...Lewis NHL Team Salary Cinco de Mayo 2015 Morrisville State College Professor Boyce Part 1 Data Represented By a Population A population is all the subjects that you want to study. It takes every part of a category that is going to be studied and makes it a known hole. The population for this project would be Forward Cap, Defense Cap, Goaltender Cap, Total Cap, and Cap Space. Data Represented By a Sample A data sample is a set of data collected or selected from a statistical population by a defined procedure. Data Collection Methods (Non-Probability or Probability-based) The difference between Non-Probability and Probability-Based sampling is that Non-Probability uses or involves a random selection where the Probability-Based method does not. This means that Non-Probability samples can’t depend on the rationale of the probability theory. Using a Probability (Based Method) To make sure the sample I collected is Probability-Based, I used a Stratified Random Sampling. In a Stratified Random Sampling, you divide the elements of the population into smaller groups called strata. This will be used in my dataset where I will gather the different team into different strata. Part 2 1. The set of data that I chose for this project includes 30 observations and 6 quantitative variables. The data includes 30 measurements of the NHL team’s salary. The detailed salary per team was measured by Spotrac. The variables in the data set are Forward Salary, Defense Salary, Goaltender...
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...MGSC 372 Fall 2014 Assignment 1 Prof. B. Smith Due Oct 4, QUESTION 1 The Pareto distribution, named after the Italian economist Vilfredo Pareto, is a probability distribution that may be used to describe social, scientific, geophysical, actuarial, and many other types of observable phenomena. Pareto originally used this distribution to describe the allocation of wealth among individuals since it seemed to show rather well the way that a larger portion of the wealth of any society is owned by a smaller percentage of the people in that society. He also used it to describe distribution of income.[8] This idea is sometimes expressed more simply as the Pareto principle or the "80-20 rule" which says that 20% of the population controls 80% of the wealth. This distribution is not limited to describing wealth or income, but to many situations in which an equilibrium is found in the distribution of the "small" to the "large". The following examples, among others, are sometimes seen as approximately Pareto-distributed: * The sizes of human settlements (few cities, many hamlets/villages. * File size distribution of Internet traffic which uses the TCP protocol (many smaller files, few larger ones) * Hard disk drive error rates The Pareto distribution function may be given as follows: fxx0,θ= θx0θx-θ-1 , ...
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...(Corresponding author) Faculty of Business & Accountancy University of Malaya, 50603, Kuala Lumpur, Malaysia E-mail: edwardwong@graduate.uwa.edu.au Dr Teoh Ngee Heng Universiti Tunku Abdul Rahman 46200, Petaling Jaya, Malaysia E-mail: tiohnh@utar.edu.my Abstract This work identifies the factors that measure job satisfaction of faculty members at two selected and major universities in Malaysia, using ten major factors corresponding to job satisfaction using the Herzberg Two-factor Theory to determine how these selected factors are related to job satisfaction of Malaysian faculty members. The conclusions drawn from this study are that the major sources of job satisfaction for Malaysian faculty members are shown to be policy, administration, and salary. The relevant sources of dissatisfaction are personal achievement, personal growth, interpersonal relations, recognition, responsibility, supervision, the work itself, and the overall working conditions. This study has a number of practical implications for institutional administrators, because if the educational institution has no instrument designed to measure faculty perceptions of their jobs and work, these administrators could elect to use the same instrument that investigates the areas of job satisfaction to gain similar results. Keywords: Higher education, Herzberg Two-factor Theory, Job satisfaction, Job dissatisfaction 1. Introduction The relationship between the individual and the factors determining job satisfaction has been extensively...
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...Running head: REGRESSION Regression Names RES/342 - Research and Evaluation II Date Professor Table of contents Executive Summary 3 Dataset 3 Data Observations 3 Statistical Analysis 4 Conclusion 4 Dataset for the 2004 season 5 Regression Analysis taking LOG (Y) 6 Regression Analysis 8 Executive Summary This report is to determine whether total team payroll for major league baseball teams directly varies with each team’s home attendance. This is an important statistical analysis because if we can prove that there is a relationship between salary and attendance then we can see that more fans in the stands will give a team more buying power when it comes to signing players. Dataset The independent variable is team payroll and the dependent variable is team home attendance. Each team plays 81 home games. The dataset consists of 30 Major League Baseball teams from the 2004 season. Data Observations For the independent variable: The arithmetic mean for home attendance is: 30,453.67 The median for total home attendance is: 31,499.50 The standard deviation for total home attendance is: 8,132.28139 The minimum for total home attendance is: 14,052 The maximum for total home attendance is: 50,499 For the dependent variable: The arithmetic mean for total payroll is: $73,052,363.27 The median...
