...-The Power of Ignorance- An argument on whether we should build the third runway Aviation industry, for the sake of urban development, undoubtedly holds the key of prosperity. Hong Kong International Airport is an irreplaceable facility contributing a potential net worth of more than HK$80 billion dollars a year with its working capacity to serve 50.9 million passengers with 4.1 million tons of cargo per day according to the Airport authority financial report (2012, p.4), has gained a well-known reputation over the globe. The expansion of the Airport is recently proposed as a must because of the ever-increasing popularity and frequent flows of passengers. However, such a large-scale construction is never a simple calculation with simply subtracting construction costs from the projected revenues. We should take environmental and social costs into account. There is indeed another ideal solution, which costs us less in sacrificing various aspects- the cooperation with Macau government. To open up another runway or cooperate with our long-lasting partner is the critical issue that I am going to discuss respective pros and cons attached. With strong emphasis on the correlation between the expansion of the Airport and Hong Kong economic development by the supporters, it appears that constructing the third runway has no ground to object. The lecture held by Mr. Howard Eng Kiu-chor, the Executive Director of the Airport Operation further convinced Hong Kong citizens to vote for...
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...and religious site looking for a trust worthy person and I decided to contact you. I am Mrs. Kavita Mazumdar of Auditing and accounting section staff in Royal bank of Scotland Barakhamba road branch New Delhi, during my investigation and auditing I came across many inactive accounts but there is a particular account that has not been noticed by the previous/past auditors the account has been dormant without any claim of the fund. I write to solicit for your support and assistance to carry out this deal in my bank that will benefit us. Lying in one of the many inactive accounts is the sum of 5,508,609.00 INR (Five Crore fifty Lakhs eight thousand Six Hundred and Nine India rupees only) belonging to a foreign customer (Mr.Chowalert Jitjamnong) who was a gas consultant here in India, he happened to be deceased during a vacation trip with his wife (Mrs .Siriphut Jitjamnong) and the only child (Chawit Jitjamnong) on board One-Two-Go Orient-Thai Airlines flight OG269 Phuket Airport plane crash of Monday, 17th September 2007 from Bangkok to Phuket. Info of this crash was on the news which we have tried to notify his relatives but to no avail, see link below for more detailed information: http://www.korat-info.com/forum/viewtopic.php?f=18 & t=1496#p6452 Unfortunately, he has no family member in India or Over-sea who are aware of the existence of the funds,...
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...status. Some variables could be considered both categorical and continuous variables. One example of this type of variable is a person's rating of someone else's attractiveness on a 4 point scale. Categorical Variables Categorical variables represent types of data which may be divided into groups. Examples of categorical variables are race, sex, age group, and educational level. While the latter two variables may also be considered in a numerical manner by using exact values for age and highest grade completed, it is often more informative to categorize such variables into a relatively small number of groups. Analysis of categorical data generally involves the use of data tables. A two samples or measures presents categorical data by counting the number of observations that fall into each group for two variables, one divided into rows and the other divided into columns. For example, a survey to identify their hair and eye color. Continuous Variables Much of the statistical analysis in medical research involves the analysis of continuous variables such as cardiac output, blood pressure, and heart rate which can assume an infinite range of values. As with discrete variables, the statistical analysis of continuous variables requires the application of specialized tests. These tests compare the means of two or more data sets to determine whether the data sets differ significantly from one another. There are four...
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...BUS 310 Notes regarding Two-Sample t-Tests and ANOVAs In Chapter 9, we learned how to conduct a t test of a hypothesis when we were testing the mean of a single sample group against some pre-determined value (i.e., the 21.6 gallons of milk consumption as the national average). This week, in Chapter 10, we will see how to test hypotheses that involve more than one sample group—such as testing to see if males are significantly taller than females. If we have two groups, then the technique that we will use will still be a t test. If we have more than two groups, then we will have to use a different test called Analysis of Variance (ANOVA, for short). The good news is that the decision rules for hypothesis testing that we learned last week are still exactly the same: Set #1: If the absolute value (ignore any negative sign) of the test statistic is greater than or equal to the critical value, then you reject the null. If the absolute value of the test statistic is less than the critical value, you do not reject the null. Set #2: If the p value is less than or equal to α, reject the null. If the p value is greater than α, do not reject the null. (Remember that we must either reject or not reject the null—we never accept the null.) In order to conduct these tests, we will need to use the data analysis feature of Excel, which probably is not installed for you, but that’s OK, because it’s available and pretty simple to install—just follow these steps: ...
