Difference Between Differences And Differences Between...

Difference Between Differences And Differences Between...
The results of analysis of variance (Table 3) showed that there were significant differences between
lines in the probability of 1% in terms of all traits; which indicating a high genetic variation for
studied lines. Existence significant differences and genetic variation among genotypes of lentil by
other authors such as Mostafaei et al, (2006), Bayoumi (2008) and Toklu et al, (2009) have also
been reported. Kumar et al, (2012) by studying 43 genotypes of lentil under field conditions found
high diversity for biological yield, seed yield and harvest index. Ruisi et al, (2015) worked on 15
accessions of lentil during two years and stated that high variation existed among genotypes in terms
of pheno–morphological and agronomic traits. In the present study, most (21.54%) and lowest
(4.79%) values of the coefficient of variation of error was observed in biological yield and days to
flowering, respectively. The mean of superior lines (Table 4) showed that a specific pure line with
high values for all traits not found; but desirable pure lines in terms of phenological traits, stem
diameter, number of pods per plant, plant height and seed yield were observed. Line No. 20
(ILL590) with large leaf length, high numbers of pods per plant, more stem diameter, fewer days to
flowering and maturity and high seed yield known as the superior line on weather conditions of
Shahrekord, Iran. After that, line No. 28 (ILL947) was with high levels of seed yield, stem diameter,
number of pods per
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Creating Social Connection
In the article Creating social connection through inferential reproduction: Loneliness and perceived
agency in gadgets, gods, and greyhounds by Epley, Akalis, Waytz & Cacioppo the researchers
conducted three studies. The purpose of the studies were to examine if loneliness was significantly
correlated with the anthropomorphic mental–state, if social disconnection increase belief in some
religious agents or actions, and whether the likelihood of attributing humanlike mental states or
traits to pets would be greater among people induced to feel social disconnection than among people
not so induced. Researchers made three hypotheses, one for each study. The first hypothesis was that
loneliness was significantly correlated with the anthropomorphic mental–state ratings, the second
hypothesis was that participants in the disconnected condition reported stronger belief in
supernatural agents than participants in the other two conditions combined. The last hypothesis was
that participants in the disconnected condition were more likely to select one of the three social–
connection traits than were participants in the other two conditions combined. After completing the
methodology, it was ... Show more content on Helpwriting.net ...
From the article by Epley, Akalis, Waytz & Cacioppo, it can be concluded that there is a relationship
to fill the gap of human social connection. What did the lonely human do to humanize their pet?
This could help explain the relationship between the pet and human. Perhaps some participants are
just normal pet owners, and some take their pet t work, dress them up in human clothes and even
read them bedtime stories. Understanding this information will allow us to know how far a person is
willing to go to fill the gap. To expand even further upon the idea researchers could examine the
cause of loneliness and divide the participants into categories to draw research–based

Investigating The Correlation Between The Primary Variable...
7. CONCLUSIONS & RECOMMENDATIONS
7.1 Summary of Results
This section summarizes the results of all the statistical tests that have been performed by this study.
The correlation analysis was performed between the primary variable of FEP Cost % and the Cost
Performance, Schedule Performance, Change Cost % and Schedule Change %. The results show
that there was a positive correlation between the effort allocated to Front–End Planning and the cost
performance of the project in DB system, Complex projects and Renovation projects. The schedule
performance was affected positively by the FEP effort only in projects delivered using CMR system.
In general, there was an observable trend of negative correlation between the FEP effort and the
change costs that occurred in a project. For this test, the statistical evidence was more significant in
the case of DB system, both Simple and Complex projects and New projects. Increase in FEP effort
reduced the schedule changes in projects only in the case of Renovation.
The following table summarized the results of the correlation analysis with the corresponding p–
values. A positive value for Spearman's ρ suggests positive correlation and a negative value suggests
the inverse correlation. P–values that are less than 0.05 are considered significant at the 95%
confidence level
Table 2: Spearman 's Rho & P–Values Summary of Correlation Analysis
FEP
Correlation Analysis Cost Performance Schedule
Performance Change
Cost % Schedule Change % ρ p

biology report for habituation of snail
TITLE
Habituation of snail.
OBJECTIVE
To investigate the effect of habituation of snails to a stimulus
To develope certain experiment skills, such as working safely, producing valid results, recording
results and drawing valid conclusions from results.
INTRODUCTION
The snails
Figure 1: Garden snail
Taken from http://abugblog.blogspot.com/2011/05/handsome–snail.html
Snails are one of the earliest known types of animals in the world. There is evidence that they
evolved more than 600 million years ago. They are able to adapt to a variety of living conditions and
they don't require large amounts of food. They have been able to continually evolve to survive the ...
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The snail is allowed to acclimatize to its new surroundings for a few minutes and its acclimatization
is indicated when its head has fully–emerge from its shell.
2. A clean cotton wool bud is dampened with water.
3. Between the eye stalks the snail is firmly touched with the dampened cotton wool bud and the
stopwatch is immediately started. The length of time between the touch and the snail being fully
emerged from its shell once again, with its eye stalks fully extended is measured.
4. As soon as the eye stalks fully reappeared, steps 3 to 5 is repeated for a total of 10 touches, and
how long the snail takes to re–emerge each time is timed.
5. The results is recorded in a suitable table and presented in an appropriate graph.
RESULTS
The number of stimulations
The time taken for eye stalks to emerge from the head of the snail/ seconds, s
1
26
2
25
3
23

4
19
5
20
6
17
7
15
8
15
9
12
10
11
Table 1: Time taken for eye stalks to emerge from the head of the snail for 10 touches of stimulus
Graph 1: Graph of time taken for snail to fully re–emerge from its shell against number of
stimulation
DISCUSSION
From the graph, we can see that the snail showed the habituation response towards stimulus. During
the first touch, the time taken for the snail's both eyes to fully re–emerge was 26 s. The duration of
time taken continue to decrease as the number of touches received