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...S A NOTE ON STATISTICS AND THE LAW w 909E01 Ileana Funez wrote this note under the supervision of Professor Greg Zaric solely to provide material for class discussion. The authors do not intend to provide legal, tax, accounting or other professional advice. Such advice should be obtained from a qualified professional. Ivey Management Services prohibits any form of reproduction, storage or transmittal without its written permission. Reproduction of this material is not covered under authorization by any reproduction rights organization. To order copies or request permission to reproduce materials, contact Ivey Publishing, Ivey Management Services, c/o Richard Ivey School of Business, The University of Western Ontario, London, Ontario, Canada, N6A 3K7; phone (519) 661-3208; fax (519) 661-3882; e-mail cases@ivey.uwo.ca. Copyright © 2009, Ivey Management Services Version: 2009-01-29 INTRODUCTION Along with advancements in science and technology, the practice of law has made advancements in the types of evidence considered to be relevant. Since the 1970s, statistical analysis has become an important part of courtroom discussions.1 Often, statistical evidence alone can provide sufficient grounds for the sentencing of a suspect. An understanding of statistical science is thus crucial for an analysis of many courtroom decisions. In this note, the use of data in court, data collection biases, requirements for evidence, and fallacious arguments will be discussed. There will...
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...Need: avenue for applying learned quantitative (statistical) skills in practical and real-life cases Opportunity: create the first statistical org in Ateneo Ateneo Statistics Circle or A-Stat Build a community of critical decision makers Outside School Orgs INPUT OUTPUT Members, Officers, Funds, Tools & Instruments Research Studies Outputs, Tutorials, Social Events, Charity Work Other AdMU Orgs Government L.S. Community The Ateneo Statistics Circle (A-Stat) was formed in the 10th of March 2005 by eleven B.S. Management Engineering students who saw the need to create an organization where students can apply quantitative methods and skills that they learned in class into solving and/or addressing real-life problems and issues present in their community. Furthermore, the founders saw the need for a Statistics-oriented student organization in the Ateneo which will cater mainly to statistics lovers as well as for those who want to learn about statistics but did not have enough opportunities because of the lack of any Statistics course in the university. Today, A-Stat, which exists vis-à-vis its external environment (e.g. other Ateneo organizations, the government, other outside school organizations, and the LS Community), delivers their outputs (e.g. research studies outputs, statistics tutorials and talks, social events, and charity works) through the work of their members and officers, through the funds that they collect from members and from fund-raising...
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...distributions are skewed to the left. d. The population variance is unknown and is estimated by the sample variance s2. e. As the sample size increases beyond 120, the t and Z distributions are indistinguishable. Feedback The correct answer is: The t distributions are skewed to the left. Question 2 Incorrect Mark 0 out of 1 Not flaggedFlag question Question text Which of the following involves a test of two-independent samples? Select one: a. Test of differences in the percent of men and women who are or are not members of Greek organizations on campus b. Test of the average incomes of magazine subscribers of Southern Living verses Better Homes and Gardens c. Test of whether the mean salary of professors at Metro University is higher than the national average for university professors Incorrect d. Test of whether a change occurred in the likelihood of heart disease among people who switched to a diet high in fish e. Test of differences in ad recall among three experimental groups (each of which saw a different advertisement) and a control group Feedback The correct answer is: Test of the average incomes of magazine subscribers of Southern Living verses Better Homes and Gardens Question 3 Correct Mark 1 out of 1 Not flaggedFlag question Question text Under which of the following conditions must the null hypothesis be rejected? Select one: a. p value < equation Correct b. p value > equation c. p value = equation d. p value cannot be determined e. p value...