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...Which statement is NOT true concerning the t distribution? Select one: a. Compared to the normal distribution, the t distribution has more area in the tails and less in the center. b. As the number of degrees of freedom increases, the t distribution approaches the normal distribution. Incorrect c. The t 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...
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...Hypothesis Testing: One Population Hypothesis testing is used to make decisions about a population based on the analysis of sample statistics. There are always two hypothesis statements which are mutually exclusive and complementary statements concerning the value of the population parameter of interest: Null Hypothesis (H0): An assumption regarding a population parameter of interest. This hypothesis always includes the equal sign as the null hypothesis is assumed to be true unless sample data produces evidence to the contrary. Alternative Hypothesis (H1): The alternative option available when the null hypothesis is rejected. Three Types of Hypothesis Tests: Lower-Tail Test Upper-Tail Test Two-Tailed Test H0: ( ( (0 H0: ( ( (0 H0: ( = (0 H1: ( < (0 H1: ( > (0 H1: ( ( (0 Two-Sided Tests: A Two-Tailed Test (TTT) is designed to detect a change in the population parameter of interest from some hypothesized value to some different value. One-Sided Tests: A Lower-Tail Test (LTT) is designed to detect a change in the population parameter of interest from some hypothesized value to some lower value. An Upper-Tail Test (UTT) is designed to detect a change in the population parameter of interest from some hypothesized value to some greater value. Test Statistics and Action Limits: A test statistic is a sample statistic corresponding to the population parameter being tested. For example, when testing a hypothesis...
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...i TEST IQ boost your brainpower 2nd edition YOUR 400 questions to Philip Carter London and Philadelphia ii Whilst the author has made every effort to ensure that the content of this book is accurate, please note that occasional errors can occur in books of this kind. If you suspect that an error has been made in any of the tests included in this book, please inform the publishers at the address printed below so that it can be corrected at the next reprint. Publisher’s note Every possible effort has been made to ensure that the information contained in this book is accurate at the time of going to press, and the publishers and author cannot accept responsibility for any errors or omissions, however caused. No responsibility for loss or damage occasioned to any person acting, or refraining from action, as a result of the material in this publication can be accepted by the editor, the publisher or the author. First published in Great Britain and the United States in 2000 by Kogan Page Limited Reprinted 2001, 2004 Reissued 2007 Reprinted 2007 Second edition 2009 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licences issued...
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...ASSIGNMENT 2 Does standardized testing relate to giving motivational instructions for elementary students in a public school system? The purpose of this study is to test whether motivational instructions improve performance on standardized tests with students in two different schools in the Chicago Public Schools System. Figuring out whether doing simple things such as changing the way the test is presented to positively impact the way the students take the test and their resulting scores ways heavily on those who give these standardized tests. An e-mail will be sent around to all elementary school principals and fourth grade teachers in the Public Schools System in Chicago. This e-mail will discuss the concern of high standardized test scores in all schools across the United States. It will also ask these principals and teachers if they will be willing to participate in a simple study that will give educators more insight as to whether the way a teacher presents the instructions of their tests has an impact on the scores of these students. Of the schools that send back an e-mail stating that they are interested in the study, five to ten schools will be chosen. These schools will be chosen according to the number of students in the fourth grade, male to female ratio, their average test scores, socioeconomic status, and representation of the population. The schools with the most similar of these variables will be chosen to participate in this study. These students...