Athletic Burnout Research Essay
After receiving approval from the Institutional Review Board of the university and permission from
the coaches of the designated sports, we administered our survey packets to student athletes that
were willing to participate in our study. We found most of our participants in the Griffon Indoor
Sports Complex and Looney Arena at Missouri Western before or after their practice times. The
student athletes were asked if they would be willing to complete surveys over self–motivation and
athletic burnout. They were notified that their identity would be kept anonymous and that it would
not affect their sport or how their coaches/teammates viewed them since the coaches were not
present during the results. We asked them to read all questions carefully ... Show more content on
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Another purpose of this study was to see if there is a relationship between an athlete's self–
determined motivation and their athletic burnout. In designing this study, various sports were
organized into team sports (football, women's volleyball, women's soccer, and baseball) and
individual sports (tennis and men's/womens golf). Our final sample size was a total of 41 athletes at
Missouri Western State University. Twenty–one of them were individual–sport athletes and 20 of
them were team–sport

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.

Optimizing The Hypothalamic Hunger Regulation Mathematical...
OPTIMIZING AND VALIDATING THE HYPOTHALAMIC HUNGER REGULATION
MATHEMATICAL MODEL
Ms. Divya1, Dr. Saurabh Mukherjee2
1Research Scholar, 2Associate Professor, Department of Computer Science, AIM & ACT,
Banasthali University, Banasthali–304022, email: jangid.divya@gmail.com
Hypothalamus has a significant effect on the physiological functions of human body like Hunger
regulation, Energy balance etc. A mathematical model is being developed which mathematically
explains the functionality of Hunger Regulation. Some hormones also acts effectively during this
process plays as important role in this model. Hypothalamic Hunger RegulationMathematical Model
(HhRM). We are using statistical optimization tools to optimize and validate this Model. The ...
This Hunger Regulation process is simulated with the help of Hypothalamic Hunger Regulating
Mathematical Model (HhRM)[2]. HhRM is a mathematical approach for this homeostatic function
of human body.HhRM divided into five different steps. Each step represents the combination of
mathematical functions and variables. A simple binary function G (h) shows that whether the
hormones are secreted by internal organs or not. The hormonal signals explain by the random
numbers.Daubechies Wavelet function interprets the movement of Hormonal signals through Vegal
Nerve.The response to the Hormonal Signals is being generated by the hypothalamic receptors. For
this the concept of signal generation is used with scaling function with Entropy. The receptors
signals transferred to Central Nervous system.
The mathematical model HhRM is as follows: dH/dt = G^ ' (h)+f(h)D4^ ' (h)+ Em(s)Sc '(s)
WheredH/dtis the change in the processing of Hypothalamus, H with respect to Time t, G(h) is the
binary function f(h) is fractal function, D4'(h) is the Daubechies function, Em(s) is entropy measure
and Sc'(s) scaling function.
2. Objective
The objective of our study is to optimize the mathematical model HhRM. In previous version of
HhRM the simple scaling function was being used. Here our objective is to study

Internet Subdiction : A Major Cause And Effects Of...
The results of the study done by Buchanan, J., O'Mara, J., Pistner, M., Young, K. were as follows;
first, boredom was one of the factors identified by participant as being a major cause in dealing with
their use of the internet.Secondly, symptoms of internet addiction found in this study were being
engrossed with the internet, anxiety when not using internet, lying and covering up internet use,
negative impacts on real–life functioning. The overuse of the internet can lead to depression or
increased depression, social isolation, loss of job, financial debt, divorce, underachievement in
school, and tension in relationship with family.
The results in the study by Howard, M. O., Li, W., O'Brien, J. E., Snyder, S. M. were as follows;
first, students tended to first access the internet when they were about 9 years old. Secondly,
students first started having problems with their internet use when they were about 16 years old.
Some of the symptoms of internet addiction found in this study were sleep deprivation,
underachievement in school, lack of exercise, lack of social activities, lack of concentration,
negative affective states, etc.
The results of the study done by Becker, B., Montag, C., Panksepp, J., Sindermann, C. were as
follows; first, females scored higher than males on the ANPS, aka affective neuroscientific
personality scales, scales of care, sadness, fear, spirituality, and anger. Males scored higher than
females on the GPIUS–2, aka generalized problematic

Essay On Cell Morphological Features
Modeling of changes in cell morphological features based on transcriptomic data}
We leverage the significant cross correlation between the $CMs$ and related transcriptomic profiles
to predict cell morphological states for a transcriptomic profile of interest (Figure 1, Step IVa)
cite{11}. We hypothesize similar transcriptomic profiles that mimic a query gene expression pattern
can be applied using appropriate computational model to predict changes in cell morphological
features in response to a compound treatment cite{13}.
We use LASSO to fit a regression model for changes in cell morphology and gene expression
profiles in response to treatment with a specific drug or small compound molecule. We fit the model
by using cell ... Show more content on Helpwriting.net ...
We repeated these procedures for 9515 transcriptomic queries (all transcriptomic profiles in
database repository) (Figure 1, Step IVb).
subsection{Application} subsection{Identification of most significant cell morphological
phenotype changes}
The magnitude of cell morphological changes in response to the compound treatment when
comparing with the DMSO treatment indicates the significance of morphological phenotype
changes (Figure 1, Step IVa) cite{4}. Our method can be applied to identify a set of query–specific
cell morphological gene sets, and model the numerical value representing morphological changes
which can give rise upon treatment with a compound molecule. We evaluated the ability of our
method to identify most significant $CMs$, where the alterations in morphological phenotypes are
re–identified through an instructional application of the method. We made use of three classes of
similar transcriptomic profiles with gene expression signatures of the textit{NOMILIN},
textit{ZARDAVERINE} and textit{HYDROCOTARNINE} drugs with no significant intraclass
correlation. All selected queries were considered active based on the significant textit{p–values},
calculated as the distance between treatment and control samples of Multiplex cytological imaging
assay cite{19}. We use the predicted values representing

