen,
2015). At the end of the study, the male students had a higher satisfaction with the OT program, and had higher levels of self–esteem and self–
efficacy (Bonsaksen, 2015). Bonsaksen (2015) also notes that regarding the self–esteem measure, the students who spent most of their time on
self–study, acquired higher scores, which suggests that the female students, who tended to have a lower self–esteem and self–efficacy, could
offset it by increasing self–study.
Holinka's (2015) study was determined to support other findings of how stress negatively correlates with college students' life satisfaction. The
analysis from her study

Statistics
Chapter 22 Correlation Coefficients 22 Correlation Coefficients The Meaning of Correlation Correlation and Data Types Pearson's r Spearman
rho Other Coefficients of Note Coefficient of Determination r2 The concept of correlation was introduced in Chapters 1 and 5. Our focus since
Chapter 16 has been basic statistical procedures that measure differences between groups –– one–sample, two–sample, and k–sample tests. Now
we turn our attention to basic statistical procedures that measure the degree of association between variables. Dr. Wesley Black studied the
relationship between rankings of selected learning objectives in a youth discipleship taxonomy between full–time church staff youth ministers
and seminary students ... Show more content on Helpwriting.net ...
The third scatterplot shows a moderately positive correlation. Notice how most of the data points do not fall on the line. It is a moderate
correlation, however, because the points fall in a tight pattern around the line. Notice the pattern is linear –– that is, a pattern suggesting a line.
The fourth scatterplot shows no correlation. Scores on one variable have no systematic association with scores on the other. The scatterplot
presents no linear pattern among the points. Beyond the graphical representation of association, we can mathematically compute the degree of
association between two variables. The numerical result of such a computation is called a correlation coefficient. The value of these coefficients
usually range from –1.00 to +1.00. A positive coefficient indicates that two variables systematically vary in the same direction: as one variable
increases, the other variable tends to increase. The closer the coefficient is to +1.00, the stronger the positive association. A negative coefficient
indicates that two variables systematically vary in opposite directions: as one variable increases, the other variable tends to decrease. The closer
the coefficient is to –1.00, the stronger the negative association. A coefficient close to zero indicates that no systematic co–varying exists
between the variables. There are several important correlation procedures. They differ according to the data types of the variables. 22–2 © 4th
ed.

Comparing Observed Meteorological Data From Two Different...
Comparing observed meteorological data from two different types of automatic weather stations
Petro Burger
11048990
HONOURS REASEARCH PROJECT – WKD 763
2016
DEPARTMENT OF GEOGRAPHY, GEOINFORMATICS AND METEOROLOGY
UNIVERSITY OF PRETORIA
ABSTRACT
Observed meteorological data collected by two different types of automatic weather stations (AWS) were statistically analysed in order to verify
if there were a difference in the measurements due to the different sensor types. The hypothesis is that the different types of AWS's will not be
statistically different. Data from January 2014 to February 2016 for six places in South Africa were analysed. Significant differences were
observed for rainfall totals, temperatures and wind speeds by using the Wilcoxon Mann–Whitney test.
1. Introduction
The objective of this study was to compare observed rainfall amounts, maximum air temperature, minimum air temperature and maximum wind
speeds at daily periods from two different types of automatic weather stations. An automatic weather station (AWS) is defined by the WMO
(1992a) as a meteorological station where observations are made and from which the data is transmitted automatically. The AWS was designed
to accurately measure and record standard meteorological variables. The design of AWS's may vary from measurement rates, methods on how
the data is retrieved or the intervals of when the data is reported (Tanner, 1990).
All functional AWS's must consist of certain specific features. These

Evaluation Of A Correlation Analysis Essay
3.3.2.2 Correlation Analysis
The next step was to perform a correlation analysis, among the selected 25 numerical variables (selected from PROC VARCLUS) and the 29
categorical variables. This technique is not a variable selection technique, but rather a variable elimination method (Aggarwal, 2011) which
gives the correlation between variables. And by using the correlations, highly correlated variables can be removed from the analysis. By the
correlation analysis performed, a heat map was generated. Thereafter, two numerical variables (Total Sales in Branch and Dairy Sales Total)
were identified as highly correlated with other variables, hence was removed from the analysis.
The code below was used to perform the correlation analysis of the data set given under 'data' and the variable set to be considered is given in
'var' (variable list available in Appendix 3). The output will be written to the file specified under 'out' attribute.
Figure 3.3 gives a part of the heat map generated for the correlation analysis. Compared to the other variables, Dairy_Tot_br variable and
sales_branch variable are correlated with many other variables. Therefore, these two variables were removed from the model.
3.3.2.3 Stepwise Regression
The next step was to take a sample of the data set and to perform Stepwise Regression for 23 numerical variables and 29 categorical variables, to
further reduce the number of predictor variables. By performing stepwise regression the total number of