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...|Statistics | Copyright © 2010, 2006 by University of Phoenix. All rights reserved. Course Description This course surveys descriptive and inferential statistics with an emphasis on practical applications of statistical analysis. The principles of collecting, analyzing, and interpreting data are covered. It examines the role of statistical analysis, statistical terminology, the appropriate use of statistical techniques and interpretation of statistical findings through applications and functions of statistical methods. Policies Faculty and students/learners will be held responsible for understanding and adhering to all policies contained within the following two documents: • University policies: You must be logged into the student website to view this document. • Instructor policies: This document is posted in the Course Materials forum. University policies are subject to change. Be sure to read the policies at the beginning of each class. Policies may be slightly different depending on the modality in which you attend class. If you have recently changed modalities, read the policies governing your current class modality. Course Materials Triola, M. F. (2010). Elementary statistics. (11th ed.). Boston, MA: Pearson. All electronic materials are available...
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...between descriptive statistics and Inferential statistics and the reasons why we use them. I will also discuss hypothesis development and testing, when to select the appropriate statistical test, and how to evaluating statistical results. In this class I learned the difference between descriptive statistics and inferential statistics. We use descriptive statistics to measure and analysis data. There are a number of reasons why we use Descriptive statistics. We use it, because Descriptive statistics numerical summaries measure the central tendency of a data set, it can include graphical summaries that show the spread of the data, and they provide simple summaries about the sample that help interpret and analyze data. First, there are a number of reasons why we use descriptive statistics we use it because descriptive statistics numerical summaries that either measure the central tendency of a data set. In business therefore descriptive statistics helps in making conclusions about various issues and therefore helps in making decision. Description statistics is the first step in analyzing data before making inferences of data, therefore it is important in analyzing any data collected that will help in describing the characteristics of data collected. There are three measurements that we tend to use. One measurement is the mean. The mean is often referred to as the average. The average is found by adding all the data and then multiplying by the total number of data value. We also measure...
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...Bahria University Bahria Institute of Management & Computer Sciences Karachi Campus Course Title: Statistical Inference Course Code: QTM 220 Credit Hours: Three Semester: 3rd Semester Prerequisite: QTM 160 Aims and Objectives: This main objective of this course is to provide wide application f the statistical tools in business management. It is also aims at to impart in-depth and rigorous knowledge to the business students to inculcate academic excellence in various fields of research and development, with special reference to business management. In addition it will provide necessary statistical knowledge and wide rage of ways to analyze data, which will improve the students statistical analytical and decision making skills. Session Lecture Outline Learning Objectives 01 Basic Probability and Discrete Probability Distributions Simple Probability To develop an understanding of basic probability concepts To introduce conditional probability To use Bayes’ Theorem to revise probabilities in light of new information To provide an understanding of the basic concepts of discrete probability distributions and their characteristics To develop the concept of mathematical expectation for a discrete random variable To introduce the covariance and illustrate its application in finance To present applications of the binomial distribution in business To present applications of the Poisson distribution in business 02 Counting Techniques 03 Continued...
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...Hypothesis Test for a Proportion This lesson explains how to conduct a hypothesis test of a proportion, when the following conditions are met: * The sampling method is simple random sampling. * Each sample point can result in just two possible outcomes. We call one of these outcomes a success and the other, a failure. * The sample includes at least 10 successes and 10 failures. (Some texts say that 5 successes and 5 failures are enough.) * The population size is at least 10 times as big as the sample size. This approach consists of four steps: (1) state the hypotheses, (2) formulate an analysis plan, (3) analyze sample data, and (4) interpret results. State the Hypotheses Every hypothesis test requires the analyst to state a null hypothesis and an alternative hypothesis. The hypotheses are stated in such a way that they are mutually exclusive. That is, if one is true, the other must be false; and vice versa. Formulate an Analysis Plan The analysis plan describes how to use sample data to accept or reject the null hypothesis. It should specify the following elements. * Significance level. Often, researchers choose significance levels equal to 0.01, 0.05, or 0.10; but any value between 0 and 1 can be used. * Test method. Use the one-sample z-test to determine whether the hypothesized population proportion differs significantly from the observed sample proportion. Analyze Sample Data Using sample data, find the test statistic and its associated P-Value...