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

noise reduction in data analysis
NOISE REDUCTION IN DATA USING POLYNOMIAL REGRESSION
Geetha Mary A, Dinesh Kumar P, Girish Kumar K, Gyanadeep N
School of Computing Science and Engineering, VIT University dinesh.venkata@yahoo.co.in
Abstract:–Noise is common in data which hinders the data analysis. We consider noise as low–level
data errors or objects that are irrelevant to data analysis. Data cleaning technique reduces the low–
level data errors but not irrelevant objects. To reduce both types of noise there are three traditional
outlier detection techniques distance–based, clustering–based, and an approach based on the Local
Outlier Factor (LOF) of an object. In this paper we introduce a new method for noise reduction
using polynomial regression and spearman's rank ... Show more content on Helpwriting.net ...
Using the equations we get values for x and y. Now we apply spearman's rank correlation coefficient
ρ for the obtained results. If ρ ϵ (–1,1) then the data is not noise, if the ρ value is not in that range
then we consider it as noise.
3. Numerical Evaluation Let us take data set as follows
X
Y
5
8
6
9
7
10
8
11
9
12
10
13 The equations obtained from the above data set are
Y=0.990 * x ^ 1.000+ 3.931
X=0.989 * y ^ 1.000– 3.249
Now we take another data set to test using above equations and if the results are not approximately
similar to the obtained results for all the models then we consider the data to be noise or outlier. For
example we take the test data set to be as follows,
X
Y

112
125
167
171
For test case 1 (112,125)
Taking x(112), then y=114.811
Taking y(125), then y=120.376
For test case 2(167,170)
Taking x(167) ,Y=169.261
Taking y(170) ,X=166.87
For the obtained results we apply spearman's rank correlation coefficient ρ, ρ = 1–(6∑di2/n3–n) if
the obtained result lies between (–1,1) then the data belongs to that set and if not in that range then it
is considered as noise or outlier.
By applying for the above results we get,
For test case1 (112,125) ρ=1–((6*((114.811–125)2+(120.376–112)2))/(2*(4–1))) ρ = –172.973
For test case2 (167,170) ρ=1–(((6*(167–166.87)2+(170–169.261)2))/(2*(4–1))) ρ =0.436979 so
from the obtained results test case1 is considered as noise

Mphil
1/22/07 252corr (Open this document in 'Outline' view!) L. CORRELATION 1. Simple Correlation
The simple sample correlation coefficient is [pic] or if spare parts [pic], [pic] and [pic] are available,
we can say [pic] Of course, since the coefficient of determination is [pic][pic] , [pic] and it is often
easier to compute [pic] and to give the correlation the sign of [pic] . But note that the correlation can
range from +1 to –1, while the coefficient of determination can only range from 0 to 1. Also note
that since the slope in simple regression is [pic] , [pic] or [pic] or [pic]. The last equation has a
counterpart in [pic] , where [pic] is the population correlation coefficient, so that testing [pic] is ...
Example: [pic] applicants are rated by [pic]officers. The ranks are below. [pic]Note that if we had
complete disagreement, every applicant would have a rank sum of 10.5. [pic]. The Kendall
Coefficient of Concordance says that the degree of agreement on a zero to one scale is [pic]. To do a
test of the null hypothesis of disagreement [pic], look up [pic] in the table giving 'Critical values of
Kendall's [pic] as a Measure of Concordance' for [pic] and [pic], [pic]so that we accept the null
hypothesis of disagreement.. Example: For [pic] and [pic] we get [pic], and wish to test [pic] Since
[pic] is too large for the table, use [pic]. Using a [pic] table, look up [pic] . Since 9 is below the table
value, do not reject [pic]. 4. Multiple Correlation If [pic]is the coefficient of determination for a
regression [pic], then the square root of [pic] , [pic] is called the multiple correlation coefficient.
Note that [pic] where [pic] is the sample variance of [pic], and that for large [pic], [pic]. 5. Partial
Correlation (Optional) If [pic], its multiple correlation coefficient can be written as [pic] or [pic].
For example, in the multiple regression problem, we got three multiple correlation coefficients [pic],
[pic] and [pic] If [pic] and we compute the partial correlation of [pic]we compute [pic] , the
additional explanatory power of the third independent variable after the

What Does The Influence Of Social Determinants Factors...
Copy and paste your text here and click "Check Unique" to watch this article rewriter do it 's thing.
Have no text to check? Click "Select Samples".Assessment 3: Applied Research Assignment –
Joanne Ng 588141 To what extent does the influence of social determinants factors have on
happiness? Happiness is usually expressed as "the point to which an individual assesses the total
worth of his or her existence as a whole positively" (Veenhoven, 1993), and regularly, considered on
an ordinal scale of answers to biased questions. Most experimental findings consume various kinds
of self–reported ideals on happiness or particular well–being dignified from various scaling
methods. Happiness is a personal and multi–dimensional notion – every distinct person depicts it in
a diverse way, it is comparative, and it is determine by an extensive range of influences, involving
individual personalities. Consequently, allowing it to be assessable and creating causal relationships
a task. The information and experimental studies distinguish between the natures of happiness and
noticing the connected expressions – life's satisfaction and well–being. The explanations of
recognised ideas overlap through the proposal on happiness and are separated into numerous
categories. In this study, the main ideas associated to happiness and their factors are shortened in
order to pinpoint the major distinctions between the suggested terms and to determine the theoretical
agenda. The pursuit for

