... Introduction to Statistics LEARNING OBJECTIVES The primary objective of chapter 1 is to introduce you to the world of statistics, enabling you to: 1. Define statistics. 2. Be aware of a wide range of applications of statistics in business. 3. Differentiate between descriptive and inferential statistics. 4. Classify numbers by level of data and understand why doing so is important. CHAPTER OUTLINE 1.1 Statistics in Business Best Way to Market Stress on the Job Financial Decisions How is the Economy Doing? The Impact of Technology at Work 1.2 Basic Statistical Concepts 1.3 Data Measurement Nominal Level Ordinal Level Interval Level Ratio Level Comparison of the Four Levels of Data Statistical Analysis Using the Computer: Excel and MINITAB KEY TERMS census ordinal level data descriptive statistics parameter inferential statistics parametric statistics interval level data population metric data ratio level data nominal level data sample nonmetric data statistic nonparametric statistics statistics STUDY QUESTIONS 1. A science dealing with the collection, analysis, interpretation, and presentation of numerical data is called _______________. 2. One way to subdivide the field of statistics is into the two branches...
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...Use of Statistical Information HCS/438 August 6, 2012 Use of Statistical Information Statistics is defined as “the science of collecting, organizing, and interpreting data” (Bennett, Briggs, & Triola, 2009). For most patients and their families, the process of healthcare appears simple. People with illnesses are admitted into a hospital facility and a specific course of treatment is identified and the care is carried out by a team of physicians, nurses, and social workers. What is not noticed is a specialized resource team aimed at keeping all patients safe throughout the course of their hospitalization. This paper will identify how statistics are utilized in the infection prevention setting, identify one example of descriptive statistics, identify one example of inferential statistics, explain data at each of the four levels of measurement and describe the advantages of accurate interpretation of statistical information to improve decision making in the workplace. How Are Statistics Used in Your Workplace There are many uses for statistical application in the field of infection prevention and control. The purpose of infection prevention and control is to put into place policies and procedures that minimize the spread of infections, especially in the hospital setting. The primary function of infection prevention and control surveillance is to reduce the occurrence of infections by using risk factors and implementation of risk-risk reduction measures and the...
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...Chapter 3 Methodology Historical Research Design purpose is to collect, verify, synthesize evidence to establish facts that defend or refute your hypothesis. It uses primary sources, secondary sources, and lots of qualitative data sources such as logs, diaries, official records, reports, etc. The limitation is that the sources must be both authentic and valid. When we think of research, we often think of a laboratory or classroom where two or more groups receive different treatments or alternative training methods. We would then determine if the treatment or training had an impact on some outcome measure. This type of research is the best at predicting cause and effect relationships and is often cited as the most rigorous and standardized form. While the experiments described above have a definite place in the research arena, sometimes we gain the best knowledge by looking into the past rather than into the future. Historical research attempts to do just that. Through a detailed analysis of historical data, we can determine, perhaps to a lesser extent, cause and effect relationships. We can also help prevent the present day teachers, managers, and other users of research from making the same mistakes that were made in the past. Historical research can also mean gathering data from situations that have already occurred and performing statistical analysis on this data just as we would in a traditional experiment. The one key difference between this type of research and...
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...Simulation with Arena Assignment G2: a multi-echelon inventory policy Christopoulou Evdoxia Kuodzevicius Bernardas 101283 534893 10/12/2012 Preliminaries The given Arena model is a steady-state model, because there is no clear event that could indicate the end of model run and actually we are interested in the long run behavior of the system represented by the given model. Before we start to do the main parts of the assignment, that is design of experiments and optimization, we conduct some preliminary experiments to check if the model could be modified in order to get better results. First we set the number of replications to 30 and we choose the length of each replication be 730 days (two years), which we think should be enough to reach the steady-state. When we run the model with these settings, we get that the mean of the main response variable - average cost - is 568.4 and the half width is equal to 2.37. Although the confidence interval is not extremely wide taking into account the relatively high value of mean, we still perform a check whether it is possible to get more precise results by using common random numbers. To figure out if the model would benefit from the use of CRN we perform a pilot study. In this study we need to have two different scenarios and then we can decide whether it is useful to use CRN by checking the following inequality: { } { } { } and if this inequality holds, then it is worth using CRN in the model. In our case the scenarios differ in three...
