...Uses of Statistical Information Darryl Lowery Statistical Applications/HCS438 February 28, 2012 Julieanne Hessler, RN MSN, MBA Introduction Statistics are used in every phase in the delivery of health care. This is 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...
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...Project Proposal Statistical Learning and Data Mining Overview: Efficient asset allocation through statistical learning methods and comparison of methods for the creation of an index tracking ETF (Exchange traded fund) Datasets: The datasets are chosen from the website of the book “Statistics and Data Analysis for Financial Engineering” by David Ruppert. The book is mentioned as one of the references for this course. The two data sets chosen are 1. Stock_FX_Bond.csv 2. Stock_FX_Bond_2004_to_2006.csv The data includes the volumes and adjusted closing prices for GM, F, UTX, CAT, MRK, PFE, MSFT, IBM, C and XOM. The data also contains the volumes and adjusted closing prices for the S&P 500 index. The data set also includes treasury rates for different maturities and rates on corporate bonds as well as foreign exchange rates for the period of 1987 to 2006. Objectives: 1. Optimal portfolios for various levels of Risk. Conventional investors look to attain maximum alpha values (rates of return) at levels of risk they are comfortable with. We can hence at any level of risk, define portfolios that generate maximal returns. In this project, we aim to identify the composition of portfolios that achieves this desired objective. Existing models such as CAPM, along with additional forms of regression will be used to compare with additional methods, not covered in the duration of the class to identify the better methods of portfolio creation. We will use learning tools...
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...TermPaperWarehouse.com - Free Term Papers, Essays and Research Documents The Research Paper Factory Join Search Browse Saved Papers Home Page » Other Topics Uses of Statistical Data In: Other Topics Uses of Statistical Data Uses of Statistical Information Darryl Lowery Statistical Applications/HCS438 February 28, 2012 Julieanne Hessler, RN MSN, MBA Introduction Statistics are used in every phase in the delivery of health care. This is 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...
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...Final Project: Statistics II Descriptive analysis of statistical data INTRODUCTION There have always been crimes, from a treachery to an assassination. Happens in every country you can think of, and every government has to deal with it. It is really stressful to try to understand the nature of the crimes: why are they done and where could they happen next. Out of this preoccupation is that we found studies gathering data from communities; we focused on one specific crime: murders. In several communities, it is thought that the murder rate is somehow related to several factors. For instance, it is common to hear that the murder rate depends on poverty and unemployment. Starting from this hypothesis, the database found to make this analysis relates the number of murders per year per 1,000,000 inhabitants with the number of inhabitants, the percentage of families’ incomes below $5000, and the percentage unemployed. OBJECTIVE OF THE STUDY Trying to estimate how many murders will happen in a year in a specific place is difficult, but not impossible. This is why we are using the dataset found with the variables mentioned above, with which we’ll be able to find a formula. So, after this project, if we want to know how many murders will be on a city, for example Monterrey, we’d just plug in the data from that city (the inhabitants, the percentage of families income below $5000, and the percentage unemployed) and we’ll get a number, which would be the predicted number of murders...
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...Evaluation of Statistical Data from Oxford Cereals Thwarting Claims of Consumers Concerned About Cereal Cheaters (CCACC) In the previous correspondence to your office dated April 27, 2014, analysis of data was presented to you showing that Consumers Concerned About Cereal Cheaters (CCACC) misrepresented the Oxford Cereals packaged weights for two (2) of their cereals, Oxford O’s and Alpine Granola Frosted Flakes. I have received further statistical data from Oxford Cereals in support of its claims that CCACC has indeed misrepresented their company related to the packaged weights. This additional statistical data was analyzed and these findings will be outlined for your further review. The following statistical data was conclusive in determining that the claim of Oxford Cereals cheating their customers was not true. There is no definitive proof that the claims of boxed weights being short of 368 grams are true. New information Ted Grable, CEO of Oxford Cereals visited Oxford Cereal Plant Number 1 with several members of the public, several off-duty firefighters and police officers, and a television reporter, Sharon Danyl. A random day was chosen by Ms. Danyl and the firefighters and police officers randomly collected 40 boxes from each of the cereal’s production lines, collecting a total of 80 boxes of cereal. The 80 boxes of cereal were then boxed and transported to an independent laboratory by agents from Parcel Express Delivery Systems. The boxes were weighed and...
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...Data Collection Instrument The instrument used for data collection for Ballard Integrated Managed Services, Inc. was a formal survey to document complaints, opinions, and suggestions from each employee. Due to the decrease in morale and low productivity rate the survey instrument was used to collect statistical information from each BIMS employee to summarize and analyze data collected to finalize a result. The survey was created to provide BIMS employees’ an opportunity to share their experiences working with BIMS. Level of measurement There are a few types of measurement levels involved in this study which is the nominal scales, ordinal scales, and interval scales. BIMS used ordinal level of management, which has no numerical value and it is to document the level of satisfaction, happiness, and discomfort (Market Research Methods, 2012). Another level of measurement BIMS used in the study was nominal level which is considered names and label variables that include questions that have no numeric value (Market Research Methods, 2012). Data Clean In order for BIMS to develop exact results; performing a data sweep to remove any input errors is helpful. The office support staff member in charge reported a few errors such as any missing data was represented with a zero, which meant according to the report there were questions that people failed to answer. It is also important to remove the number of times a ‘6’ is typed when it should be ‘5’...