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

Pest Analysis on Airasia
Introduction The aim of this report is to understand the consumer's behaviour and consumer's
perception on IKEA home office furniture and market strategies in terms of brand awareness,
design, price and service. As the consultants of IKEA Company we found from the secondary
research that the number of self employed people at home increasing steadily and most of them
work at home (Mintel report 2006). The market trend is that people working at home, with
technological advances and more businesses try to find more flexible working practices. For this
reasons the demand for home office furniture has increased. Therefore, this research is trying to give
some of marketing strategies of home office furniture business for IKEA Company in ... Show more
content on Helpwriting.net ...
Data collection and analysis proceed in parallel and interact, and because of the nature of the
material gathered, results cannot be subjected to tests of statistical probability. For this reason,
organisations have been less inclined in the past to sponsor such research, even though the evidence
produced may well reveal much richer data than that obtained through a simple quantitative
questionnaire. Quantitative Research: Quantitative methods are those in which data are collected
and subsequently analysed through a process sometimes mockingly referred to as 'bean–counting'
(Daymon 2002). Normally this is kind of method use for surveys with questionnaires. . The Type of
Research in This Project: From analysis above, both quantities and qualitative research have
advantages and disadvantages. Therefore our decision is use both of them in order to improve the
quality of our information. Focus group: This project was started with the qualitative research. We
conducted two focus groups. The participants were people who work at office and at home in UK.
We had 8 members who were selected by us with experience and fully of knowledge about the home
office furniture in each group, and the venue was in one of our project member house. A moderator
leaded the discussion about our Ikea topic. We provided drinks and snacks to the participants. The
focus group members felt comfortable and expressed a lot of useful

The Great Depression and The Global Economy
Since the great depression, the global economy has been facing a number of ups and downs. With
the markets being built rapidly and crashing down in the other instant, elements that actually make
up the skeleton of the international economy seems to have correlated variables. These variables
seems to have been correlated with each other in numerous combinations and their correlation is
what makes the market fluctuate. The volatility of the global market becomes more apparent in
times of recession when the correlation between variables like stocks, bonds, US dollar, Euro, gold
and oil becomes more apparent. Therefore, it is of paramount importance that these correlated
variables should be studied with a very keen eye. Since the link between currencies, commodities,
stocks an bonds runs very deep, change in any one of them seems to have a profound impact on the
rest hence changing the face of the market.
Background:
One way to describe the correlation between the major assets of the international trade is that it
should be seen as what compels the market that create dynamics between these variables. During
long periods of prosperity and financial stability, players of the international trade ease up about the
risk of loss either through a systematic underestimation of those risks, or a decline in their risk
assessment tactics due to increasing wealth, or both. This aversion to the idea of risk and keeping
that period of prosperity continuous makes the investors greedy, and

Collaborative Proposal Analysis
any knowledge about the items. For example a book recommender system does not require any
knowledge about the contents in the book, the author and price etc. Collaborative recommendation
approaches take a matrix of given user–item ratings as the only inputs and produces the prediction
of a new item and a list of 'N' recommended items. However, the top 'N' list does not contain the
items that the current user has already bought. The algorithms for collaborative filtering can be
grouped into two general classes: memory based and model based. Memory–based recommendation
Memory–based algorithms are heuristics that make rating predictions based on the entire collection
of items previously rated by the users [4]. The different kinds of ... Show more content on
Helpwriting.net ...
U = f(Alice; Bob; John; Smith) ; I = f(Book1; Book2; Book3; Book4); To predict the unknown
rating of Alice for Book4, first we should find the similar users of Alice. One common measure used
in recommender systems is Pearson's correlation coefficient. The similarity Sim(x,y) of user 'x' and
'y', given the rating matrix R, is defined as follows. Now to make prediction of Alice for Book4, we
can use the following formula. Therefore, by using the above calculation schemes one can predict a
value for any unrated item in the rating database. In the literature, there is a number of metrics
available like cosine similarity, mean squared diff erence or spearman's rank correlation. However,
at least in the majority of the domains the Pearson's coefficient method outperforms other measures
of comparing users for determining similarities between users [4]. However, memory–based
approach suffers from two basic problems: sparsity and scalability [6]. Sparsity refers to the
difficulty that most users rate only a small number of items. As a result, the accuracy of the method
is often quite poor. As for scalability, memory–based approaches often cannot deal with large
number of users and items [6]. Item based nearest neighbor recommendation Several studies
revealed that user based approaches are not applicable, when there is a large number of users and
items in the system. In particular, the need to scan a large number of

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

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

IB Geography IA
How do levels of urban stress, such as noise levels and pollution, vary when moving further away
from the CDB of Bandung, Indonesia? School: Mutiara Nusantara International School Candidate
Number: Candidate Name: Constantijn Louis Pennekamp Word count: 2,410Table of contents: Front
Page..........................................................................................1 Fieldwork question and Geographic
context.................................2 Hypothesis..........................................................................................4
Justification and procedures............................................................5 Investigation and Presenting of
Data.............................................6 Data and
Figures...............................................................................8 Analysis of Data and
figures......................................................... .10
Conclusion....................................................................................... 12
Evaluation.........................................................................................13 Fieldwork Question: ... Show
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I took 10 pictures with a 10 second interval between each one. Later during the processing of the
data, I will count the amount of cars (only) visible on the picture, and calculate an estimate of cars
passing per hour. ( 350) The reason what we resorted to simple techniques to obtain necessary data
is simply because high tech and accurate equipment is too expensive to buy, especially in Indonesia,
where recourses are very limited. This would however lead to more variables than one might like,
but this could easily be handled by controlling other key elements, making the data as reliable as
possible. Materials used –HD camera –HQ sound Recorder –Vaseline –Cardboard –Measuring tape
–Stopwatch 1. Prepared 9 Vaseline Samples by stapling a white sheet of paper on cardboard and
applying Vaseline on a pre measured circular area 2. Went to each of the 9 sites and: sticking the
Vaseline samples vertically in a Dry and safe place as near to the read as possible, measure the speed
of 20 cars by counting mow much time it took for a car to travel 50 meters and calculate the mean
speed of cars within the area, take 10 pictures from the highest elevation possible with an interval of
10 seconds of the nearest road from the station, and recording the sound produced by the area for 5
minutes long and later on measuring the mean decibels in a computer software. Investigation The

