...using the same method with the main paper, we got the four similar tables there. Firstly, we got monthly returns of 200 stocks in ASX from data stream, and used them to calculated standard deviations. Moreover, the table 1 was made out below (in order to maintain a neat, all the data we retain all four decimal places.) In the first table, when we made eight stocks as a portfolio, the rate of portfolio standard deviation to standard deviation of a single stock has been nearly 50%. We also found that the ratio will be constant at 0.2217 if we make more than 100 stocks as a diversified portfolio. These two main points are similar to the main article, but the difference is only the data. Elton and Gruber found that 10 stocks portfolio got the rate of near 50%, and the rate would be constant at 0.39 when they made a 200 stocks portfolio. The main reason we thought is that the different between the two markets’ size. In addition, we used the two functions as the original paper to get the result of figure 1. Certainly, the SML we made as the similar condition, we also used ten randomly selected stocks as a portfolio G (10), and the diversified portfolio of ten stocks as P (10). The line should be 200-stock line. We got the result the risk premium became to 6.4%, and the standard deviation of P (200) and G (10) were 2.96% and 14.61% respectively. We got a big difference between these two standard deviations, contrast with the main research. Therefore, the expected return of P...
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...team member’s descriptive statistics for week four incorporating the best elements into one team data analysis paper, including data and charts. Descriptive Statistics The research topic for this paper is “McDonald’s is Closing Hundreds of Stores.” As part of the research a sample size of 400 was selected to ensure accuracy of results based on the population size of 410. The given sample size was randomly surveyed to test the variables – Independent Variable - Change in consumer food preference and competitive market place and Dependent Variable – Reduced sales hence reduced profit. Age Three Hundred and Eighty-Five McDonald’s consumers were randomly selected and their ages measured. The age ranges were 15 and 65 years. Average consumer is aged 31 with a standard deviation of 14 years. Approximately half or more of their ages are above 31. Income The income of the randomly surveyed consumers is averaged at $30.82 and with a standard deviation of $14.04. Income range is $15 to $65 and there is enough evidence that half or more of these consumers averages $30.82 per year. Strengths and Weaknesses of Team Members’ Individual Assignments Efforts were made by each team member to better understand the use of the statistical tool made available to us (MegaStat). More knowledge was gained and applied in the interpretation of data and findings on this paper. Additionally, each team member pulled their weight in the interpretation and findings in the completion of...
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...Market Research On Fashion & Sustainability Submitted by Ishita Bhatia Under the supervision of Jagriti Mishra Submitted to Department of Fashion Management Studies (FMS) National Institute of Fashion Technology (NIFT) (Ministry of Textiles, Govt. of India) GH-0 Road, Behind Infocity Gandhinagar 382007. Gujarat http://www.nift.ac.in December, 2013 Fashion & Sustainability BackGround Myth: Sustainable Fashion is just wearing natural, organic or green fashion. Truth: Sustainable Fashion is about being * Eco friendly * Socially-Responsible * Commercially feasible * Animal-Cruelty Free Sustainability and responsibility are two sides of one and the same coin. Today Apparel Industry stands as a big medium of innovation and smart up cycling. Sustainability becomes more crucial if one has to deal with it in the apparel sector in order to manage excess and wastage. This systematic research aims to find out about all the sustainable measures practiced by companies producing such articles. Acknowledgement I would generously like to thank my Mentor Jagriti Mishra for her continual support, feedback and constructive discussions. I owe my secondary research to Ebsco, DELNET Google Scholar, Nift Resource Center and Library and the whole FMS department of NIFT, Gandhinagar. table of contents Background study 3 acknowledgement 4 table of contents 5 1 INTRODUCTION 7 1.1 Statement of the problem 8 1.2 Objectives 8 ...
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...American InterContinental University Abstract In this paper for the Unit 1 IP it will talk about a study for American Intellectual Union (AIU). In this paper it will talk about the examined data and the results. Also the paper talks about qualitative data and quantitative data. Introduction The Unit 1 Individual project states a scenario. This scenario is that American Intellectual Union (AIU) has assembled a team of researchers in the United States and around the world to study job satisfaction. Also with the scenario we are to write about the study and the findings from the data of the research. The results will allow managers all over to be able to have job satisfaction within the companies no matter what size. Chosen Variables The first variable that was chosen to analyze is Gender for the qualitative variable. This is so because it would give a better view on why someone does or does not have job satisfaction and if it is because of the gender of the individual. “Qualitative variable is when observations cannot be described meaningfully in terms of numbers.” (Qualitative variable and quantitative variable, 2000) For quantitative variable Intrinsic was chosen. “A quantitative variable is observations that can be characterized in numerical terms.” (Qualitative variable and quantitative variable, 2000) Difference in variable types There is a difference between qualitative and quantitative variables. Qualitative data is data that you are not able to...
