...probability and statistics are worked with in the business. Understanding how important statistics and its value to any business will lead the way to success. Overview of the Data Set The variables consist of both quantitative and qualitative data in regards to quantitative data that is known to have a numeric value as this data set includes age, job satisfaction and benefits (Cernauskas, Grey, Hemphill & Segal, 2011). The Qualitative data has a nonnumeric value and the variables for this data set consist of gender, position and department (Cernauskas et al, 2011). The two categories together provide the statistical data for the AIU staff analysis. Use of Statistics and Probability in the Real World The probability theory has survived for over three hundred years and it has grown to be a major part of everyday life (Vidal, n. d.). We have all made decisions based on the simplest activity such as picking straws or rolling dice. However, decisions are also based on likelihood of an event or simply by a hunch (Cernauskas et al, 2011). There are substantial ways that statistics are being used today ranging from areas in genetics, economics, and medicine. Another important use for statistics is for education; the National Center for Educational Statistics (NCES) provides analysis and reports on the data collected in regards to the condition of education in the US as well as the conducting and reporting of educational activities worldwide (National Center for Statistics, n. d.)....
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...PLANNING AND MANAGEMENT COURSE: LDP 603: RESEARCH METHODS ASSIGNMENT STUDENT; GITHUNDI BEDAN. ADMISSION REF-27086/2013 LECTURER; Dr. Lilian Otieno, Resident Lecturer I am tasked to distinguish between parametric and non-parametric statistics and explain when to use each method in analysis of data. I shall first seek to define what parametric and non-parametric statistics mean and then compare and contrast them in the analysis of data. Parametric statistics is a branch of statistics that assumes that the data has come from a type of probability distribution and makes inferences about the parameters of the distribution. Most well-known elementary statistical methods are parametric. (According to Wikipedia, the online dictionary). In statistical analysis, parametric significance tests are only valid if certain assumptions are met. If they are not, nonparametric tests can be used. A parameter is a measure of an entire population, such as the mean height of every man in London. In statistical analysis, one practically never has measurements from a whole population and has to infer the characteristics of the population from a sample. Generally speaking parametric methods make more assumptions than non-parametric methods. If those extra assumptions are correct, parametric methods can produce more accurate and precise estimates. They are said to have more statistical power. However, if assumptions are incorrect, parametric methods can be very misleading. For that reason they are often...
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...DISTINGUISH BETWEEN PARAMETRIC AND NONPARAMETRIC STATISTICS AND DISCUSS WHEN TO USE EACH METHOD IN ANALYSIS OF DATA The word parametric comes from “metric” meaning to measure, and “para” meaning beside or closely related. The combined term refers to the assumptions about the population from which the measurements were obtained. The two classes of statistical tests are: Parametric Statistics Nonparametric Statistics i. Parametric Statistics: Parametric statistics are statistical tests for population parameters such as means, variances and proportions that involve assumptions about the populations from which the samples were selected. These assumptions include: Observations must be independent i.e. when values in one set are different and unrelated from another set Observations must be drawn from normally distributed populations The populations must have the same variances The sample must be random Use of Parametric Statistics in Data Analysis: Parametric tests are used when the above parametric assumptions are met. Parametric tests are also used to analyze interval and ratio data. Interval data are numerical data in which we not only know the order but also the exact differences between the values e.g. the time interval between the starts of years 1981 and 1982 is the same as that between 1983 and 1984 which is 365 days. Ratio data on the other hand describe measurements with attributes that have the qualities of nominal, ordinal and interval data and...
