...data to assist in making more effective decisions. Types of Statistics There are two different types of statistics Descriptive Statistics and Inferential Statistics. Descriptive Statistics is the methods of organizing, summarizing, and presenting data in an informative way. Inferential Statistics is the method used to estimate a property of a population on the basis of a sample. Levels of Measurement There are four levels of measurements with statistics. The levels of measurement are the nominal, ordinal, interval, and ratio. Nominal Level of Measurement Of the four, the lowest and most primitive of the four levels of measurement is the nominal level of measurement. In the nominal level, the data are sorted into categories with no particular order to the categories. Ordinal Level of Measurement The ordinal level of measurement presumes that one classification is ranked higher than another classification. Interval Level of Measurement The interval level of measurement has the ranking characteristics of the ordinal level of measurement plus the characteristics that the distance between values is a constant size. Ratio Level of Measurement The highest, or the level that gives the most information about the observation, is the ratio level of measurement. The ratio level of measurement has all the characteristics of the interval level, plus there is a 0 point and the ratio of two values is meaningful. Statistics in the Business Decision Making Process Statistics...
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...be time to call Guinness. You've got to be close to breaking the record. Qualitative data is information about qualities; information that can't actually be measured. Some examples of qualitative data are the softness of your skin, the grace with which you run, and the color of your eyes. However, try telling Photoshop you can't measure color with numbers. Here's a quick look at the difference between qualitative and quantitative data. The age of your car. (Quantitative.) The number of hairs on your knuckle. (Quantitative.) The softness of a cat. (Qualitative.) The color of the sky. (Qualitative.) The number of pennies in your pocket. (Quantitative.) Remember, if we're measuring a quantity, we're making a statement about quantitative data. If we're describing qualities, we're making a statement about qualitative data. Keep your L's and N's together and it shouldn't be too tough to keep straight. There are a number of ways in which qualitative data can be displayed. A good way to demonstrate the different types of graphs is by looking at the following example: When Apple Computer introduced the iMac computer in August 1998, the company wanted to learn whether the iMac was...
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...Organize and strengthen knowledge in each measurement tool for decision-making GB519: Learn to thoroughly examine decisions using measurement perspectives; immediately interpret the possible outcomes of decisions based on quantitative and qualitative values. GB519: The class text truly taught me a number of measurement concepts in decision-making including our ch. readings and assignments related to decision-tree analysis, forecasts, and pay-off table. The course material and the hands-on excel assignment was definitely a huge contribution to what I now know and understand of it. Investigate effective measurement techniques GB519: Understand the ongoing issues in decision-making such as investment risks, residual income, or performance-related issues pros and cons today. GB519: Unit 2’s discussion on decision making and analysis in today’s music market segments directly helped me understand effective qualitative measurement techniques in making decisions. Forecasts is another great pointer for making decisions based on quantitative understanding. Applying ethical principles GB519: Explore current cases in management decisions and identifying issues. GB519: There were several unit discussion topics that helped enhance my view in understanding ethics in decision-making including our insightful threads on biases, data integrity, and auditing. Understanding leadership approaches to processing decision GB519: Learn to be proactive and determine what’s good, bad, or what...
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...with the accuracy the business collects of the information to review and help make the best decision based on these findings. It is concerned with extracting the best possible information from data in order to aid decision making. As Define statistics a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data Identify different types and levels of statistics. Nominal Measurement There are handful of types and levels of statistics, Nominal measurements, “In social research, variables measured at a nominal level include gender, race, religious affiliation, college major, and birthplace. Ordinal measurement, in this classification, the numbers assigned to objects represent the rank order (1st, 2nd, 3rd etc.) of the entities measured. The numbers are called ordinals. The variables are called ordinal variables or rank variables. Comparisons of greater and less can be made, in addition to equality and inequality” ("Level Of Measurements," 2015). Interval measurements, “the numbers assigned to objects have all the features of ordinal measurements, and in addition equal differences between measurements represent equivalent intervals. That is, differences between arbitrary pairs of measurements can be meaningfully compared. Ratio measurement, a ratio measurement scale is one in which the ratio between any two measurements is meaningful. To achieve this a ratio scale has to have a non-arbitrary zero value. Then operations...