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...approximately equal to the variance of the population divided by each sample's size. This statistical theory is very useful when examining returns for a given stock or index because it simplifies many analysis procedures. An appropriate sample size depends on the data available, but generally speaking, having a sample size of at least 50 observations is sufficient. Due to the relative ease of generating financial data, it is often easy to produce much larger sample sizes. • Null Hypothesis: States the assumption (numerical) to be tested, for Example: The average number of TV sets in U.S. Homes is at least three (H0: μ ≥ 3). 1. Is always about a population parameter, not about a sample statistic. ✓ H0: μ ≥ 3 X H0: [pic] ≥ 3 Always begins with the assumption that the null hypothesis is true, similar to the notion of innocent until proven guilty. Refers to the status quo. Always contains “=”, “≤” or “≥” sign. May or may not be rejected. 1. • The Alternate Hypothesis : Is the opposite of the null hypothesis e.g.: The average number of TV sets in U.S. homes is less than 3 ( HA: μ< 3 ) Challenges the status quo...
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...Teradata Database Release Summary Release 12.0 B035-1098-067A March 2008 The product or products described in this book are licensed products of Teradata Corporation or its affiliates. Teradata, BYNET, DBC/1012, DecisionCast, DecisionFlow, DecisionPoint, Eye logo design, InfoWise, Meta Warehouse, MyCommerce, SeeChain, SeeCommerce, SeeRisk, Teradata Decision Experts, Teradata Source Experts, WebAnalyst, and You’ve Never Seen Your Business Like This Before are trademarks or registered trademarks of Teradata Corporation or its affiliates. Adaptec and SCSISelect are trademarks or registered trademarks of Adaptec, Inc. AMD Opteron and Opteron are trademarks of Advanced Micro Devices, Inc. BakBone and NetVault are trademarks or registered trademarks of BakBone Software, Inc. EMC, PowerPath, SRDF, and Symmetrix are registered trademarks of EMC Corporation. GoldenGate is a trademark of GoldenGate Software, Inc. Hewlett-Packard and HP are registered trademarks of Hewlett-Packard Company. Intel, Pentium, and XEON are registered trademarks of Intel Corporation. IBM, CICS, RACF, Tivoli, z/OS, and z/VM are registered trademarks of International Business Machines Corporation. Linux is a registered trademark of Linus Torvalds. LSI and Engenio are registered trademarks of LSI Corporation. Microsoft, Active Directory, Windows, Windows NT, and Windows Server are registered trademarks of Microsoft Corporation in the United States and other countries. Novell and SUSE are registered trademarks...
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...Statistics in Business Adam Cavkic QNT/351 12/15/2014 Mark Alsakka Statistics in Business Statistics can be defined as the science of data; statistics consists of collecting, classifying, summarizing, organizing, analyzing, and interpreting numerical data. The different types and levels of statistics are descriptive and inferential statistics. Descriptive statistics are numerical and graphical methods used to look for patterns in a data set so that the information in the data set can be analyzed so that the information can be summarized in a convenient form for others to clearly understand the presented information. Inferential statistics are estimates, decisions, and predictions based on the study of sample data to summarize a larger set of data. The role of statistics in business decision making is crucial as statistics can give companies an idea of what the consumers want simply by observing the different goods and services that the company put out to see how much money was made and how much of a demand is there still for that particular good or service. Statistics in business decision making also consists of comparing present statistics with older previous statistics to see what area could be improved. Some examples or problem situations in which statistics were used or could be used would be Microsoft using earlier sale records of previous Xbox consoles released to make a prediction...