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...Applied Business Statistics FINAL Examination 1. The t distribution A) assumes the population is normally distributed. B) approaches the normal distribution as the sample size increases. C) has more area in the tails than does the normal distribution. D) All of the above. 2. Suppose a 95% confidence interval for μ turns out to be (1,000, 2,100). Give a definition of what it means to be "95% confident" in an inference. A) In repeated sampling, the population parameter would fall in the given interval 95% of the time. B) In repeated sampling, 95% of the intervals constructed would contain the population mean. C) 95% of the observations in the entire population fall in the given interval. D) 95% of the observations in the sample fall in the given interval. 3. In the construction of confidence intervals, if all other quantities are unchanged, an increase in the sample size will lead to a wider interval. A) narrower B) wider C) less significant D) biased 4. An economist is interested in studying the incomes of consumers in a particular region. The population standard deviation is known to be $1,000. A random sample of 50 individuals resulted in an average income of $15,000. What is the upper end point in a 99% confidence interval for the average income? A) $15,052 B) $15,141 See worksheet C) $15,330 D) $15,364 5. A prison official wants to estimate the proportion of cases of recidivism....
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...17 March 2015 In 2013, Michigan State University football team went a span of 194 minutes and 33 seconds without allowing a touchdown; Michigan State’s defense has allowed just 3.75 yards per play and 2.10 yards per rushing attempt, both of which rank No.1 in FBS; The Spartans lead the FBS in time of possession (34:56 per game).(SpartyOn.com) In Michigan, from 2009 to 2013 there were 88.9 percent of people age of 25 above have education of high school graduate or higher which is higher than United State average of 86.0 percent, and also have 25.9 percent people have Bachelor’s degree or higher. In addition, Michigan has an average salary of jobs of $58,000. (Census.gov) Where these numbers came from? It is Statistics. “People cannot make research without statistics and analysis.”(Zeleke) Statistics is important and critical, it can solve for society problem. Nowadays, we have a lot of technological advancement, mobile technology and data in our daily life. The world becomes more and more complex. We need people to be proficient to understand all information out there. How do we process? What is important? How do we analyze the information and make the right decision? Now, there are lots of problem that we are facing: human, race, climate change, economics hardships, and political instability etc. For solving these problems, we need statistics and modeling. Statistics become more and more important; it is not only for statistician but also for everyone. Statistics not only help...
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...QNT 275 NEW FINAL EXAM 2016 Click Link Below To Buy: http://hwaid.com/shop/qnt-275-new-final-exam-2016/ What is the name of the variable that's used to predict another variable? Explanatory Standard error of the estimate Response Coefficient of determination Professors at a local university earn an average salary of $80,000 with a standard deviation of $6,000. The salary distribution is approximately bell-shaped. What can be said about the percentage of salaries that are at least $74,000? About 97.5 percent About 84 percent About 68 percent About 95 percent What type of relationship is indicated in the scatterplot? A positive linear or curvilinear relationship No relationship A negative curvilinear relationship A negative linear relationship The study of statistics can be defined as: the art and science of getting information from data. All of the answers the language of data. the study of collecting, analyzing, presenting, and interpreting data. In the accompanying stem-and-leaf diagram, the values in the stem and leaf portions represent 10s and 1s digits, respectively. The stem-and-leaf diagram shows that the distribution is ___________. symmetric positively skewed negatively skewed None of the answers Which of the following is most influenced by outliers? Median Mode 75th percentile Mean serial correlation is typically observed in: sparse data outliers cross-sectional data time series data n the sample regression equation...
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...------------------------------------------------- RES/351 Final Examination Study Guide This study guide will prepare you for the Final Examination you will complete in Week 5. It contains practice questions, which are related to each week’s objectives. In addition, refer to each week’s readings and your student guide as study references for the Final Examination. ------------------------------------------------- Week One: Recognizing the Situation Objective: Recognize a situation, problem, issue, or opportunity that needs addressing. 1. Consider the following example: "Retail sales increases in the 2005 holiday season were below projections. Sales were disappointing because consumers were not confident about economic growth." This is an example of _____. a. an inductive argument b. a deductive argument c. an empirical argument d. a factual argument 2. The acronym, RFP, stands for _____ and refers to the document used to invite research firms to propose ideas for addressing the research needs of the organization. a. request for proposal b. recency frequency population c. research firm proposal d. recognition of problem Objective: Determine the significance, scope, magnitude and feasibility of finding a solution to the situation, problem, issue, or opportunity. 3. Consider the following statements: "Inner-city household interviewing is especially difficult and expensive. This survey involves substantial inner-city...