Major Rock Units And Deformation Events
Figure 1: (A) North America with the location of Figure B outlined by the black box. (B) Simplified map of the tectonostratigraphic terranes
comprising the Superior Province with locations of mineral deposits. (C) Tectonostratigraphic terranes of Minnesota. The location of Figure 3a
is denoted by the black box. Terrane boundaries are denoted by thick black lines and iron formation is shown by thin red lines. Table 1: Major
lithologic units of the Wabigoon subprovince in Canada that are on strike with the rocks in the study area. Modified from Davis et al. (1989),
Fralick and Davis (1999), and Czek and Poulsen (2010). Figure 2: Lithostratigraphc correlation of major rock units and deformation events in
the Neoarchean terranes of Minnesota. ... Show more content on Helpwriting.net ...
Most drilled massive sulfide deposits and iron formation layers occur near the top of the volcanic pile and overly the flanks of the LLIC. Felsic
rocks underlying massive sulfide deposits in the top of the volcanic pile are FI and FII types. Rocks with a magnetic signature similar to known
massive sulfide deposits occur down section and over the center of the LLIC. These rocks are interpreted as having the highest potential for
hosting Au–rich VMS deposits. Mafic rocks of the Oaks Intrusion (OI) occur in the eastern part of the belt and have been dated at 2671±8 Ma
(Keatts et al, 2003). Likely time correlative to the OI, a magnetic mafic sill (Oaks Intrusion sill; OIS) intruded and inflated the volcanic pile after
or contemporaneously with the main deformation event (D2). Table 2: Magnetic susceptibility of common igneous rocks used for interpretation
and modeling. From Ford (2008) and Anderson et al. (2013). Figure 4: Profiles of magnetic data on cross sections A–A', B–B', and C–C'. The
location of these cross section lines is shown on Figure 3b and Figure 6. Location of massive sulfides (MS), the Lost Lake Intrusive Complex
(LLIC), magnetic halos (MH) surrounding the LLIC, the Oaks Intrusion sill (OIS), and faults (FLT) are labeled on residual field magnetic data
plots. Vertical and horizontal derivative techniques outline shallow, highly magnetic causative anomalies

What Correlation Between All Variables Were Computed By...
The correlations between all variables were computed by applying the Pearson product moment method. The correlations among all the
variables are presented in Table 1. Variables measured in this study, namely, Attitude, Subjective Norms and Self–Efficacy demonstrated strong
and positive correlation with Intention to enlist. With respect to Attitude towards military, the four dimensions such as Evaluation of working
Condition and benefits, Self and physical development, Perceived risk, and Teamwork and patriotism was found to be positively related with
intention to enlist in military. Subjective norm for military enlistment was positively correlated with intention to enlist in military. In addition,
there was a positive relationship between intention to enlist and a person's self–efficacy. Hence, overall relationship indicates the model showed
a strong and positive relationship to intention.
––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
Insert Table 2 about here
––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
The multiple regression analysis was performed to find out predictive factors such as Attitude towards Military, Subjective Norms, and Self–
Efficacy that account for the maximum proportion of the variance in criterion variable Intention to Enlist. The multiple regression was
conducted to determine the contribution of the independent variables in predicting enlistment behavior. Regression results indicate that the
overall model

The Level Of Self Esteem And Academic Performance Of...
Abstract
This study was conducted to determine the relationship between the level of self–esteem and academic performance of PSY105 student at the
HELP University Campus in 2014. Convenience sampling was used to collect the 30 samples from the population, without specific gender and
ethnicity. Based on the literature it is stated that having a high self–esteem produces higher academic performance. The researcher used an
existing Rosenberg Self–Esteem scale to obtain a raw data of each participant. The statistical test used is the Pearson Product–Moment
Correlation Coefficient. The study was based on a non–experimental correlational design. The results shows a significant negative correlation
between the level of self–esteem and academic performance, this concludes the level of self–esteem do influence academic performance.
The level of Self–Esteem and Academic Performance Self Esteem has been one of the elements that play a role in the student's life of education.
Past study has found high correlation between the level of self–esteem as the elements that affects academic performance, it shows that majority
of student with higher self–esteem would be enthusiastically motivated to get involved in the learning environment (Colquhoun & Bourne,
2011). The aim of this research is to determine the correlation between the level of self–esteem and academic performance. This research begin
focusing on two general factors of self–esteem first is the worth of self which

