...Statistics is the study of the collection, organization, analysis, interpretation and presentation of data.[1][2] It deals with all aspects of data, including the planning of data collection in terms of the design of surveys and experiments.[1] The word statistics, when referring to the scientific discipline, is singular, as in "Statistics is an art."[3] This should not be confused with the word statistic, referring to a quantity (such as mean or median) calculated from a set of data,[4] whose plural is statistics ("this statistic seems wrong" or "these statistics are misleading"). Some consider statistics a mathematical body of science that pertains to the collection, analysis, interpretation or explanation, and presentation of data,[5] while others consider it a branch of mathematics[6] concerned with collecting and interpreting data. Because of its empirical roots and its focus on applications, statistics is usually considered a distinct mathematical science rather than a branch of mathematics.[7][8] Much of statistics is non-mathematical: ensuring that data collection is undertaken in a way that produces valid conclusions; coding and archiving data so that information is retained and made useful for international comparisons of official statistics; reporting of results and summarised data (tables and graphs) in ways comprehensible to those who must use them; implementing procedures that ensure the privacy of census information. Statisticians improve data quality by developing...
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...NIGERIA MILLENNIUM DEVELOPMENT GOALS REPORT 2010 © 2010, Government of the Federal Republic of Nigeria TABLE OF CONTENTS Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2 Acronyms and abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 Executive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8 MDGs status at a glance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12 Goal 1 – Eradicate extreme poverty and hunger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13 Goal 2 – Achieve universal primary education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17 Goal 3 – Promote gender equality and empower women . . . . . . . . . . . . . . . . . . . . . . . . . . . .22 Goal 4 – Reduce child mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27 Goal 5 – Improve maternal health . . . . . . . . . . ....
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...Statistics in Business Kathleen S. Power-Davenport QNT/351 May 25, 2015 Lance Milner Statistics in Business Introduction Statistics is "the science of collecting, organizing presenting, analyzing, and interpreting data to assist in making more efficient decisions" (Lind, Marchal & Wathen, 2011). This paper will summarize the types, levels, and the role of statistics in business decision making, followed by examples of statistics in action. Types, Levels, and the Role in Business Decision Making The two categories of statistics are descriptive and inferential. Descriptive statistics is the analysis of data that describes, or summarizes the data in a meaningful way (Laerd Statistics, 2013). Business leaders can organize large amounts of data into a comprehensive format utilizing descriptive statistics. But descriptive statistics do not make conclusions about the data. An inferential statistic is calculated by taking a sample of the data from the population, and drawing a conclusion about the whole based on the small amount (Lind, Marchal & Wathen). Decision makers move forward based on a conclusion drawn from statistical inference. The data gathered for statistics is classified into four levels of measurement: nominal, ordinal, interval and ratio (Lind, Marchal & Wathen). Data at the lowest level is nominal and has a qualitative variable divided into categories or outcomes. Ordinal data is qualitative and represented by sets of labels or names...
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...Topic Proposal Basic Math Skills and Scholastic Performnce among Grade III pupils of Dona Pilar Learning Center Foundation, Inc. Mathematics is the foundation of learners to improve their reasoning and thinking skill. It is widely recognized not only as a core component of the curriculum but also as a critical contributor to many educational and career opportunities (Scriphai, S. & Damongpanit, S.,et al, 2011). In reality, mathematics encompasses a wide variety of skills and concepts. These skills and concept are related each other but there’s a chance that you can easily master to some and still struggles with others, (Nathan V. Lauren, Sarah Lee Adam 2000). Early academic skills appear to be the strongest predictor of subsequent scholastic success – early math skills more so than early reading skills. http://news.uci.edu/features/kids-skilled-early-in-math-do-better-in-school/ In its report on the 2006 PISA results, the OECD outlines the importance of math skills in today’s world: With the growing role of science, mathematics and technology in modern life, the objectives of personal fulfilment, employment and full participation in society increasingly require that all adults, not just those aspiring to a scientific career, should be mathematically, scientifically and technologically literate. The performance of a country’s best students in mathematics and related subjects may have implications for the role that that country will play in tomorrow’s advanced...