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...Performance Measurement Promotes Effective Management Effective management is based on a foundation of effective measurement, and almost everything else is based on that. Bain & Company director emeritus and customer loyalty expert Frederick Reichheld unequivocally put it this way: "Measurement systems create the basis for effective management."[7] As Figure 1-1 illustrates, measurement determines what management does, and it works—through management—to touch every part of the organization, including compensation and rewards. Figure 1-1: MEASUREMENT: THE MOST FUNDAMENTAL MANAGEMENT SYSTEM. Organizations are conglomerations of many systems. Measurement is actually the most fundamental system of all. When the "measurement system" works well, management tends to manage (and reward) the right things—and the desired results will occur. The measurement system—for good or ill—triggers virtually everything that happens in an organization, both strategic and tactical. This is because all the other organizational systems are ultimately based on what the measurement system is telling the other systems to do. Unfortunately, as we will see, most organizations do not have one integrated measurement system, but rather many measurement systems located in functional "silos" and not well interconnected. I am continually amazed how many leaders pursue the wrong things— and it almost always comes down to what is being measured. The wrong measures tend to trigger the wrong activities—because...
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...agent-based intelligent environmental monitoring system Ioannis N. Athanasiadis and Pericles A. Mitkas ABSTRACT Fairly rapid environmental changes call for continuous surveillance and on- line decision- making. Two areas where IT technologies can be valuable. In this paper we present a multi-agent system for monitoring and assessing air-quality attributes, which uses data coming from a meteorological station. A community of software agents is assigned to monitor and validate measurements coming from several sensors, to assess air-quality, and, finally, to fire alarms to appropriate recipients, when needed. Data mining techniques have been used for adding data-driven, customized intelligence into agents. The architecture of the developed system, its domain ontology, and typical agent interactions are presented. Finally, the deployment of a real-world test case is demonstrated. Keywords : Multi-Agent Systems, Intelligent Applications, Data Mining, Inductive Agents, Air-Quality Monitoring Introduction Environmental Information Systems (EIS) is a generic term that describes the class of systems that perform one or more of the following tasks: environmental monitoring, data storage and access, disaster description and response, environmental reporting, planning and simulation, modeling and decision- making. As the requirements for accurate and timely information in these systems are increasing, the need for incorporating advanced, intelligent features in EIS is revealed. In this context...
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...statistics, the four levels of data measurement, the role of statistics in decision making, and last, the implementation of statistics is problem solving. Statistics According to Jaggia and Kelly, the definition of statistics is a method of the collection, organization, and interpretation of data. In a broad sense, statistics is the communication of numerical information into written form. The authors discuss the breakdown of statistics; first, finding the right data, second, using the right tools to display the data, and finally, to communicate the numerical data into a written language (2014). Qualitative data Qualitative data such as, labels or names are used to identifying different characteristics of variables on a set of people, objects, or events (Jaggia & Kelly, 2014). Qualitative derives from the word quality. As an example, if we examine a latte, the qualitative description/data would be; the robust aroma, the frothy appearance, the strong taste and the beige ceramic cup it is poured in. Quantitative data Quantitative variables are described with numerical values (Jaggia & Kelly, 2014). Let's take the latte example and examine it in quantitative data form. The latte is 12 ounces, the serving temperature is 150º Fahrenheit, the serving cup is 5 inches in height and the cost is $4.00. Four levels of data measurement To conduct statistics, we must use data measurements. In statistics, there are four types of measurement scales. In order to choose the...
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...humanities, government and business ("Statanalysis Consulting", 2013). Statistics is used in decision making that affects our everyday lives. The study of statistics is divided into two categories and has four levels of measurements. The two types of statistics are descriptive statistics and inferential statistics. Descriptive statistics is the organizing, presenting, and analyzing of data in an informative way. Inferential statistics is the methods used to estimate a property of a population on the basis of a sample. The four levels of measurements in statistics are nominal, ordinal, interval, and ratio. The first scale is nominal. The nominal level of measurement is the lowest level. Nominal data deals with names, categories, or labels. The next level is called the ordinal level of measurement. Data at this level can be ordered, but no differences between the data can be taken that are meaningful. The interval level of measurement deals with data that can be ordered, and in which differences between the data does make sense. The fourth and highest level of measurement is the ratio level. Data at the ratio level possess all of the features of the interval level, in addition to a zero value (Taylor, 2013). Probability is used in business to both evaluate financial and decision-making risk and to improve business performance. Business statistics is the science of making sound decisions in spite of uncertainty, and it may be applied to fields ranging from econometrics and financial...