A New Client For A Cereal Making Company
A new client for a cereal making company has asked us to help promote their cereal as "healthy".
This new cereal is called *name here*, and it is our job to determine the correlation between calories
and potassium in order to make the new cereal "healthier" by lowering the calories but increasing
potassium. We have researched the interrelationship between calories and potassium and this paper
is a product of our analysis. We have compared data between the top fifteen cereals and have found
that calories and potassium have a negative correlation. However this is only a coincidence as it is
other factors, such as sugar, fiber, protein, and fat that correlate most directly to calories, while
certain ingredients have more potassium than others. Calories and potassium are both essential parts
of the diet that the human body needs in order to survive. A calorie is a unit of energy that measures
how much energy the body gets just by eating or drinking it. It is generally thought that the higher
the calories, the worse it is for the body. It is thought that way because the extra calories that the
body doesn't use is converted to fat, and too much fat is linked to health problems such as arthritis
(joint degeneration), heart disease and diabetes. Potassium is an electrolyte (meaning it conducts
electricity in the body), it is essential for the proper function of cells, tissues and organs. It is crucial
for heart function and the contraction of smooth and skeletal muscles. Too much

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

Transformational Leadership And Guest Satisfaction Ratings...
Introduction The following study was selected for summary based on the subject matter. Leadership
in any industry has been an object of study for centuries. As the name implies, transformational
leadership is a leadership style in which the leader attempts to better understand the goals of the
followers and inspires a transformation geared towards achieving those goals. In the book
Leadership: Theory and Practice, Northouse explains that transformational leadership is "An
encompassing approach, [that] can be used to describe a wide range of leadership, from very
specific attempts to influence followers on a one–to–one level, to very broad attempts to influence
whole organizations and even entire cultures" (2013, p.186). This study was designed to determine if
there is a relationship between transformational leadership and guest satisfaction ratings within the
hospitality industry. The hospitality industry as whole is geared towards providing quality and
satisfactory service. Establishing the role of transformational leadership in providing such service
could prove beneficial in the way that managers in the industry are trained and their methods of
leading.
Discussion
Padron's dissertation Transformational Leadership of Hotel General Managers and Guest
Satisfaction Ratings: A Correlational Study, was obtained through the ProQuest Digital Dissertation
and Thesis Database. The research questions addressed include; to what degree does
transformational leadership of a hotel GM

Does Lower Grade Point Average Equate to Poor Health? Essay
In this study piloted by Trockel, Barnes and Egget (2000) they hypothesized that poor health
behaviors would be greater amongst those with low grade point averages. The predictors of the
correlation study were: exercise, eating, sleep habits, mood states, perceived stress, time
management, social support, spiritual habits, number of hours worked per week, gender and age.
The outcome variable was the students' grade point averages. The goal of the study was to see which
health behavior affected grade point averages the most. The participants were 200 freshmen. The
university's Office of Institutional Studies gave the names, on–campus addresses and phone
numbers of 200 randomly selected freshmen. The authors used the health behavior ... Show more
Questions asking about the number of hours they work per week were also collected and the
students' gender and age were collected from the university. The students were mailed the survey, a
cover letter a consent form. They were given 9 days to do the survey. The students that did not
complete the survey were contacted and they did the survey on the telephone. 143 completed the
mail survey and 43 completed the telephone survey. The total usable rate was 92%. The authors used
the spearman's rank order correlation to analyze how each item related to academic performance and
the stepwise regression analysis to identify which predictor was the main effect on academic
performance. The variables later weekday and weekend wake up times, later weekday and weekend
bed times, number of hours of sleep on weekend nights and number of hours worked per week were
responsible for low GPAs. No other variable affected academic performance. The relationship
between sleep habits and grade point averages was the strongest and so it supports the hypothesis for
this study (Trockel, Barnes & Egget, 2000). This hypothesis is relevant to my own topic area
because I will be studying if practicing a healthy lifestyle affects students' performance. The
conceptual variables for this study were almost identical to my variables. For my study, my
predictors are going to be exercise, eating habits, moods throughout the day and sleeping habits. I
will

Lab Report On The Urinary Concentration Of Tnf-
participant in sterilized urine containers and used to determine albumin in 24 h urine specimen. The
urine levels of the biomarkers were normalized to the urinary creatinine concentration to control for
variations in hydration status. Serum and urinary TNF–α: serum levels were measured by an
enzyme–linked immune absorbent assay (ELISA) using commercially available standard kits
(Quantikine high–sensitivity human TNF–α Research & Diagnostic Systems, Europe Ltd, Abington,
UK). The urinary concentration of TNF–α was determined using an enzyme–linked immunosorbent
assay (ELISA) with a Human TNF–α Quantikine ELISA kit (DTA00C; R&D systems, Minneapolis,
MN, USA). The study protocol was approved by the Ethical Committee of Faculty of Medicine,
Zagazig University and informed written consent was obtained from each individual. Statistical
analyses Were performed using the Statistical Package for the Social Sciences for Windows (version
22.0; SPSS Inc., Chicago, IL, USA). Data were expressed using descriptive statistic (mean ±
standard deviation) and were analyzed. One–way analysis of variance (ANOVA) test was done to
compare different parameters between more than two groups. Pearson correlation coefficient was
used to assess the association between serum and urinary TNF–α levels, clinical, biochemical tests
and other studied metabolic parameters in patients with diabetic nephropathy. P–values were
considered significant if < 0.05).On the other hand there were no significant