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...occur. The purpose of basic research is not the formation of a definite solution, but to create a set of probabilities to predict current or future events. Team B has chosen a set of data that includes statistic relating to the business of Major League Baseball. The statistical value of this sport is more main-stream than ever after the release of Money Ball, a movie based on true events that focused solely on statistics and not player’s visual abilities or presence. Team B will use the statistics presented to determine if there is a measurable advantage in the production of games won based on a team’s payroll, facility size, and attendance record. The statistics provided are for the years of 1989 to 2005. Team B will attempt to predict who the Major League Champion will be in 2006 using only the statistics given in the data set. Purpose of the research The purpose of this research is for Team B to try and determine the 2006 Major League Baseball, (MLB) champion with data provided only through 2005. The problem with this research is there are multiple variables that take place. For example, the data shows teams with higher attendance both in the higher bracket and lower bracket of wins. Same goes for the error statistics; St Louis Cardinals committed 100 errors but also the most wins...
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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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...Assess the strengths and limitations of using official statistics for investigating the effects of material deprivation on educational achievement. Material deprivation is a technical name for poverty and its effects on educational achievement. It is a theory put forward by sociologist Harker. Official statistics is a form of secondary data produced and published by the government and its agencies. These are collected in three main ways: government surveys, registration and record-keeping. The strengths of official statistics are that they are easily accessible and cheap. They are an up-to-date source of data which means the researcher doesn’t have to spend time and money collecting information. Official statistics can be useful in providing relevant statistics in areas such as household income. They cover large populations and are therefore representative, which is useful when conducting a large, quantitative study. This information can be linked to educational achievement by studying income alongside educational achievement rates in schools in poor and wealthy areas. Official statistics have shown that students who are from materially deprived backgrounds and who are entitled to free school meals and bus passes are the children who tend to have lower results when they finish school. Attendance is also a factor that has been found through official statistics, to affect how a student will achieve in school. They have also shown that EMA used to affect the achievement of...
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...1. State the null and the alternative hypotheses in this scenario (4 pts): A new sales force bonus plan is developed in an attempt to increase sales. Null hypothesis: New bonus plan does not increase sales. Alternative hypothesis:--New bonus plan increases sales. 2. For this question refer to Case Problem 1 (Quality Associates Inc.) on page 410 of your text (30 pts) Sample 1 1) H0: μ = 12 Ha: μ ≠ 12 2) α = .01, but for two-tail test will = .005 3) Z = (x-bar – μ) / (σ/√n) 4) Z Critical value at .005 = 2.575 5) Z = (11.9587 – 12) / (.21/√30) = -1.077187 The observed value lies outside the rejection region, so we fail to reject H0. 6) P –value is between .2814 for a two-tailed test Sample 2 1) H0: μ = 12 Ha: μ ≠ 12 2) α = .01, but for two-tail test will = .005 3) Z = (x-bar – μ) / (σ/√n) 4) Z Critical value at .005 = 2.575 5) Z = (12.0287 – 12) / (.21/√30) = .74855 The observed value lies outside the rejection region, so we fail to reject H0. 6) P-value is 0.4541 for a two-tailed test Sample 3 1) H0: μ = 12 Ha: μ ≠ 12 2) α = .01, but for two-tail test will = .005 3) Z = (x-bar – μ) / (σ/√n) 4) Z Critical value at .005 = 2.575 5) Z = (11.889 – 12) / (.21/√30) = - 2.895 The observed value lies inside the rejection region, so we reject H0. 6) P-Value is .0038 for a two-tailed test Sample 4 1) H0: μ = 12 Ha: μ ≠ 12 2) α = .01, but for two-tail test will = .005 3) Z = (x-bar – μ) / (σ/√n) 4)...
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...this option please state you are my student and the class name and section or I will not accept invitation.) Faculty Service Center: (513)732-5335 Electronic Communication This is an online course which uses Blackboard linked to MyMathLab. Course Description: This course develops fundamental knowledge and skills for applying statistics to business decision making. Topics include descriptive statistics, probability distributions, confidence intervals and hypothesis testing and the use of computer software for statistical applications. Learning Outcomes: The successful Business Analytics I student should be able to: 1) Organize and summarize data using appropriate descriptive statistics and graphical methods. 2) Understand the concept of probability and to be able to calculate probabilities required in order to perform statistical inferences. 3) Understand the concept of a random variable and use discrete and continuous random variable and their corresponding distributions to calculate probabilities. 4) Understand the concept of a sampling distribution and be familiar with the primary sample statistics and their distributions. 5) Estimate population parameters using...