Pearson Product-moment Correlation Coefficient and Causal...
Assignment: Interpreting Correlational Findings Following are brief summaries of correlational findings, in which variables were found to be
significantly associated with each other. Your task is to determine which of the three major causal models (i.e., interpretations) could account for
each finding. Indicate in the table below, by placing an X in the appropriate space, which of these three models could provide a possible
explanation. Place an X in the space only if you judge the causal model to be possible & reasonably plausible. If you decide that the third model
is possible, generate two possibilities for what variable "C" could represent, and type a short summary (one to 4 words should be sufficient) of
these variables in ... Show more content on Helpwriting.net ...
Causal interpretation
–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
A Variables correlated (A & B) A(B B (A C B
–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
Having a pet in childhood (A) & ___X___ _______ _______ likelihood of becoming a CEO (B) Potential third Variables:
_____________________ _____________________ 2. A study of factors predicting profitability in bank branches found that branches with
friendly tellers (friendliness as rated by bank customers) were more profitable than were branches with less friendly tellers. Causal interpretation

Corporate Loyalty Essay
EMPLOYEES' MONTHLY SALARY AND ORGANIZATIONAL COMMITMENT
a Mini–Research
Presented to the
Decision Sciences Department
De La Salle University
In Partial Fulfillment
Of the Course Requirements
In DECSCI2 K34
SUBMITTED TO:
Dr. Alfredo Dimaano
SUBMITTED BY:
ABADILLA, Raina Crysta M.
SANTOS, Catherine Erika P.
TEJADA, Jan Patrizia S.
16 December 2013
ACKNOWLEDGEMENT
The authors would like to extend their deepest gratitude to the following people for their help and support, and have helped the authors in
making this study successful: Dr. Alfredo Dimaano, for his support, suggestions, and guidance, which benefited the authors in the completion of
the study. Also, the authors are beyond grateful to him for providing the ... Show more content on Helpwriting.net ...
A business may possess inferior employees but the huge amount of loyalty would have can send a very insignificant business to amazing
heights. Likewise, those employees with unsubstantial amount of loyalty may cause tremendous business to collapse.
DuPont being one of the largest chemical company in the world, it is a necessity for them to continue to work as effective and efficient as
possible. To help them with such we have conducted a study on employee loyalty. With this study, we aim to come with an output that will be
able to assist DuPont to design different programs to help improve the employee organizational loyalty. Through this we as well want to prove
that the amount of loyalty of the employees of a business plays a significant role in the success of the corporations.
Theoretical Framework
John Meyer and Natalie Allen proposed the Three Components of Commitment model, which explains how organizational commitment is a
psychological–related idea. They suggested three factors that affect how an employee sees his/her organization. With this knowledge and better
understanding, one can increase not only the engagement of the employees, but their well–being and job satisfaction as well. By using these
components together with various appropriate approaches, a manager now has the ability to effectively motivate and work with his/her team.
The first type is the Affective

Relationship Between Appraisals Of Strain And Of Gain And...
Introduction The study of Rapp and Chao (2000) aimed to understand the relationship between appraisals of strain and of gain and psychological
wellbeing of family caregivers of dementia patients. The study addressed the gaps in the literature related to applying caregivers' appraisals of
strains and of gains to predict both negative and positive affect on caregivers' wellbeing. Thus, Rapp and Chao (2000) proposed three
hypotheses. First, the study hypothesized that the greater caregivers appraise their role strains, the higher negative affect (NA) they would
experience on their psychological wellbeing and vise–versa. Second, the researchers predicted that the relationship between caregivers'
appraisals of strains and of gains and negative ... Show more content on Helpwriting.net ...
The introduction of the study, however, does not explain some concepts well. From the title of the article, Rapp and Chao (2000) emphasize the
scope of the study as caregivers' psychological wellbeing. During the introduction of the article, there is no specific conceptualization of the
term "psychological wellbeing", except for a brief mention that there are positive affect and negative affect related to psychological wellbeing.
Likewise, in the third hypothesis, the researchers express an interest in understanding objective stressors without providing a definition of
objective stressors. The lack of main concept explanation may mislead readers' understandings in the next sections. Design and methods In the
method section, Rapp and Chao (2000) present participants and interview procedures, measurement, and statistical procedures. Notably, the
researchers did not explicitly explain their study design. No information about the design and the duration of the research project was noted.
Regarding participants and recruitment procedure, the article proposes that 65 primary caregivers were recruited from three community–
dwellings. Among them, 27 caregivers were from a university–affiliated dementia clinic, 25 from a local Alzheimer's association, and 13 from
the community. The inclusion criteria show that family caregivers who provide daily living assistance or instruction to an older