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...Ethics Game Week 5 Performance measurements Performance measurements are used to characterize and define performance in a project. They are used to track and manage progress toward achieving specific project goals. Performance measurements help determine how decision-making processes of a project led to its success or failure, understanding these can help organizations make future improvements. It is a project manager's responsibility to measure performance based on the triple constraints of time, budget, and quality of a project. There are many performance measurements a project manager can use based on the type of project at hand, this paper compares and contrasts the following measurements - * Earned Value * Customer Satisfaction * Requirements Performance Earned Value Earned Value measures work performed in terms of schedule and budget of a project. It helps identify schedule and budget mishaps in all areas of a project. "Earned Value is an approach where you monitor the project plan, actual work, and work-completed value to see if a project is on track. Earned Value shows how much of the budget and time should have been spent, with regard to the amount of work done so far" (Haughey, 2013). It measures current performance in a project, which helps project managers determine what the future performance will be. Using earned value, project managers can determine how much work is completed vs., how much was expected to be completed at a certain point in a project...
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... AACSB: Communications AICPA BB: Industry AICPA FN: Decision Making Difficulty: Easy Learning Objective: C1 2. The time period principle assumes that an organization's activities can be divided into specific time periods. TRUE AACSB: Communications AICPA BB: Industry AICPA FN: Decision Making Difficulty: Easy Learning Objective: C1 3. Interim statements report a company's business activities for a 1-year period. FALSE AACSB: Communications AICPA BB: Industry AICPA FN: Decision Making Difficulty: Medium Learning Objective: C1 4. A fiscal year refers to an organization's accounting period that spans twelve consecutive months or 52 weeks. TRUE AACSB: Communications AICPA BB: Industry AICPA FN: Decision Making Difficulty: Medium Learning Objective: C1 5. Adjusting entries are made after the preparation of financial statements. FALSE AACSB: Communications AICPA BB: Industry AICPA FN: Decision Making Difficulty: Easy Learning Objective: C2 6. Adjusting entries result in a better matching of revenues and expenses for the period. TRUE AACSB: Communications AICPA BB: Industry AICPA FN: Decision Making Difficulty: Easy Learning Objective: C2 7. Two main accounting principles used in accrual accounting are matching and full closure. FALSE AACSB: Communications AICPA BB: Industry AICPA FN: Decision Making Difficulty: Easy Learning Objective: C2 8. Adjusting...
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...Business Performance Measurement At the Crossroads of Strategy, Decision-Making, Learning and Information Visualization February 2003 Vince Kellen CIO & Faculty,School of CTI DePaul University Chicago, IL U.S.A. http://www.depaul.edu Abstract Business Performance Measurement (BPM) systems have grown in use and popularity over the past twenty years. Firms adopt BPM systems for a variety of reasons, but chiefly to improve control over the firm in ways that traditional accounting systems have not allowed. Several approaches, or frameworks, for building and managing BPM systems have evolved with the balanced scorecard as the dominant framework in use today. Despite the growing use of BPM systems in organizations of all kinds, significant problems cause firms to experience difficulty in implementing BPM systems. The problems range across a variety of topics: excessive diversity in the field of study, data quality and information system integration problems, lack of linkage to strategy, fundamental differences in how a strategy is formulated and executed in the firm, ill-defined metrics identification processes, high levels of change in BPM systems, analytical skills challenges, knowledge as a social and non-deterministic phenomenon, judgment and decision biases (from prospect theory literature) and organizational defenses that can undermine successful BPM systems use. To help address these problems, a set of critical...