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...SPSS Instruction Manual University of Waterloo Department of Statistics and Actuarial Science September 1, 1998 Table Of Contents Page Before Using This Manual……………………………………………………………………………….3 Introduction to SPSS……………………………………………………………………………………..4 SPSS Basics……………………………………………………………………………………………... 5 Tutorial 1: SPSS Windows.…………………………………………………………………………5 Tutorial 2: Starting A SPSS Session.……………………………………………………………...6 Tutorial 3: Getting Help on SPSS.………………………………………………………………… 6 Tutorial 4: Ending A SPSS Session.……………………………………………………………… 6 Creating and Manipulating Data in SPSS.……………………………………………………………. 7 Tutorial 1: Creating a New Data Set.……………………………………………………………... 7 Tutorial 2: Creating a New Data Set From Other File Formats.……………………………….10 Tutorial 3: Opening an Existing SPSS Data Set.………………………………………………. 16 Tutorial 4: Printing a Data Set.…………………………………………………………………… 16 Generating Descriptive Statistics in SPSS…………………………………………………………...17 Tutorial 1: Mean, Sum, Standard Deviation, Variance, Minimum Value, Maximum Value, and Range.……………………………………………………….. 17 Tutorial 2: Correlation.…………………………………………………………………………….. 18 Generating Graphical Statistics in SPSS……………………………………………………………..20 Tutorial 1: How to Generate Scatter Plots.………………………………………………………20 Tutorial 2: How to Generate A Histogram.………………….…………………………………... 22 Tutorial 3: How to Generate A Stem and Leaf Plot……………………………………………..23 Tutorial 4: How to Generate A Box Plot………………………………………………………….26 Statistical Models in SPSS……………………………………………………………………………...
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...mining, marketing research, information analysis and findings. Statistics is way to finding the answer. Statistics – The Method of Organizing Data Generally, statistics is a set of disciplines to analyze quantitative information. Statistics entails all aspects of information: comprehending, collecting, communicating, organizing, and interpreting. All of these are the key reference for forecasting consequences or decision making. Thus, it permits us to estimate the extent of our errors. Purchasing a Business It is not an easy task or decision to purchase a business. Before the final decision is made there are many things to consider. To start with, what exactly do you want to achieve? For whatever reason, you must be sure that it is something that you are ready to devote a large amount of time and energy too. Otherwise, you might be trapped into doing something that you loathe. You must ask yourself how far you are ready to commit. How much of your own time, energy, and money are you willing to sacrifice? Finer Diner Sales Proposal The owner of the Finer Diner submitted a proposal to you in hopes of selling the business to you. His asking price is $250,000. Your financial institution advises that your monthly payment to finance that amount would be $1850.00. This is in addition to other business expenses you would incur such as product, payroll, etc. Upon reviewing the accounting records from the restaurant, you discover that it grosses roughly $3000...
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...Assignment 1: Bottling Company Case Study xxxxxxx xxxxx Professor xxxxx Math 300 – Statistics June 9, 2014 Imagine you are a manager at a major bottling company. Customers have begun to complain that the bottles of the brand of soda produced in your company contain less than the advertised sixteen (16) ounces of product. Your boss wants to solve the problem at hand and has asked you to investigate. You have your employees pull thirty (30) bottles off the line at random from all the shifts at the bottling plant. You ask your employees to measure the amount of soda there is in each bottle. Note: Use the data set provided by your instructor to complete this assignment. In this case, as the supervisor of the bottling company, I began an investigation to find out why customers are complaining about our bottles having less ounces than the sixteen ounces that are advertised. To begin my research, I needed to find an answer of how many ounces are each bottle that we send out, and to accomplish this we need to start by calculating the mean number, median and standard deviation of the ounces in each bottle. Today, I decided to randomly pull 30 bottles to calculate the ounces of each, which will give us an idea of what to do if there is a problem. To determine the average of a set of data values, we need the sum of all of the data values divided by the number of data values. Which is calculated as follows: Mean = (Sum of all data values) / (Number of data values). In my research...
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