The Relationship Between Sensitivity And Punishment And...
The Relationship between Sensitivity to Reward and Punishment and Eating Behaviours
Courtney Andrews
Royal Melbourne Institute of Technology University
Abstract
A study involving 252 participants undergoing the course Biological Psychology was carried out in order to examine the correlation between
sensitivity to reward (SP), Body Mass Index (BMI), weight and more frequent consumption of unhealthy fast foods, (e.g., high in fat and sugar).
The core results showed the participants found that sensitivity to reward was strongly negatively correlated with BMI and weight. However, both
these correlations are not statistically significant at the 95% confidence level. Alongside this finding, sensitivity to reward was positively
correlated with unhealthy fast foods, which leads to more frequent consumption of fatty and sugar rich foods. These values were also not
statistically significant. This research needs to consider gender balance inequality, environmental cues such the accessibility of fast food (e.g.,
the amount and distance these restaurants are from their home residence) and one time collection of data used.
The Relationship between Sensitivity to Reward and Punishment and Eating Behaviours
Undoubtedly, the obesity epidemic in western society has never been so prevalent as the rate continually is climbing. There is an ample body of
research that suggests that more frequent consumption of unhealthy fast

Difference Between Depression And Women Essay
More over the second hypothesis was that the mean difference in depression for men differed from the mean difference in depression for women
because according to Silverstein et al. (2013), women were 33% more likely than men to have pure depression and over 50% more likely to have
somatic depression. Finally, the third and last hypothesis was that the mean difference in self–esteem for men differed from the mean difference
in self–esteem for women because according to Sprecher, Brooks, and Avogo, (2013), in a study among Blacks, Hispanics, Whites, and Asians,
men had higher self–esteem than women across all races with the exception of black females who's self–esteem did not significantly differ from
black men. Method Participants The current study consisted of a total of 80 undergraduate students who were recruited from the University of
California Riverside. Consequently, the ages of the participants ranged from 18–25 years of age with the average age being 21 years of old.
Furthermore, the sample was comprised of 60 females of the total 80 participants. Over all, the majority of the sample consisted of 34 Hispanic
students, including Mexican American, Central American, and others. Next, 20 of the participants in the sample were Asian or Asian American
including Chinese, Japanese, and others. Moreover, the third biggest group of participants identified as White Caucasian, Anglo European
American, not Hispanic students who made up a total of 9 participants from the sample.

Sample of Math Ia Essay
Plan of Investigation
While watching National Hockey League (NHL) games, I often heard the play–by–play announcer mention at the start of the third and final
period how it would be tough for a team to come back from a one goal deficit. This led me to wonder just how difficult it was mathematically,
and how much previous periods affected the final one. In this project, I will investigate whether the scores at the end of the first period affect the
final score of NHL games.
I will gather the scores of 200 hockey games between 2005–2008 from the nhl.com website. I chose these years because the type of hockey
before and after the new Collective Bargaining Agreement is different in terms of goals scored per game, with more goals scored per ... Show
more content on Helpwriting.net ...
The trendline, known as the line of best fit or the least squares regression line, shows the linear equation which best explains the sums up the
data's trend. The formula on the right is the formula of the line of best fit.
As can be observed from these plots, teams who win at the end of the first period have a much larger range of data, with 26 separate points
versus 14 separate points on Team B's graph. Since the scatter plot does not use a thicker dot when numerous teams share one place on the plot,
this suggests that teams who lose at the end of the first period tend to have similar scores, as they have twelve fewer points than teams who win.
If a team loses in the first period, this means that its X–range must be smaller than that of the winning team. Since 9/26, or almost 35%, of Team
A's points are on 3 or 4 on the X–axis, it is logical for Team A to have a larger range. However, even disregarding 3 and 4 on the X–axis, Team
A's range is still larger than that of Team B's. There is a greater spread of data on the Y–axis of Team A, as well.
Note that when Team A scores one goal in the first period, there are instances of them ending the third period with five or six goals. However,
when Team B scores one goal in the first period, the most goals they ended up with is only four. This pattern is repeated when the teams score
two goals in the first period. With Team A, there are instance(s) when they end up with seven; with