Statistical Handling Data Coursework on High School Students
Statistical Handling Data Coursework: High School For this handling statistical data coursework I
will be investigating the heights and weights of students of years 7 to 11 in High School. Although
this is a fictitious school the data is based on a real school. I will look for a trend in the heights and
weights of the students to see if the taller they are, the more they weigh. This is my hypothesis. My
Null hypothesis is that there is no correlation between height and weight, and my Alternative
hypothesis is that there is strong, positive correlation between them. I will then investigate the
heights of boys in years 7 and compare them to the girls, and then do the same in year 11. I will then
be able to compare these two sets ... Show more content on Helpwriting.net ...
Height and weight is continuous data so only some graphs and calculations can be done. I have
decided to select a sample size of 100 students because 1183 students are too many. I won't be able
to compare the data well since I will have such a wide range of results. I also won't be able to fit all
the information on one graph or one box–plot making the comparison even more difficult. I will be
able to cope with 100 students' heights and weights better. In order to get a sample of 100 students, I
will take a stratified sample of each year group, and then of each gender within the year groups. I
will use stratified sampling because using this I can get a fair sample that is proportional and to the
ratio of the original number of students within each year group out of the whole school. Once I have
my stratified sample of each year group, I will use random sampling to choose which of the students
I will take my data from. This is a fair way of sampling due to the fact that there will be no biased
decision as to who is picked for their data. The following data is what I will use in order to take a
stratified sample of 100 students: Year Group Number of Boys Number of Girls Total 7 151 131 282
8 145 125 270 9 118 143 261 10 106 94 200 11 84 86 170 Total 604 579 1183 To take a stratified
sample of the year groups I will do the following calculations: Year Group Calculation Total
(answer) 7 (282/1183) x 100 = 24 8 (270/1183)

Quantitative Data Anaylsis Using the IBM SPSS Statistics...
This paper is an illustration of quantitative data analysis using the IBM SPSS Statistics software. It
does not provide the details of technical skill to operate SPSS but focuses on developing a set of
decisions and actions in order to set up, describe, manipulate and analyse data in the specific context
of the study of Jackson and Mullarkey (2000). In order to fulfil the task, this paper illustrates a step–
by–step of actions that were made on the data. It also gives the insight into the determination of each
step that helps interpret the findings from the data. 1. DATA SET UP IN SPSS It is important to set
up the data before conducting further activities on data by using SPSS. The establishment of data
needs a preliminary handling of the ... Show more content on Helpwriting.net ...
B, 3 = C, 4 = D Age Age of Participant None Gender Gender 1 = Female, 2 = Male Auto1 Individual
Timing Control 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal Auto2
Individual Method Control 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal
Demand4 Production Pressure 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal
Auto5 Role Breadth 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal Demand3
Monitoring Demands 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal Auto6
Task Variety 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal Demand1
Problem–solving Demands 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal
Demand5 Production Responsibility 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great
deal Demand2 Skill Utilisation 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal
Auto3 Collective Timing Control 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great
deal Auto4 Collective Method Control 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A
great deal Social1 Social Contact 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great
deal Social4 Social Support 1 = Not at all, 2 = A little, 3 = Somewhat, 4 = A lot, 5 = A great deal
Social2 Group Cohesiveness 1 = Strongly disagree, 2 = Disagree, 3 = Neither agree nor disagree,

The Dynamical Behaviors Of Complementary Correlations...
REFEREE REPORT MANUSCRIPT # SREP–16–20322 PAPER DESCRIPTION In the paper titled
"The dynamical behaviors of complementary correlations under decoherence channels", Du et.al
have investigated the relationship between complementary correlations (CC) and the entanglement
over noisy channels. In particular, for bipartite qubit systems, it has been shown that there exists an
optimal threshold to which CC has to be compared in order to determine the dynamical behavior of
entanglement. Furthermore, authors claim to derive a novel threshold on environment parameter as
well which is based on the Pearson correlation between measured outcomes of complementary
observables. This topic has already been investigated to some extent in Ref. [1], the main novelty of
this work is the inclusion of the decoherence. COMMENTS AND DECSISION Besides a number of
grammatical and spelling typos, the paper has been demonstrated a relation between CC and
entanglement over noisy quantum channels for bipartite qubit systems. Also, in my opinion, the
claims based on the results haven 't been exaggerated. In view of all of this, I can recommend
publication of this paper in the scientific reports provided the authors address the following
questions/concerns appropriately: QUESTIONS AND CONCERNS From the

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.

Advantages And Disadvantage Of A Company's Control Of...
Disadvantages:
1. The manufacturer company does not have any control over the of goods distribution method.
2. If the distributor company does not distribute the goods for any reason, the producer will be
paralyzed due to the unity of the distribution channel.
3. The company's financing system is subject to the payment of a single source.
4. If the performance of the distribution system is not satisfactory to the manufacturer, the
manufacturer company cannot demonstrate a proper and rapid response.
5. In the long–term, the distribution company will effectively determine the manufacturer's policy,
and the manufacturer must comply with the distributor's decisions.
6. The repayment period of the cost of goods sold to large distribution companies ... Show more
The capillary distribution channel is one of a variety of distribution channels that performs this task
in retail mode and aims to increase the number of customers who purchase goods and increase the
level covered.
Statistical population, sampling method and sample size: The statistical population in this research is
all the broadcast industry companies and the sample considered is Hafez broadcasting company. In
the past few years, according to the statistics and reports of commerce department this company is
among the top 100 companies in Iran with distributing more than 20 thousand tons of various types
of basic goods and quotations, and freed at a constant rate in the country in particular in the year
2010.
To conduct sampling, cluster sampling was used in this research. At first, five branch offices of
Hafez broadcasting company were randomly selected, and then at the next stage, among the
directors and sales and planning authorities, these branches were randomly being selected as
research samples.
Among of 100 distributed questionnaires between employees, 90 questionnaires that were fully
answered were selected for