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...NOMOR 1 Buatlah ringkasan statistik deskriptif (max, min, rata-rata, median, deviasi standar, kuartil) dari variabel III, IV dan V. Anda akan lihat output komputer di Windows Session. TUJUAN Untuk melihat persebaran nilai tertinggi, rata-rata, nilai tengah standar deviasi dan nilai di setiap quartil di dalam ‘Y_total”/ pendapatan total di seluaruh kecamatan yang ada. Teori Pendugaan Parameter Untuk mengetahui mengetahui hasil dari seluruh nilai yang meliputi nilai variable Y_total : Pendapatan total dari setiap kecamatan N : jumlah populasi yang di analisa Mean : rata rata pendapatan dari seluruh kecamatan yang ada SE mean : StDev : besarnya nilai penyimpangan yang mungkin terjadi di nilai rata rata populasi yang ada Minimum : pendapatan terkecil dari seluruh kecamatan Q1 : Median : nilai tengah dari data populasi yang ada Q3 : Maximum : pendapatan terkecil dari seluruh kecamatan HASIL DATA MINITAB Variabel Kategorik Variabek Kuantitatif Kelompok I II III IV V 3 Monitoring Evaluasi Y_Total ExpEduc ExpHealth Descriptive Statistics: Y_Total Variable N N* Mean SE Mean StDev Minimum Q1 Median Y_Total 151 0 22765636 2170459 26671048 200000 7200000 13200000 Variable Q3 Maximum Y_Total 30000000 180000000 Untuk Pendapatan Total Rata-rata pendapatan total di pedesaan adalah IDR 22,765,636,-, dengan ukuran yang menggambarkan tingkat penyebaran data dari nilai rata-rata...
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...Statistics 5 Hypothesis of the test 5 Statistical Findings 6 Interpretation of results 6 3.2 Question 2: Satisfaction level between gender 7 Descriptive statistics 7 Hypothesis 7 Method used and nature of the test 7 Reporting of statistical analysis 8 Interpretation of results 8 3.3 Question 3: Difference between satisfaction levels across business divisions. 9 Descriptive Statistics 9 Hypothesis 9 Method used and the nature of the test 9 Reporting of Results 9 Interpretation of results 10 3.4 Question 4: Gender composition across divisions 11 Descriptive Statistics 11 Hypothesis 11 Method used 11 Reporting of Statistical analysis 11 Interpretation of results 12 3.5 Question 5: Years of service and overall satisfaction level 12 Null and alternate hypothesis 12 Method used 12 Nature of test used: 13 Reporting of Results 13 3.6 Question 6: Employment basis and their perception of their values. 14 Descriptive Statistics 14 Hypothesis 14 Method used and the nature of the test 14 Reporting of Results 15 Interpretation of results 15 3.7 Question 7: Difference between values employees placed on income and training opportunities 16 Descriptive statistics 16 Hypothesis 16 Method used and nature of the test 16 Reporting of statistical analysis 17 Interpretation of results 17 3.8 Question 8: Value on work social events and numbers of hours 18 Descriptive statistics 18 Hypothesis 18 Method used and nature of the test 18 Reporting of statistical analysis...
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...Practice Exam Chapter 10- TWO-SAMPLE TESTS SECTION I: MULTIPLE-CHOICE 1. The t test for the difference between the means of 2 independent populations assumes that the respective a. sample sizes are equal. b. sample variances are equal. c. populations are approximately normal. d. All of the above. 2. If we are testing for the difference between the means of 2 related populations with samples of n1 = 20 and n2 = 20, the number of degrees of freedom is equal to a. 39. b. 38. c. 19. d. 18. 3. In testing for differences between the means of two related populations, the null hypothesis is [pic] 4. In testing for differences between the means of two independent populations, the null hypothesis is: [pic] [pic] a. 0.0166. b. 0.0332. c. 0.9668. d. 0.9834. 6. If we wish to determine whether there is evidence that the proportion of items of interest is higher in group 1 than in group 2, the appropriate test to use is a) the Z test for the difference between two proportions. b) the F test for the difference between two variances. c) the pooled-variance t test for the difference between two proportions. d) the F test for the difference between two proportions. SECTION II: TRUE OR FALSE 1. The sample size in each independent sample must be the same if we are to test for differences between the means of 2 independent populations. False 2...
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