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...presenting, and interpreting data (McClave, Benson, & Sincich, 2011). Four scales of measurement are available for obtaining data on a exacting variable: nominal, ordinal, interval, and ratio (Lind, Marchal, & Wathen, 2011). The scale of measurement for a variable is nominal when the data are labels or names used to identify an attribute of an element (McClave, Benson, & Sincich, 2011). The scale is ordinal if the data have the properties of nominal data the order or rank of the data is meaningful. The scale is interval if the data have the properties of ordinal data the interval between observations is expressed in terms of fixed unit of measure (Lind, Marchal, & Wathen, 2011). Finally, the scale of measurement is ratio if the data have all the properties of interval data and the ratio of two values is meaningful. For propose of statistical analysis, data can be classified as qualitative or quantitative (Lind, Marchal, & Wathen, 2011). Qualitative data are labels or names used to identify an attribute of each element. Qualitative use either the nominal or ordinal scale of measurement and may be non-numeric or numeric. Quantitative data are numeric values that indicate how much or how many. Quantitative data use either the interval or ratios scales of measurement (Lind, Marchal, & Wathen, 2011). Ordinary arithmetic operations are meaningful only if the data are quantitative. Therefore, statistical commutations used for quantitative data are not always appropriate...
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...ORG An Efficient Connection between Statistical Software and Database Management System Sunghae Jun Department of Statistics, Cheongju University Chungbuk 360-764 Korea ABSTRACT In big data era, we need to manipulate and analyze the big data. For the first step of big data manipulation, we can consider traditional database management system. To discover novel knowledge from the big data environment, we should analyze the big data. Many statistical methods have been applied to big data analysis, and most works of statistical analysis are dependent on diverse statistical software such as SAS, SPSS, or R project. In addition, a considerable portion of big data is stored in diverse database systems. But, the data types of general statistical software are different from the database systems such as Oracle, or MySQL. So, many approaches to connect statistical software to database management system (DBMS) were introduced. In this paper, we study on an efficient connection between the statistical software and DBMS. To show our performance, we carry out a case study using real application. Keywords Statistical software, Database management system, Big data analysis, Database connection, MySQL, R project. 1. INTRODUCTION Every day, huge data are created from diverse fields, and stored in computer systems. These big data are extremely large and complex [1]. So, it is very difficult to manage and analyze them. But, big data analysis is important issue in many...
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...Analysis of data Qualitative data Data is a subjective description in words which varies depending on who is recording it (it is open to interpretation) such as a description of housing quality * In its simplest form this could be an analysis of some graphs. This is quick, visual and shows the obvious anomalies. * One of the simplest approaches to qualitative analysis is to see if two variables are related by using a scatter graph. A line of best fit will show the correlation between the two as either a positive or negative correlation. If there is no correlation then the two variables aren’t linked. Quantitative data Statistical data which consists of numbers. It is objective and should be value free. * When there is no clear trend or link between two sets of data the analysis of data can be taken into further detail with statistical analysis. They can identify trends, groups and anomalies as well as predictions from larger sets of data that is too complex to be analysed by using qualitative analysis. Statistical analysis is useful as it shows whether a relationship really exists as well as the strength of the relationship. It can also simplify large sets of data into a single result that can give a measure of its level of accuracy and reliability. A few things to think about when doing statistical analysis: * Keep it simple- don’t do statistical analysis for the sake of it and start off with simple methods of analysis as often the result is clear without...
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...KNBS DATA DISSEMINATION AND ACCESS POLICY November 2012 VISION A centre of excellence in statistics production and management MISSION To effectively manage and coordinate the entire national statistical system to enhance statistical production and utilization Herufi House, Lt. Tumbo lane P.O. Box 30266 – 00100 GPO Nairobi, Kenya Tel: +254-20-317583/86/88,317612/22/23/51 Fax: +254 – 20-315977 Email: info@knbs.or.ke Web: www.knbs.or.ke i WI-83-1-1 Preface Kenya National Bureau of Statistics (KNBS) is the principal agency of the Government for collecting, analysing and disseminating statistical data in Kenya. KNBS is the custodian of official statistical information and is mandated to coordinate all statistical activities, and the National Statistical System (NSS) in the country. Official statistics are data produced and disseminated within the scope of the Statistical Programme of the National Statistical System (NSS) in compliance with international standards. To achieve this mandate, KNBS strives to live up to the aspirations of its vision; to be a centre of excellence in statistics production and management. Chapter Four on The Bill of Rights section 35 of the new constitution in Kenya gives every citizen right of access to information held by the State. This policy document strives to provide a framework for availing statistical information to the public in conformity with this bill and government’s open data initiative. This...