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...Question 1: Conceptual Question (a) Model I: The major econometric issue is on the error term ui. The equation ui2=γ1+γ2x1,j indicates that the error term ui is related with the independent variable x1. Under the general assumptions, the error term us designed to capture ‘unexpected’ events, as such the error term should be random and the independent variable x1 is not random which means that its value if known. Therefore, model I breaks out this assumption, the error term ui is related with the independent variable x1 (not random), error term uiwill hence be not random as well. As a result, the dependent variable y will be not random which is wrong in econometrics. (b) Model II: The major econometric issue is on the error term vt. The equation vt=ρvt-1 indicates that for the pair of random error term vt and vt-1, there is linear association among them. Under the fourth assumption of the simple linear regression model, the covariance between any pair of random errors is zero, implying that there is no linear association among them. Therefore, model II breaks out this assumption, one random error term vt has a linear relationship with another random error term vt-1. (c) Model III: The major econometric issue is on the independent variable x1,i. x1,i~i.i.d(ux, σx2) indicates that x1,i is independent and identically distributed random variables. Under the fifth assumption of the simple linear regression model, it requires the regressors x1,i to...
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...Tests of Hypotheses: z-test and t-test 0801-HypothesisTests.doc Page 1 of 4 NOTES TESTS OF HYPOTHESES As was mentioned earlier, sometimes we cannot survey or test all persons or objects; therefore, we have to take a sample. From the results of analysis from the sample data, we can predict the results from the population. Some questions that one may want to answer are 1. Are unmarried workers more likely to be absent from work than married workers? 2. Are the sixth graders in a certain school significantly less skilled in their mathematical abilities than the average student in the district? 3. In Fall 1996, did students in Math 163-01 score the same on the exam as students in Math 163-02? 4. Is there any difference between the strengths of steel wire produced by the XY Company and Bob’s Wire Company? 5. A hospital spokesperson claims that the average daily room charge for a specific procedure is $622. Can we reject this claim? WHAT IS A HYPOTHESIS? Hypothesis: A statement about the value of a population parameter developed for the purpose of testing. Examples of hypotheses, or statements, made about a population parameter are: The mean monthly income from all sources for systems analysts is $3,625. Twenty percent of all juvenile offenders ultimately are caught and sentenced to prison. Hypothesis testing: A procedure, based on sample evidence and probability theory, used to determine whether the hypothesis is a reasonable statement and should not be rejected, or is unreasonable...
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...will incorporate both descriptive and inferential statistics to evaluate his or her results and create a credible conclusion. Descriptive statistics provides information focused on an immediate group of data. After defining what needs to be analyzed, the descriptive statistics will help the analyzer abridge the data to a more meaningful and comprehendible form, which will then provide patterns in his or her research that, will provide a foundation to his or her thesis. For example, a person could use descriptive statistics to evaluate the answers on an exam taken by 400 American students, and use descriptive statistics to determine the overall performance of the 400 students at that school. By using descriptive statistics, the analyzer can use his or her findings, to provide useful information regarding which subjects students need to improve most in, and which minority group or grade level are grasping the educational tools provided at the school more effectively, then those not grasping the provided educational tools and still need more room for improvement. While descriptive statistics helps an analyzer assess an immediate group of data from a single population, inferential statistics allow an analyzer to collect data using bits and pieces of samples which are portions of a collection of data focusing on the group or population of interest in which the analyzer research is concentrated on at the time. Inferential statistics will allow the analyzer to create a conclusion which...
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...11. List the five steps of hypothesis testing, and explain the procedure and logic of each. Step 1: Restate the Question as a Research Hypothesis and a Null Hypothesis about the Populations. You want to restate the question as research hypothesis and null hypothesis about the populations because it allows you to think of two different samples. The research hypothesis and the null are opposite of each other. One is true and the other is not. The researcher predicts something and researches it and the null hypothesis says there will be no difference if what the researcher predicts. The logic is figuring out the probability of getting a particular result if the null hypothesis is true. Step 2: Determine the Characteristics of the Comparison Distribution In the hypothesis-testing process, you compare the actual sample’s score to this comparison distribution. The comparison distribution is the distribution that represents the population situation if the null hypothesis is true. If the null is true both samples will have a normal curve. Step 3: Determine the Cutoff Sample Score on the Comparison Distribution at Which the Null Hypothesis Should Be Rejected You will need Z scores and percentages, if a researcher decides that the score is lower than a certain percent then they would reject the null. Psychology researchers use a cutoff on the comparison distribution with a probability of 5% that a score will be at least that extreme if the null hypothesis were true. They are described...