Determining The Percentage Of People During The Future...
Abstract:
The purpose of this experiment is to predict the percentage of people in the future generation of contracting Type 2 Diabetes in their lifetime. In
order to find results on this information, research involving Type 2 Diabetes was conducted using several resources, including the American
Diabetes Association, CDC, the National Institutes of Diabetes and Digestive Kidney Disease, and. After gathering the information useful to
understanding how Type 2 Diabetes is contracted and who is affected, a small survey experiment was conducted using a random sample size of
approximately 241 senior students at W. B. Ray High School in Corpus Christi, TX. The survey was randomly conducted by distributing the
surveys through all senior English ... Show more content on Helpwriting.net ...
Conclusion (pgs. 14–15)
VI. Appendix 7 Raw Data (pg. 15)
VII. Sources
I. Introduction:
Research Question:Are there correlations between different risk factors that teenagers possess that attribute to Type 2 diabetes and what do they
mean in reference to the chances of future diagnosis and health?
Type 2 Diabetes is a prevalent and growing epidemic in South Texas, according to the American Diabetes Association. It is the community's
duty and obligation to recognize the problems and risk factors that attribute to Type 2 Diabetes, so that further generations can avoid these
lifestyle habits. Type 2 Diabetes is an insulin deficiency disease that occurs in people aged 40 or older, and is much more common than Type 1
Diabetes because it can be acquired genetically, but it is more commonly a progressive disease based on the individual's unhealthy lifestyle,
which is why adolescents are still at risk to contract Type 2 Diabetes. When a person has Type 2 Diabetes, they may suffer from insulin
resistance. The insulin levels in their body are too low, or the cells in a person's body do not respond properlyto the correct amount of insulin.
Insulin is a hormone produced in the pancreas that strictly regulates the use and amount of glucose (sugar) levels in an individual's blood. Sugar
must be stored for the future or used as energy by the body. Without insulin regulating an individual's blood sugar level, a person may become
hyperglycemic, with too high of a

The Mediating Roles Of Psychological Contract Fulfillment
Hypothesis For this study the authors gave five hypotheses. These hypotheses were related to the mediating roles of psychological contract
fulfillment, need for change and trust. Trust being the only one included in three of the hypotheses. For hypothesis 1 the authors hypothesized
that psychological contract fulfillment moderates the relationship of attitude toward change and change information, therefore change
information is positively correlated to psychological contract fulfillment. Furthermore psychological contract fulfillment would be positively
correlated to behavioral, affective, and cognitive dimensions of attitude toward change. For hypothesis 2 it was hypothesized by the authors that
perceived need for change influences the relationship between change information and attitude toward change showing that change information
and perceived need for change are positively correlated. Also that perceived need for change is positively correlated to the behavioral, affective,
and cognitive dimension of attitude toward change. For hypothesis 3a, it was hypothesized that trust moderates the relationship between attitude
toward change and change information, therefore there's a positive correlation between trust and change information, and trust and the affective,
behavioral, and cognitive dimension of attitude toward change. Furthermore, for hypothesis 3b, the authors hypothesized that trust affected
psychological contract fulfillment in a positive way. Lastly, for

Correlation as a Measure of Association Summary
Correlation as a measure of association summary
BSHS/435
January 24 2016
Correlation as a measure of association summary
Introduction
In this essay I will describe correlation is a measure of association as well as describe different methods of establishing a correlation between
variables. In this essay I will also explain advantages and disadvantages of each method, were each must be applied, and provide particular
circumstances and examples in which a researcher may want to establish correlation
Describe correlations as measured of association
"A correlation is a statistical to determine the tendency or pattern for two (or more) variables or two sets of data to very consistently" (Creswell,
(2012). any ... Show more content on Helpwriting.net ...
In situations where every/or nearly/case has its own unique rink, and there are no or a few ties, the data are said to be fully ordered" (Monette,
Sullivan & DeJong, (2011).The interval data " the most used measured of association for interval data is the correction or Pearson's r. The
correlation coefficient is mathematically related to both phi and Spearman's rho, making comparisons among them possible" (Monette, Sullivan
& DeJong, (2011).
"There are several different kinds of relationships between variables. Before drawing a conclusion, you should first understand how one variable
changes with the other. This means you need to establish how the variables are related – is the relationship linear or quadratic or inverse or
logarithmic or something else" ("Relationship Between Variables ", n.d) advantages and disadvantages for correlational research methods
"Correlation is a measure of association that tests whether a relationship exists between two variables. It indicates both the strength of the
association and its direction (direct or inverse). The Pearson product–moment correlation coefficient, written as r, can describe a linear
relationship between two variables" Correlation (n.d). As a human service professional and completing research there are advantages and
disadvantages to correlational research methods, such as using correlational research it allows us to collect data and determine the strength and
direction of what it is we

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