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...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 enrolled in youth education courses at Southwestern Seminary.1 Questionnaires were returned by 318 students and 184 youth ministers.2 Ten objectives in each of five categories (Personal Ministry, Christian Theology and Baptist Doctrine, Christian Ethics, Baptist Heritage, and Church Polity and Organization) were ranked by these two groups. The basic question raised by Black in this study was whether students prioritized discipleship training objectives for youth in the same way as full-time ministers in the field. Using the Spearman rho correlation coefficient, Black found the correlations of rankings generated by students and ministers of the ten items for each of five categories were as follows: Personal Ministry, 0.915; Christian Theology...
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...Organizational Loyalty: ABS-CBN DECSCI2 K34 MINI RESEARCH PAPER Dr. Dimaano Gino Tang Joshua Moya Ynna San Juan John Anthony Castelar Acknowledgement The authors would like to thank Dr. Dimaano for providing us the template for this paper and the questionnaires as well; De La Salle University for the facilities for our research and ABS-CBN for providing us with participants. Executive Summary When preparing to write an executive summary, ask yourself the following questions: • Who will read your executive summary? Sometimes your executive summary may have an “intended” audience: your professor might require you to write it for a CEO, department head, or supervisor, for example. On other assignments, your audience won’t have a specific identity, but always keep in mind that the reader of an executive summary needs to know all of the important information in the main document without reading the actual document. Even if you know that your instructor will be reading everything that you submit, write the executive summary as a “stand alone” document. • What is the main document’s main topic, theme, or idea? Most reports have a “thesis” or central point that they are seeking to communicate. Try to sum this up in two or three sentences. If you are having trouble with this, imagine that someone has asked you, “what’s this report about?” and that you have to explain...
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...1. Which type of research includes an array of interpretative techniques which seek to describe, decode, translate, and otherwise come to terms with the meaning of certain phenomena? • Qualitative • Quantitative • Descriptive • Statistical 2. Which term below refers to the descriptors of variables computed from sample data used to estimate those same variables in the population? • Population parameters • Standard errors • Systematic estimates • Sample statistics Find the Latest Final Exam answers here QNT 565 Final Exam (Latest) 3. A population consists of the following data: 7, 11, 12, 18, 20, 22, 25. The population variance is • 36.82 • 22.86 • 5.16 • 6.07 4. If the hypothesis presented is tested using a .05 alpha level and the resulting p value is .01, which of the following interpretations of the results is most appropriate? • As income increases, food expenditures increase. • There is a relationship between income and food expenditures. • As income decreases, the percentage of income spent on food increases. • There is no relationship between income and food expenditures. 5. Paired comparison scales result in _____ data. • ratio • interval • ordinal • nominal To download the Complete Assignment of QNT/565 Class check QNT 565 Entire Course 6. Five homes were recently sold in Oxnard Acres. Four of the homes sold for $400,000 while the fifth home sold for $2.5 million. Which measure of central tendency best represents a typical home...
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...use analytics data because most companies are offering similar products and services. They also must know what the customer want and how much they are willing to pay for that product. Competitors should also know the compensation costs, turnover rates and how to calculate how much personal contribute to or detract from the bottom line and how salary levels relate to individuals’ performance (Davenport 2006). When you define your key industrial competitive pressures can provide a framework for developing strategies for your growth. Analyzing your primary competitor and identifying their strengths, weakness, opportunities and threats (SWOT Analysis) help determine target markets, marketing plan, customer service, sales forecasting and sales planning. Competition in business is not new. Competing on Analytics is rapidly becoming not just a good idea, but vital for more and more companies as the economy squeezed from all sides (Taylor 2007). “Organizations that become more analytical have leaders who fully embrace analytics and lead the company’s culture toward fact-based decision making. According to Tom Davenport, a distinguished professor of Information Technology Management at Babson College in Massachusetts, analytical competitors need to focus on the DELTA model, an acronym for five crucial analytical factors. Data focus on the successful analytics. It requires large volumes of high quality...
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