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...Statistics as a discipline is the development and application of methods, and a collection of mathematical techniques that help to collect, analyze, interpret, and present data. Modern statistical methods involve associated tasks such as the designing and analyzing of experiments and surveys, the quantification of biological, social and scientific phenomenon and the application of statistical principles to understand more about the world around us. Statistics can also imply a second meaning, which is the computed quantity with the help of statistical methods. Thus, it could be said that the main statistics of a particular study are the median age and income of the group. Thus statistics can imply a statistical parameter as well. Statistics can be applied to various different problems and situations but the underlying concepts all remain the same. It can also be broadly classified into descriptive statistics and inferential statistics. The ideas of presenting data and drawing relevant inferences are central to the successful use of statistical theory. In the end, the statistical analysis should be able to tell us something concrete about the sample that we are studying. A number of errors are possible in the interpretation of statistical results and a careful analysis needs to be made to prevent these errors. Basically, statistics is applicable in a variety of fields, and business is not exclusive. Decision making in business is a complex thing. It is not something like “I...
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...ForecastX Software (There will be additional ForecastX notes for subsequent chapters) 1. Insert disk and install a. Note: you will have to do this every time you use a campus computer, but the process should only take a minute or two. b. Insert disk. If a McGraw Hill screen pops up, just agree to what it is asking you, and then reduce the window. c. Double click on “My computer” d. Select (click once on) cdrom drive (or whatever the listing is for the drive into which you have inserted your disk), right click over the shaded area, select “open” from the menu, click on “forecast x installer”, click on “setup.exe” (You may find there are two “setup” files, if so, choose the top one, but try the bottom one if the top one doesn’t work.) 2. Add in the forecast x add-in. a. Open excel b. Click on the following: File, options, add-ins. You should see “Forecastx7Toolbar” underneath “Active Application Add-Ins”. To make sure that ForcastX is installed, click on “go” at the bottom of the page, and make sure that there is a check in the check box next to ForecastX in the pop up box that appears, then click on OK. Then close out of Excel, and reopen Excel. You should find ForecastX when you select the Add-Ins bar at the top of the page. c. If you do not see ForecastX in the pop up box, click ok and close Excel. Then close Excel and do step 2b again. If you still do not see ForecastX in the pop up box, Click on...
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...and statistics are two related but separate academic disciplines. Statistical analysis often uses probability distributions, and the two topics are often studied together. However, probability theory contains much that is of mostly of mathematical interest and not directly relevant to statistics. Moreover, many topics in statistics are independent of probability theory. Probability (or likelihood) is a measure or estimation of how likely it is that something will happen or that a statement is true. Probabilities are given a value between 0 (0% chance or will not happen) and 1 (100% chance or will happen). The higher the degree of probability, the more likely the event is to happen, or, in a longer series of samples, the greater the number of times such event is expected to happen. These concepts have been given an axiomatic mathematical derivation in probability theory (see probability axioms), which is used widely in such areas of study as mathematics, statistics, finance, gambling, science, artificial intelligence/machine learning and philosophy to, for example, draw inferences about the expected frequency of events. Probability theory is also used to describe the underlying mechanics and regularities of complex systems. Statistics is the study of the collection, organization, analysis, interpretation and presentation of data. It deals with all aspects of data, including the planning of data collection in terms of the design of surveys and experiments. The word statistics, when...
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...Statistical Methods This paper talks about statistical methods. Statistical data indicates that the agency 's approach is characterized by its population by inference Presented from a representative sample of the population views. As scientists rarely observed throughout Crowd, sampling and statistical inference is essential. This paper discusses some of the general principles Visualization of planning experiments and data. Then, a strong focus on the appropriate choice Standard statistical models and statistical inference methods. First of all, the Standard Model described. These models, in order to apply interval estimation and hypothesis testing parameters Also described, including the next two sample cases, when the purpose of comparing two or more of the population For their means and variances. Secondly, non-parametric inference tests are also described in the case where the data Sample distribution is not compatible with standard parameter distribution. Thirdly, using multiple resampling methods Computer -generated random sample finally introduced the characteristics of the distribution and estimate Statistical inference. The method of multivariate data processing of the following sections involved. method Clinical trials also briefly review process. Finally, the last section of statistical computer software discussion And through the collection of citations to adapt to different levels of expertise, and to guide readers theme. In this article, there are some methods such...