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... Psych 125 Academic Procrastination and Academic Achievement Nowadays, procrastination has been a common phenomenon happening in our daily lives. This practice can be observe almost everywhere, in our home, at work, in different fields and especially at school. In this fast-paced era where everything seems to be moving quite rapidly. Some people find it difficult to manage their tasks and so they tend to result to procrastination. This practice can be observe most commonly in schools or universities especially on college students where the student needs to manage their time between tasks. Like studying for multiple tests, completing their assignments, reviewing for future quizzes, completing their term papers and projects and doing extracurricular activities which will determine their academic achievement or academic performance. Yet, students still engage themselves in delaying their tasks. This widespread phenomenon is also known as procrastination. Academic Procrastination According to Solomon and Rothlum (1984) The term procrastination is defined as the act of needlessly delaying tasks to the point of experiencing subjective discomfort or putting off that which is necessary to reach some goal. Furthermore, Popoola (2005) stated that procrastination has an internal and external negative effect. The internal negative effects of procrastination includes tension, regret and self-blame. While external negative effects of procrastination include...
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...Standard Deviation Abstract Paper Miguel Ramos, Waleska Molina, Pollyana Cotto, Jessica Casiano, QRB 501 Quantitative Reasoning for Business University Of Phoenix October 30, 2013 Prof. Angel Melendez-Melendez Standard Deviation Abstract Paper The purpose of this paper is to write a basic abstract for each article selected by the member of the learning team and establish for each article the purpose of the study, the research question(s), the hypothesis of the study, and the main findings of the study. The articles selected by each members of the learning team were: Explaining satisfaction in double deviation scenarios: the effects of anger and distributive justice (Jessica); Consumer Socialization in a Wired World: The Effects of Internet Use and Parental Communication on the Development of Skepticism to Advertising (Waleska); Real Estate in the Real World: Dealing with Non-Normality and Risk in an Asset Allocation Model (Pollyanna); and Social network productivity in the use of SNS. (Miguel). In the student (Jessica) article is an article in where the research has shown that more than half of attempted recovery efforts only reinforce dissatisfaction, producing a double deviation effect. Surprisingly, these double deviation effects have received little attention in service marketing literature. To fill this gap, this article aims to develop and empirically test a model of how customers form satisfaction judgments in double deviation scenarios. The article seeks...
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...Journal of Education and Practice ISSN 2222-1735 (Paper) ISSN 2222-288X (Online) Vol 3, No 1, 2012 www.iiste.org The Effectiveness of Co-curricular Activities on Academic Achievements of Secondary School Students in District Abbottabad Pakistan - A Case Study Zahid Bashir, Shafqat Hussain NUMLs Islamabad Pakistan Abstract This research was conducted to examine the effect of co-curricular activities on academic achievements of secondary school students in District Abbottabad. The research is experimental in nature, pre-test Post–test equivalent group design was selected for this purpose. In this study, an achievement test covering four chapters of mathematics and four lessons of English was used as measuring instrument. Depending upon pre-test scores, 200 students of 10th class were divided into two equal groups (n=100) named as experimental group and control group. The experimental group was involved in co-curricular activities and the control group did not participate in any activity beyond the classroom. There were two types of co-curricular activities. First physical i.e., games, athletics and P.T (physical training) etc and the other was debates, drama speeches etc. The experimental group carried out activities for forty minutes daily for twelve weeks. The post-test was administered after twelve weeks. The pre-test and post-test scores of the experimental and control groups served as data for this study. The analysis of data revealed that on the whole...
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...University of Phoenix Material Time to Practice – Week Two Complete Parts A, B, and C below. Part A 1. Why is a z score a standard score? Why can standard scores be used to compare scores from different distributions? It is a scores relationship to the mean indicating whether it is above or below the mean. It does this by converting scores to z score. Yes – keep going – just a bit more is needed.2 out of 3 pts 2. For the following set of scores, fill in the cells. The mean is 74.13 and the standard deviation is 9.98. |Raw score |Z score | |68.0 |-.6142 | |?58.16 yes! |–1.6 | |82.0 |.789 | |92.09 |1.8 | |69.0 |-.514 | |69.14 |–0.5 | |85.0 |1.089 | |91.096 |1.7 | |72.0 |-.213 no | Calculations? Always include either calculations or SPSS output. 2 out of 3 pts 3. Questions 3a through 3d are based on a distribution of scores with [pic] and the standard deviation = 6.38. Draw a small picture to help you see what is required. a. What is the probability of a score falling between a raw score of 70 and 80? .5668ok b. What is the probability of a score falling above a raw score of 80? .2166ok c. What is the probability of a score falling between a raw score of 81 and 83? .0686 close d. What is the probability of a score falling below a raw score...