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...Activity 1 Advance Statistics with Computer Application Submitted to : Ms Maricar Flores, Ed.D Submitted by: Mary Monette Wee-Diputado 1. What is the title of the research? * Academic Grades, Regional Achievement Test Results and Least Learned Skills of Grade V Mathematics Pupils: Basis for Enrichment Program 2. What are the variables used in the research? If there are two or more variables used, classify each variable as independent, dependent, intervening, or moderating variable. * The age, area of specialization and years of teaching experience of the Math teachers are independent variables. * The age and gender of the Grade V pupils are also independent variables. * The least learned skills in Math V is a moderating variable * The results in the Regional Achievement test is the dependent variable * The grades in Math of the Grade V pupils is also a dependent variable 3. Write all the research questions. For each question, a. Identify what kind of data (qualitative or quantitative) is asked from the respondents b. Identify the kind of statistical treatment/s (descriptive or inferential) used, if the question is quantitative in nature. b.1 If descriptive, what specific statistical tool was used? b.2 If inferential, what specific statistical tool was used? * What is the profile of the Mathematics teacher (s) in terms of: a. Age a. 1(QUANTITATIVE) i. Descriptive (ranging) ...
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...implied population. A recent report on the weekly news presented the findings of a study on the effectiveness of Onglyza, along with diet and exercise, for treating diabetes. Implied population is people with diabetes. 2. In the following scenario identify the type of statistical study that was conducted. A Gallop poll surveyed 1,018 adults by telephone, and 22% of them reported that they smoked cigarettes within the past week. Polls are an Observational type of study as they do not try to sway the numbers. Statistical stats are gathered to measure ‘variables of interest’. 3. In the following scenario what is the statistic and the parameter it would estimate. A recent study of 460 drivers age 70 and over by the National Highway Traffic Safety Administration reported that 75% of those drivers had uncorrected vision problems. The statistic is the 75% of drivers in the study of 460 drivers that have uncorrected vision problems. The parameter is drivers age 70 and over. 4. What type of sampling procedure...
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...Statistics in Business Statistics is defined by Merriam-Webster as a branch of math dealing with the collection, analysis, interpretation and presentation of masses of numerical data; or a collection of quantitative data (Statistics, n.d.). Statistics is all around us. Everything from our actions, to our purchases, to even sports involve the collection, analysis, interpretation and presentation of data. There are two types of statistics. One type is called, descriptive statistics, which uses numbers and graphs to identify patterns and trends in data sets and is used to present revealed information in an easy to understand form. The other type of statistic is known as inferential statistic. Inferential statistics is using sample data collected from a smaller sample, and using those results to make predictions, estimates, decisions and other generalizations about a larger set of data (McClave, Benson, & Sincich, 2011). Statistics plays a number of roles in business decisions. One of the more obvious roles it plays is in marketing. Research studies allow businesses to be proactive by predicting customer behavior and creating specific marketing plans. For instance a business that sells sandals would use statistics to identify when sales have increased and when they are likely to increase again. For instance the spring and summer months show statistics of higher sales, which tells the business to increase inventory at those times. Another one of the many roles statistics...