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...Define Statistics More than 100 years ago H.G. Wells, an English author and historian, suggested that one day quantitive reasoning will be as necessary for effective citizenship as the ability to read”. This author was ahead of his times because it affected all the aspects of life, business and personal. Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making a more effective decision. We use statistics everyday of our lives from the moment we wake up and start making decisions to the moment we put our heads back in the pillow at night to go to sleep. Almost every type of major requires us take a course of statistics. There are three major reasons; the first one is because there is numerical information everywhere, second one is that statistical techniques are used to make decisions that affect our daily lives. The third reason is that having the knowledge of statistical methods will help us have a better understanding of how decisions are made and how they affect us. Types and Levels of Statistics The types of statistics are, Descriptive Statistics and Inferential Statistics. Descriptive statistics is the method of organizing, summarizing and presenting the data in an informative way. The text use an example of a presentation of the population of the United States from the 1960’s till the present showing the increase on the population throughout the years. Inferential statistics is the method used to...
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...TERM END EXAMINATIONS,MARCH-2013 BACHELOR OF COMMERCE, YEAR – III ELEMENTARY STASTISTICS Time: 3 hours M.Marks:60 SECTION A Note: - Attempt any 4 questions. All questions carry equal marks. (4 X 5) The answer should be limited upto 200 words. 1) What is statistics? Explain the nature and limitations of statistics? 2) What is frequency distribution? What are the different types of frequency distribution? 3) What is frequency curve? Explain cumulative frequency curve with example? 4) Suppose mean of a series of 5 item is30.four values are respectively, 10, 15, 30 and 35.estimate the missing 5th value of the series. ANSWER : Mean = (10+15+30+35+x)/5=30 Therefore, x=(30*50)-( 10+15+30+35) i.e x = 150-90, hence x=60 5) Calculate median of the following distribution of data. Class interval | 0-5 | 5-10 | 10-20 | 20-30 | 30-50 | 50-70 | 70-100 | frequency | 12 | 15 | 25 | 40 | 42 | 14 | 8 | n= 12+15+25+40+42+14+8=156 Hence median is at the average of n/2 & (n/2 +1) positon i.e 78th & 79th position Class interval | 0-5 | 5-10 | 10-20 | 20-30 | 30-50 | 50-70 | 70-100 | frequency | 12 | 15 | 25 | 40 | 42 | 14 | 8 | Position 12 27 52 92 134 148 156 6) Calculate the coefficient of correlation...
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...Write a brief paper on Statistics and Operations Research in the context of Analytics. Analytics is defined as the scientific process of transforming data into insight for making better decisions. It is the combination of skills, technologies, applications and processes used by data scientist to gain insight in to their business based on data and statistics to drive business planning. It typically use’s data, statistical and quantitative analysis to measure the performance of the subject (Organization/ website etc.) on which a study is to be conducted. Analytics can be used in various fields such as market research, for studying user web pattern behavior & in many other applications to derive some meaningful information out of the complex world around us. But we will first touch upon the area of operations research & how Analytics with the help of various statistical tools can help to solve the operation related problem in an organization. Operations research overlaps with other disciplines, such as industrial engineering and operations management. It is often concerned with determining an optimal solution out of a business problem. It may either to maximize your profit, performance, or yield or minimize your losses, risk, or cost. In the fields of production, logistics, or sales where managers are facing a problems so as how to allocate resources, develop production schedules, manage the supply chain, and set prices. For example, it many help to decide how to organize...
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...analysis with statistics has got less to do with numbers, and more to do with rules for arranging them. It even lets you create some of those rules yourself, so instead of looking at it like a lot of memorization, it's best to see it as an extension of the research mentality, something researchers do anyway (i.e., play with or crunch numbers). Once you realize that YOU have complete and total power over how you want to arrange numbers, your fear of them will disappear. It helps, of course, if you know some basic algebra and arithmetic, at a level where you might be comfortable solving the following equation There are three (3) general areas that make up the field of statistics: descriptive statistics, relational statistics, and inferential statistics. 1. Descriptive statistics fall into one of two categories: measures of central tendency (mean, median, and mode) or measures of dispersion (standard deviation and variance). Their purpose is to explore hunches that may have come up during the course of the research process, but most people compute them to look at the normality of their numbers. Examples include descriptive analysis of sex, age, race, social class, and so forth. 2. Relationalstatistics fall into one of three categories: univariate, bivariate, and multivariate analysis. Univariate analysis is the study of one variable for a subpopulation, for example, age of murderers, and the analysis is often descriptive, but you'd be surprised how many advanced statistics can be computed...