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...particularly true as it relates to the cost of providing health care services (Eaton, 2006). At Mercy Medical Center, not unlike any other health care facility, the use of statistics is pervasive throughout the organization. First and foremost Mercy uses statistics to develop and maintain its financial imperatives (Minnis, 2008). Simply stated if actual cost of providing health care services exceeds the revenue generated the organization will have difficulty keeping its doors open. This paper will discuss examples of descriptive and inferential statistics in use at Mercy Medical Center. Also discussed will be how data at nominal, ordinal, interval, and ratio levels of measurement are used within the organization. Finally, the advantages of accurate interpretation of statistical data and improved decision making within the organization will be discussed. Descriptive Statistics An example of a descriptive statistic used at Mercy Medical Center is time spent by the Emergency Department on yellow alert status. Yellow alert is defined by the Maryland Institute for Emergency Medical Services Systems (2012) as ambulance diversion from a designated emergency department that is unable to effectively manage additional patient volume at that time. Several years ago it became an organizational imperative to minimize and indeed eliminate barriers for patients accessing health care services provided by Mercy Medical Center. Yellow alert creates a barrier to accessing health services...
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...Kaplan University Graduate School of Management SELF DIRECTED LEARNING PLAN Your Name: Tiaira Walls Date: October 21, 2013 Course Title: GB519 Measurement and Decision Making Professional Goal (2-3 years) from now: My professional goal two to three years from now is to graduate with my Master’s degree in Human Resources and hopefully obtain a entry level position in Human Resources or management. Strengths to Leverage Step 1: The most effective and satisfied people align their work with their natural strong points. Identify 3-5 of your key strengths (see Column 1 below); these could be a competency, skill, ability, knowledge area or personal characteristic. Think about how you can leverage those strengths to be effective in your work, achieve your professional goals, and become a leader in your profession. Step 2: At the beginning of each course in your MBA program, answer the following question either using this template or a narrative format. What do you expect to learn in this course that will help you leverage your strengths? (See Column 2 below). Be as specific as you can, e.g., assume that strength is your analytical ability. You might expect to understand more about macroeconomics so that you can analyze how the housing crisis affects other segments of the economy, such as interest rates or unemployment. At the beginning of the course you are not expected to be an expert in all facets of the course learning; however, you can...
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...Statistics in Business Debbie Masterson University of Phoenix Statistics for Decision Making QNT/275 Charlene Dunfee December 13, 2014 Statistics in Business In today’s very competitive and global economic climate, it is ever more important for businesses to have reliable data to predict and plan. Definition of Statistics and Role in Decision-Making Statistics are the collection, presentation and interpretation of data. Statistics is a branch of mathematics and is a mathematical analysis of data or observations. Statistics also provide tools to predict and forecast based on the data collected and is applicable to not only businesses but to science, health and government (Stine & Foster, 2014). The use of statistics will help businesses and individuals make decisions by reducing the amount of guesswork and uncertainty of making decisions with no data to support them. Statistics provide unbiased data and evidence, lending a level of confidence to the leaders and employees that their decisions are reasonable and sound. Types and Levels of Statistics The types of data are qualitative, or non-numeric, and quantitative, or numeric (Stine & Foster, 2014). This data are often termed categorical and are also individual and variable such as the hair color of the people I work with. An example of qualitative data is answers to a survey of customer service of poor, fair, good, better, best. I can frequent the same eating establishment and order the same meal multiple...
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...describing data sets and drawing conclusions based on sampling about the data sets (McClave, Benson & Sincich, 2011). Statistics are divided into two areas: descriptive statistics and inferential statistics. Descriptive statistics are procedures used to describe and organize the basic characteristics of the data studied. Descriptive statistics provide simple summaries about the sample group and the measures. This application of statistics is used to present quantitative data in manageable forms such as charts, graphs, or averages. Descriptive statistics differ from inferential statistics in that they are simply describing what the data indicates. Inferential statistics are used to draw conclusions, interpret data, and make predictions or decisions beyond the immediate data. Inferential statistics are used to infer from the sample population data what a larger population may think or to predict future behaviors. Therefore, inferential statistics are used to make inferences from a sample data to draw conclusions pertaining to broader, general conditions whereas descriptive statistics merely describe the data. The two basic types of variables are quantitative and qualitative. Quantitative variables are divided into two types: 1) discrete variables, which assume certain values and the gaps between those values, and 2) continuous variables,...
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