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... Those shown a photo of an athlete in their sports uniform were not also shown the photo of that same athlete in their everyday clothing, and those shown a photo of an athlete in their everyday clothing were not also shown the photo of that same athlete in their sports uniform. A hypothesis test performed on the resulting averages of the surveys handed out to participants showed no significant results. According to our findings, the fact that someone is an athlete has no effect how how attractive they are found by those around them. Page 2 Much research has been done on the topic of attractiveness and qualities that make people attractive. Attractiveness is a very broad topic that is hard to pinpoint because what is deemed “attractive” differs greatly from person to person and there is no set guidelines to follow that tell specifically what is attractive and what is not. The general topic of attractiveness allowed for many different more specific topics of research pertaining to attractiveness that could be linked or similar to our...
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...Week 3 E-Text Chauntilena Goodwin RES/342 May 1, 2012 Olivia Scott Week 3 E-Text 10.30 In Dallas, some fire trucks were painted yellow (instead of red) to heighten their visibility. During a test period, the fleet of red fire trucks made 153,348 runs and had 20 accidents, while the fleet of yellow fire trucks made 135,035 runs and had 4 accidents. At α = .01, did the yellow fire trucks have a significantly lower accident rate? (a) State the hypotheses. H0: p1 ≥ p2 H1: p1 < p2 (b) State the decision rule and sketch it. Reject the null hypothesis if the critical value is less than z.010= -2.326 and the p-value is greater than .01. (c) Find the sample proportions and z test statistic. P1 = 4135,035 = .00002962 p2 = 20153,348 = .00013042 P = x1+ x2n1+ n2 = 4+20135,035+153,348 = .00008322 z.010 = P1-P2p1-P[1n1+1n2] = .00002962-.00013042.000083221-.0000832[1135,035+1153,348] = -2.9610 (d) Make a decision. Since the z.010 < -2.326 the decision is to reject the null hypothesis (e) Find the p-value and interpret it. P (z<-2.9610) = .0015. The probabilities of a z-score lower than -2.9610 is only .0015. (f ) If statistically significant, do you think the difference is large enough to be important? If so, to whom, and why? The difference of statistical significant is important so that the fire department can have information that can lower cost and make operation safer. (g) Is the normality assumption fulfilled? Explain. The sample size is large...
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...Data Collection and Calculation: Real Estate Data QNT/351 Real Estate: Home Price and Size Analysis The purpose of this paper is to perform a descriptive statistics analysis on the real estate dataset. The analysis will be aimed at investigating relationships between the price of a home and the home’s square footage. The team will use the dataset to figure out if there is a direct relationship between price and square footage, the assumption being there is a positive correlation between home size and price. Research Questions Purchasing a home is the largest financial decision made by most American families. The traditional view has been that people should first buy a small “starter home,” build equity for a few years, and then move into a bigger home. The logic behind this is that smaller homes are relatively cheaper than larger homes, i.e. that there is a direct positive correlation between the price of a house and its square footage. This brings up the following research questions: • What are some of the descriptive statistics for home prices and home sizes? • Is there a relationship between the price of a home and its size? These research questions will be answered through an analysis of the descriptive statistics of two of the variables in the real estate dataset, specifically Price (in dollars) and Size (in square feet.) These two variables are both quantitative, with a ratio level of measurement. Descriptive Statistics The following table summarizes...
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...University of Frankfurt am Main Bachelor Seminar Business Cycle: Theory and Empirical Applications Country of interest: Netherlands Teacher: Prof. Ctirad Slavik Summer Semester 2013 Yisong Dong Student ID: 3903447 June 17.2013 Contents 1. Introduction……………………………………………………………………3 2. Data Work………………………...…………………………………………...3 2.1 2.2 2.3 2.4 2.5 Data……………………………………………………………………3 Detrending the data with Hodrick-Prescott Filter………………..……4 Basic Statistics for the detrended data………………………………...7 Construct the Solow residual without labor……………………...…..11 Construct the Solow residual with labor…………….………………12 3. Calibrating and simulating a simple stochastic RBC model…………………13 3.1 3.2 Two procedure for calibrating θ and calculating the I/K, K/Y and I/Y ratios……….…………………………………………………………13 Stimulation…………………………………………………………...16 4. Conclusion……………………………………………….………………...…21 References………………………………………………………………………..22 2 1. Introduction Business cycle refers to economy-wide fluctuations in production, trade and economic activity in general over several months or years in an economy organized on freeenterprise principles.1 It has been a well-documented feature of economic life for two centuries or more. Business cycle is the upward and downward movements of levels of GDP2 and refers to the period of expansions and contractions in the level of economic activities (business fluctuations) around its long-term growth trend.3 These fluctuations occur around...