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...Statistics Assignments Assignment-W13 Question 1 Statistical data analysis involves the application of various statistical methods in analyzing and deriving inferences from data. Mainly, statistical methods are useful for communicating the research findings and supporting the research hypotheses. Consequently, the methods and analyses ensure that the research methodology and the conclusions of a research are credible. Concisely, the statistical data analysis helps to obtain usable and useful information from data. At a basic level, statistical methods help in describing and summarizing data, identifying variable relationships, comparing variables, identifying variable differences, and forecasting outcomes. In various business scenarios, statistical...
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...TECHNOLOGY. BACHELOR OF BUSINESS INFORMATION TECHNOLOGY ADM NO. 113/01479 SPSS REPORT INTERNAL INDUSTRIAL BASED LEARNING 1 PRESENTED TO: JULIUS NYERERE SPSS is a software package used for statistical analysis. The software name originally stood for Statistical Package for the Social Sciences (SPSS). SPSS is the acronym of Statistical Package for the Social Science.SPSS is one of the most popular statistical packages which can perform highly complex data manipulation and analysis with simple instructions. It is designed for both interactive and non-interactive uses. It is also used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations, data miners, and others. The original SPSS manual (Nie, Bent & Hull, 1970) has been described as one of "sociology's most influential books" for allowing ordinary researchers to do their own statistical analysis.[4] In addition to statistical analysis, data management (case selection, file reshaping, creating derived data) and data documentation (a metadata dictionary was stored in the data file) are features of the base software. Statistics included in the base software: * Descriptive statistics: Cross tabulation, Frequencies, Descriptive, Explore, Descriptive Ratio Statistics * Bivariate statistics: Means, t-test, ANOVA, Correlation (bivariate, partial, distances), Nonparametric tests...
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...Definition SPSS has scores of statistical and mathematical functions, scores statistical procedures, and a very flexible data handling capability. It can read data in almost any format (e.g., numeric, alphanumeric, binary, dollar, date, time formats), and version 6 onwards can read files created using spread sheet/data base software. It also has excellent data manipulation utilities. The following is a brief overview Benefit of spss Statistical analysis can be conducted using two main methods. One is simply by using a generalized spread sheet or data management program such as MS Excel or through using a specialized statistical package such as SPSS. Here are key reasons why SPSS is the best option to use. 1. Effective data management While it is spot on that a spread sheet program offers more control with regards to the data organization, this can also be seen as a demerit. In contrast, you cannot move data blocks in SPSS as it is meant for organizing data in an optimal manner. A row represents one case, whereas a column denotes one variable. SPSS makes data analysis quicker because the program knows the location of the cases and variables. When using a spreadsheet, users must manually define this relationship in every analysis. 2. Wide range of option SPSS is specifically made for analysing statistical data and thus it offers a great range of methods, graphs and charts. General programs may offer other procedures like invoicing and accounting forms, but specialized...
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... | |1/29/2011 | | | Identify the Problems Analysis of gathered data Medialogic Pakistan Ltd. is currently not analyzing the gathered data. Although at the current stage gathering first hand information is very useful for companies, but a lot further analysis can give more valuable insight for the channel operators. User profiles may be inaccurate For identification of different viewers is determined by different buttons. In many cases the operator of the remote is not watching a channel of his/her liking instead is changing the channels on someone else’s behalf. This may misinterpret the information gathered. According to the case there are a total of 4200 people’s data gathered by the company representing 10 million urban users. The sample size in comparison to the population size is far more stretched. Within this sample there is less room for such errors....
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...presentation of data. There are variety of different types of statistics, hard statistics are numerical data that can not be manipulated, soft statistics are numerical data that can be manipulated, official statistics are produced by formal institutions whilst unofficial are carried out by informal institutions. By definition, statistical data is quantative data which increases its reliability. Using Statistics in research has a variety of different advantages. This kind of research is cheap and easily accessible. Also, as not much time is spent on primary research, analysis will be fairly quick so the results are fairly up to date. The ready availability of official statistics mean the researcher does not have to spend time and money collecting his / her own information. Unlike in Qualitative research methods such as interviews that could possibly involve travelling costs. It may be the case that official statistics are the only available source for a piece of research. Durkheim, for example, in his study of in 1897 used official statistics drawn from coroners' reports from different societies to establish that suicide rates varied within societies. By doing this, he was able to argue that social factors, such as religious belief, were significant variables and influences in the explanation of why people committed suicide. For some topics, therefore, secondary research is the only way to find data that relates to your study. You cannot go back in time to collect data so you have...
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