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...STATISTICS TEST Length: 1090 words (3.1 double-spaced pages) Rating: Red (FREE) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Statistics are necessary for scientific research because they allow the researchers to analyze empirical data needed to interpret the findings and draw conclusions based on the results of the research. According to Portney and Watkins (2009), all studies require a description of subjects and responses that are obtained through measuring central tendency, so all studies use descriptive statistics to present an appropriate use of statistical tests and the validity of data interpretation. Although descriptive statistics do not allow general conclusions and allow only limited interpretations, they are useful for understanding the study sample and establishing an appropriate framework for the further analysis in the study. Further analysis using appropriate statistical methods allows the researchers to establish correlations between independent and dependent variables, define possible outcomes, and identify areas of potential study in the future accurately. Statistics is important for researchers because it allows them to investigate and interpret the data more accurately, and researchers will notice patterns in the data that would be overlooked otherwise and result in inaccurate and possibly subjective conclusions (Portney &ump; Watkins, 2009). Frequency distribution is a method used in descriptive statistics to arrange...
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... Lynne s Background (Why me?) Lynne’s Background (Why me?) • 40+ years in industry – Nabisco, then Kraft , – Unilever (Lipton) – Hunt‐Wesson Foods • Academic – AB Math The Colorado AB Math, The Colorado College – MS, Applied and Mathematical Statistics, Rutgers – PhD, Interdisciplinary, Rutgers • Government: NIST Government: NIST • Academia – Cal. St. Fullerton (MBAs) – Rutgers (Experiment Station) ( ) • ASA – Chair P&Q Division – Fellow ‘94 • Consulting – Consumer goods – Pharmaceuticals – R&D, Manufacturing, Quality • ASQ – Chair Statistics Division – Fellow ’86 – Column Quality Progress Column: Quality Progress Slide 3 Statisticians?? Not sure N t Yes No Don’t care. This is the only session that looked remotely interesting. that looked remotely interesting 4 How can you tell? How can you tell? • If you have more than one pen with you If you have more than one pen with you • If you know more than one joke about the binomial distribution binomial distribution • If your glasses are thicker than mine • If you are too shy to be an accountant • If you talk to your colleagues in SAS y y g 5 1. Motivation 1 Motivation Statistical Engineering 1. Motivation The State of Statistics as...
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...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. * Standard deviation. Compute the standard deviation (σ) of the...
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...Institute of Management Sciences Peshawar Bachelors in Business Studies Course Plan Course Title: Statistics for Business Instructor: Shahid Ali Contact Email shahid.ali@imsciences.edu.pk Semester/Duration: 16 Weeks Course objectives : To introduce students to the concepts of statistics and to equip them with analytical tools to be used in business decision making. The course is intended to polish the numeric ability of the students to identify business problems, describe them numerically and to provide intelligible solutions by data collection and inferential principles. Course pre-requisites Intermediate statistics Attendance Policy: Late arrivals are highly discouraged. Any student coming late to a class late by 5 minutes after the scheduled start time will be marked as absent for the day. The teacher reserves discretion, however, to allow or disallow any student, to sit in the class in case of late arrivals. Attendance is not be entertained once the attendance register is closed. Class Project Students will be divided in groups for a class project. Each group will have to nominate a group leader. The details of the project will be made available to the group leader. Class Presentations Each student will have to make at least one individual presentation and one group presentation in the class. The group presentation will be on the project explained earlier. The individual presentations will...
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