The Influences On Attitudes Across Demographic...
There are two ways to answer this question: comparing the influences on attitudes across seven
constructs of the HBM; and comparing attitudes across demographic characteristics. Correlation:
Total Health Belief Score by Seven Constructs First, to determine the difference of influences on
attitudes by each of the seven constructs in the HBM, the total health belief score generated in
research question 2 was used as the dependent variable, and the seven constructs in the PCHAB
questionnaire were used as independent factors. An ANOVA for linear regression analysis was
performed to test if there were significant differences (see Table 6.1). The results showed that the
interaction effect between seven constructs and the total health belief score was significant (f =
19284.073, p = 0.000). In accordance with the detailed correlation coefficients for the seven
constructs listed in Table 6.2, the regression equation could be demonstrated as: The total health
belief score = 0.135 Perceived Susceptibility + 0.103 Perceived Severity + 0.133 Perceived Benefit
+ 0.171 Perceived Barriers + 0.132 Cues to Action + 0.131 Self–efficacy + 0.200 Subjective Norms
(p = 0.000). Consequently, the order of the seven constructs in the extended HBM, from the most
influential one to the least, is shown as follows: Subjective Norms > Perceived Barriers > Perceived
Susceptibility > Perceived Benefit > Cues to Action >

The Gentrification of Vesterbro
BIRKERØD INTERNATIONAL GYMNASIUM
SØNDERVANGEN 56, 3460 BIRKERØD, DENMARK
BIRKERØD INTERNATIONAL GYMNASIUM
SØNDERVANGEN 56, 3460 BIRKERØD, DENMARK
What are the physical and statistical signs of gentrification in Vesterbro in Copenhagen, Denmark?
Emil , 000632–022
Supervisor: Mette
May 2013
Wordcount: 2360
What are the physical and statistical signs of gentrification in Vesterbro in Copenhagen, Denmark?
Sophus Emil Petersson, 000632–022
Supervisor: Mette Bahnson Weber
May 2013
Wordcount: 2360
Geography HL Internal Assessment
Geography HL Internal Assessment
Photo; courtesy of Jonathan Sandidge
Table of Contents Aim of the report: 3 Research question: 3 Geographical context 4 Introduction to
Vesterbro: ... Show more content on Helpwriting.net ...
Hypotheses:
Hypothesis 1:
At least 50% of the buildings in and around Istedgade have been renewed.
The renewal of buildings in Vesterbro has been going on now effectively for 10 years, along with
the pace of the reurbanisation, which is the inward movement of people from the countryside to the
city, (reurbanisation is the opposite of counter–urbanisation) of Copenhagen. Most buildings have
been renewed on the inside, with improved hygiene and living standards, but the outside has in most
cases been left with the original façade to withhold the authenticity of the working quarters of
Copenhagen.
Hypothesis 2:

There is a strong correlation between the size of apartment and the income of the surveyed people.
This seems obvious as more income usually means a bigger apartment. However; in Vesterbro there
aren't very many large apartments, as most of the buildings are from 2 centuries ago. The renewal of
the buildings however may have lead to bigger and lighter apartments. The pricing of apartments in
Vesterbro have gone up, due to the fact that it is now becoming a very trendy area. This is mainly
because it is has undergone renewal, but kept it's authenticity, and because the crime rate has gone
down, or rather been moved to the North West part of Copenhagen.
Methods of data collection:
The following will be an outline on the process leading up

SAT Scores Research Paper
Are SAT Scores and Family Income Independent of each other in the Test–Takers of 2013
Worldwide?
Tiffany Cacy
02–22–16
IB Math Studies SL
Mrs. Mello
Yosemite High School
Introduction Thousands of students take the SAT examination every year. It is a requirement for
colleges worldwide and is a primary factor in college acceptances, making high scores very
desirable and valuable. Many prestigious colleges are very difficult to get into and will not consider
students unless they score well on the SAT. This puts a lot of pressure on students who hope to
attend such schools. Many go to great lengths in order to give themselves an advantage.
Unfortunately for middle and lower class students, those measures generally cost a considerable ...
Graph 2 shows the positive and consistent correlation between SAT scores and family income. This
is also supported by the r2value .9582110109 found by Pearson's Correlation Coefficient Formula.
(This graph was created using Microsoft Excel.)
Chi–Squared Chi–Squared is used to determine whether or not there is an independent or dependent
relationship between two variables. Chi–Squared is represented by the following equation. x2=(fo–
fe)2fe fo= Observed Value
fe=Expected Value
Observed Values:
B1
B2
Total
A1
A
B
A+B

A2
C
D
C+D
A3
E
F
E+F
Total
A+C+E
B+D+F
N
Calculations of Expected Values:
B1
B2
Total
A1
(A+C+E)(A+B)N
(B+D+F)(A+B)N
A+B

Statisitical report Essay
BU1007 Business Data Analysis and Interpretation Singapore Campus, Study Period SP53, 2013
Statistical Report Analysis of Case study 3: Heavenly Chocolates website transactions Prepared for
Dr Tjong Budisantoso Done by Mr. Keung, Tseung Student ID : 12776910 20/12/2013 Table of
contents Introduction
–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
Question a
–––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––
Question b ... Show more content on Helpwriting.net ...
Vice versa, the less time spent and page viewed, the less payment made. The total amount of
transaction have reached two peak points recorded $758.86 on Monday and $925.43 on Friday.
From Tuesday to Thursday, has a slight decline from $414.86 to $294.03. Furthermore, on both
Saturday and Sunday, the transactions have a relative low amount compared to the rest of the days,
recorded $394.4 and $222.15, respectively. c). You have to develop a scatter diagram and compute a
simple correlation coefficient to explore the relationship between the number of pages viewed and
the amount ($) spent (use horizontal axis for the number of pages viewed). Correlations Analysis
Step 1: Scatter Diagram: the amount ($) spent and the number of pages viewed Independent
variable: Number of pages viewed Dependent variable: Amount Spent Step 2: Elaboration The
Scatter diagram illustrate a strong positive linear correlation and a direct relationship between the
two variables. To apply the Coefficient of Correlation (r) formula: Correlation coefficient =
0.9(Solved by Excel) When r is close to 1, which proves it is a positive correlation, so there is a
direct relationship can be seen between the number of pages viewed and the amount spent , and the
value of 0.9 is rather close to 1.00, so it can be concluded that the