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...median we take the middle of those numbers which is 17 Group C: Median= the fifth and sixth numbers are 38 and 39 to find the median we take the middle of those numbers which is 38.5 Group D: Median= the fifth and sixth numbers are 86 and 86 to find the median we take the middle of those numbers which is 86. 4. Standard Deviation Group A: (26-39.5)^2= 182.25 (38-39.5)^2= 2.25 (19-39.5)^2= 420.25 (51-39.5)^2= 132.25 (58-39.5)^2= 342.25 (19-39.5) ^2= 420.25 (61-39.5)^2= 462.25 (34-39.5)^2= 30.25 (68-39.5)^2= 812.25 (21-39.5)^2= 342.25 Total= 3146.25 Standard deviation equals √3146.25/10-1= √349.61) = 18.70 Standard Deviation Group B: (24-16.8)^2= 51.84 (18-16.8)^2= 1.44 (11-16.8)^2= 33.64 (16-16.8)^2= 0.64 (22-16.8)^2= 27.04 (8-16.8) ^2= 77.44 (10-16.8)^2= 46.24 (22-16.8)^2= 27.04 (21-16.8)^2= 17.64 (16-16.8)^2= 0.64 Total= 283.6 Standard deviation equals √283.6/10-1= √31.51 = 5.61 Standard Deviation Group C: (37-38.3)^2= 1.69 (44-38.3)^2= 32.49 (33-38.3)^2= 28.09 (44-38.3)^2= 32.49 (34-38.3)^2= 18.49 (39-38.3) ^2= 0.49 (38-38.3)^2= 0.09 (42-38.3)^2= 13.69 (41-38.3)^2= 7.29 (31-38.3)^2= 53.29 Total= 188.1 Standard deviation equals √188.1/10-1=...
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...Sample Hypothesis Testing Paper RES/342 Two-Sample Hypothesis Research Question A company decides to purchase homes to rent out to their employees. They have to decide if purchasing homes in a rural area is cheaper than purchasing homes from the inner city. 15 miles from the center of the city is inner city and anything passed 15 miles is rural area. The mean house pricing in the urban area is $232,736 out of a sample size of 59 with a standard deviation of $48,651. The mean house pricing in the rural area is $206,183 out of a sample size of 46 with a standard deviation of $40,896. At the 0.05 significance level, the company assumes that urban area is higher than rural area. Formulating a Verbal and Numeric Hypothesis To formulate a verbal and numerical hypothesis statement one must determine which type of two-sample statistic test the problem describes. The statement indicates that one would perform a right-tailed test. The words “is higher than” indicates that the alternate hypothesis will have the greater than sign in it. The statement also indicates that the standard deviation is known. Using this knowledge one may begin to formulate a verbal hypothesis. The researchers will test the hypothesis statement and try to find sufficient evidence to support the null hypothesis. If the evidence is insufficient one will reject the null hypothesis. If the evidence is sufficient one may fail to reject the null hypothesis. Simply put one is trying to figure out if the company...
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...ERRUPTIONS OF THE OLD FAITHFUL GEYSER 1.0 Literature Review A geyser refers to a hot spring that occasionally due geographical processes and difference in pressure erupts hot water and steam in the air. The Old Faithful Geyser at Yellowstone National Park , Wyoming is one of the most famous geyser in the world. Given the fame of this geyser, it receives visitors from various parts of the world. For convenience of time, the national park service have erected some sign at the site to try help visitors predict the time for the occurrence of the next eruption. The Old Faithful Geyser is not the biggest or most regular geyser in Yellowstone but it is the biggest regular geyser. It has been erupting in the same fashion throughout the recorded history. In fact becoming oneof the most the moststudied geyser in the history. In trying to predict the next eruption time, researchers make use of the duration of the current eruption. The duration is timed from the first heavy surge which lifts water skywards at the start of the eruption until the last small splash above the cone at the end. Previous studies show that, a 2 minute eruption results in an interval of about 55 minutes. There have existed various misconceptions with respect to this geyser; the first being that Old Faithful plays hourly, this misconception came about during the 1870, Washburn expedition where one of the members reported that that the geyser played hourly and so each day there are usually about 21 to 23...
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