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...Statistics in Business Joseph Giardino Qnt 351 November 20, 2013 Forrest Boyd Statistics in Business Webster’s dictionary (2013) defines statistics as “a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data; a collection of quantitative data.” At its core, statistics is a mathematical process of crunching numbers and solving equations, just like all other math disciplines. Statistics separates itself by using the data and equations to interpret and influence business decisions. Statistics are commonly classified in one of two category types, descriptive and inferential. Descriptive statistics can be summarized as “the information revealed in a data set, and to present the information in a convenient form” (McClave, Benson, & Sincich, 2011). Inferential uses the data sample to allow individuals to predict or make decisions that will impact the larger data. Having accurate data plays a huge role in the decision-making process businesses go through on a daily basis. “Successful managers rely heavily on statistical thinking to help them make decisions” (McClave, Benson, & Sincich, 2011). Everyday issues that managers face are solved most efficiently when managers create a statistical question that can be solved by data. Collecting data and analyzing outcomes prior to implementing actions will allow the manager to make an informed decision and save time and money by avoiding trial and error. ...
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...Tests of Hypotheses: z-test and t-test 0801-HypothesisTests.doc Page 1 of 4 NOTES TESTS OF HYPOTHESES As was mentioned earlier, sometimes we cannot survey or test all persons or objects; therefore, we have to take a sample. From the results of analysis from the sample data, we can predict the results from the population. Some questions that one may want to answer are 1. Are unmarried workers more likely to be absent from work than married workers? 2. Are the sixth graders in a certain school significantly less skilled in their mathematical abilities than the average student in the district? 3. In Fall 1996, did students in Math 163-01 score the same on the exam as students in Math 163-02? 4. Is there any difference between the strengths of steel wire produced by the XY Company and Bob’s Wire Company? 5. A hospital spokesperson claims that the average daily room charge for a specific procedure is $622. Can we reject this claim? WHAT IS A HYPOTHESIS? Hypothesis: A statement about the value of a population parameter developed for the purpose of testing. Examples of hypotheses, or statements, made about a population parameter are: The mean monthly income from all sources for systems analysts is $3,625. Twenty percent of all juvenile offenders ultimately are caught and sentenced to prison. Hypothesis testing: A procedure, based on sample evidence and probability theory, used to determine whether the hypothesis is a reasonable statement and should not be rejected, or is...
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...MATH 221 Homework Week 1 -Latest IF You Want To Purcahse A+ Work then Click The Link Below For Instant Down Load http://www.acehomework.net/wp-admin/post.php?post=3308&action=edit IF You Face Any Problem Then E Mail Us At JOHNMATE1122@GMAIL.COM MATH 221 Homework Week 1 1. Determine whether the data set is a population or a sample. Explain your reasoning. The age of each resident in an apartment building. Choose the correct answer below. 1. Population, because it is a collection of ages for all people in the apartment building. 2. Sample, because it is a collection of ages for all people in the apartment building, but there are other apartment buildings 3. Population, because it is a subset of all apartment buildings in the city. 4. Sample, because it is a collection of ages for some people in the apartment building. 1. Determine whether the data set is a population or a sample. Explain your reasoning. The salary of each baseball player in a league Choose the correct answer below 1. Sample, because it is a collection of salaries for some baseball players in the league 2. Sample, because it is a collection of salaries for all baseball players in the league, but there are other sports 3. Population, because it is a collection of salaries for all baseball players in the league 4. Population, because it is a subset of all athletes 2. Determine whether the underlined value is a parameter or a statistic. The average age of men who have walked on the moon...
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...problems, which encourage me to pursue a higher degree in Statistics. Because some useful statistics topic in my undergraduate education were either only brought up for a definition or not covered, besides the missing value imputation method, the graphical Markov models, fixed and random effects, and variance analysis are also some of the topics I wish to learn in my graduate study. Besides advanced statistical methodology, I am particularly motivated to develop the links between statistics and computer science, although I have made every effort in studying Statistic software, like SPSS, Eviews, and Clementine, and I use my spare time learning R and C language by myself, I think there is still long way to go. I plan to further improve my programming ability, especially the options and programming techniques I didn’t know before, like the combination of C++ and R will make the loop in R run faster. With the huge amounts of data collected in the worldwide everywhere in every second, the marriage of theories, the effective methodology of numerical analysis and computer science becomes more urgent and important than ever. I believe a good statistician need also be a good programmer. So a university that emphasize statistical methodology and statistical programming is perfect fit my goal. And I found the Master of Science with a Major in Applied Statistics in MSU is the one. I have built up a sufficient foundation in statistics knowledge during my undergrad study. The courses Calculus...
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