Factors That Affect The Combined Analysis Of Sa And Iud
In this section, we present a four–step methodology to quantify distinct factors that affect the
combined analysis of SA and IUD in real domains, as well as the potential benefits of this type of
analysis. Basically, the proposed methodology takes into account the domain 's temporal dynamics,
the sampling sensitivity of the methods and the observed reciprocity between the collective opinion
and opinions propagated by opinion–leaders. Through this methodology, we intend to quantify some
important issues related to combine SA and IUD. We are not assuming a closed and complete
assessment on all existing issues, which comprise promising research directions for the
area.looseness=–1
subsection{Temporal Dynamics Analysis}
A main ... Show more content on Helpwriting.net ...
First, we derive the collective opinion $O$ of a whole data sample $D$, using a SA method existing
in the literature. Specifically, we adopt in this work the method SACI cite{jws2015}. SACI is
relevant to our goal since it was originally proposed for estimating efficiently collective sentiment
on data samples, instead of aggregating the sentiment derived for each individual document. Further,
the authors demonstrated that SACI is more effective in estimating the collective opinion than
aggregation–based SA methods. SACI represents $O$ as a distribution probability among the
sentiment classes positive, negative and neutral. Thus, we split $D$ into time units of equal size
(e.g., days, weeks, months). Then, we estimate the collective opinion $O_t$ using only the posts
belonging to each distinct time unit $t$. Finally, we perform a visual inspection on the derived
distributions. The more dynamic a domain, the more different are opinions estimated on distinct
time units.looseness=–1
In turn, we measure drifts on the subset of opinion–leaders over time as follows. First, we identify
the ordered list $L$ of top–k opinion–leaders on $D$ by using an IUD method. Specifically, we use
the presented in cite{iccs2015}, a meta–learning strategy based on PCA that combines linearly
orthogonal information exploited by distinct state–of–the–art IUD methods. We will call this method
as PCA–IUD. We chose PCA–IUD since it combines

The Effects Of Social Media On Students Essay
One–hundred and nine participants (15 women, 7 men, Mage = 22.4 years, age range: 18–25 years).
Some of the participants were from a university in North Carolina and some were asked via social
media post. Participants who were undergraduates received course credit for participating while
non–students did not receive compensation. Materials Social Media Use. Participants completed an
open–ended questionnaire examining how many minutes per day they spent on each SM platforms,
(i.e., Facebook, Twitter, Instagram, Snapchat, and Tumblr), how many times they checked it, and
how many times they upload a post or picture. Self–Esteem Assessment. Participants completed a
self–esteem questionnaire using Rosenberg Self–Esteem Scale (Rosenberg, 1965). Participants
indicated their self–esteem level answering a 10–item forced–choice questions on a 4–point
scale(0=strongly disagree to 3=strongly agree), with higher overall showing higher levels of self–
esteem . all." Higher scores indicated high levels of self–esteem. Depression Assessment.
Participants completed a modified Patient Health Questionnaire to assess symptoms of depression
(i.e., sadness, hopelessness, tiredness), (Kroenke et al., 2001). There were 7 questions and 2
questions were removed because of potential sensitivity to questions (0=not at all, to 3=nearly every
day). The questions were forced–choice and had a response set, and there were no neutral options,
and no reverse coding. Questions ranged from "Feeling down,

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

A Survey On Friend Recommendation Essay
A Survey on Friend Recommendation in a Social Bookmarking System
Bhavesh Jain1, Tejas Kadiya2, Ramesh Prajapati3, Dr.Samrat Khanna4
1M.E Computer Engineering Student, IIST–Rajpur
2Assistant Professor, IIST–Rajpur
3Dept. of Computer Science Engineering, Rai University, Dholka
4Dept. of Information Techmology, V.Vnagar
Abstract–The technique of Collaborative Filtering is especially successful in generating
personalized recommendations. Collaborative Filtering is quickly becoming a popular technique for
reducing information overload, often as a technique to complement content based information
filtering. More than a decade of research has resulted in numerous algorithms, although no
comparison of the different strategies has been made. In fact, a universally accepted way of
evaluating a Collaborative Filtering algorithm does not exist yet. In this survey, we explain different
techniques found in the literature, and we study the characteristics of each one, highlighting their
principal strengths and weaknesses. This Paper Present a new user similarity model to improve the
recommendation performance to calculate the similarity of each user. The model not only consider
the local context information of user rating but also the global preferences of user behavior.
Index Terms–PCC, Jaccard, MSD, cold–start, Proximity, Sigmoid
I. INTRODUCTION
The Internet, with hundreds of millions of pages worldwide, has become the greatest source of
information that has ever existed. In

Spearman's Rank Correlation Essay
Spearman's Rank Correlation Coefficient Review Spearman's rank correlation coefficient is a
mathematic and statistics tool used to measure correlation or in other words, there is a number that
reveals how closely related, two sets of different data can be associated and how closely related they
are. This can only be used with information that can be put in rank order from highest to lowest. The
Spearman's rank correlation coefficient is also used to determine whether the two variables are
associated or related in any monotonic way, in which a variable will increase and the other variable
will also increase or it will decrease. As a result of this, the measurement will be converted to ranks
therefore researchers will use the Spearman's rank ... Show more content on Helpwriting.net ...
As part of this research Messina et al. used the Spearman rank correlation coefficient to help
determine any relationship between the mean score of patient satisfaction (independent variable) and
the admissions volume (dependent variable).The patients were given surveys/questionnaires to be
filled out which they graded on a ranking scale of their own satisfaction on the hospital type they
received their treatment. The results of this research using the Spearman rank correlation coefficient,
has shown that there is a significant but negative correlation between the variables in the combined
sample between admissions and patient satisfaction. The research performed by Messina et al.
(2009), definitely answers the research question if there is any relationship between patient
satisfaction and inpatient admissions across teaching and nonteaching hospitals. When one looks at
the Spearman's rank correlation coefficient results by itself you will see that there is statistically a
significant and positive correlation between the patient satisfaction and the admission volumes in
teaching hospitals (Messina et al.,

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