c. ratio scale d. interval scale 2. Data obtained from a nominal scale a. must be alphabetic b. can be either numeric or nonnumeric c. must be numeric d. must rank order the data 3. In a post office‚ the mailboxes are numbered from 1 to 4‚500. These numbers represent a. qualitative data b. quantitative data c. either qualitative or quantitative data d. since the numbers are sequential‚ the data is quantitative 4. A tabular summary of a set of data showing the fraction of the total number
Free Random variable Standard deviation
Genmo Corporation Balance Sheet As of December 31‚ 1992 As of December 31‚ 1993 ASSETS Current Assets Cash 18 Account Receivable 214 273 Marketable Sec 494 Prepaid expenses 728 1533 Inventories 972 872 Total Current Assets 2426 2678 Investments 898 898 Real estate‚ plant and equipment 4727 4727 Less: Accumulated Dep 2433 2294 2711 2016 Special Tools
Premium Generally Accepted Accounting Principles Balance sheet Revenue
Lab – Data Analysis and Data Modeling in Visio Overview In this lab‚ we will learn to draw with Microsoft Visio the ERD’s we created in class. Learning Objectives Upon completion of this learning unit you should be able to: ▪ Understand the concept of data modeling ▪ Develop business rules ▪ Develop and apply good data naming conventions ▪ Construct simple data models using Entity Relationship Diagrams (ERDs) ▪ Develop entity relationships and define
Premium Entity-relationship model
business‚ but he is debating whether to start a S corporation or a C corporation due to potential environmental factors associated with his business. He wants to maintain a limited liability and wants to avoid double taxation by paying himself a salary equal to his companies before tax earnings. He also would like to issue preferred stock to his son in the future to keep his interests in the business. He was advised by his friend to choose a C Corporation to maintain maximum flexibility in the business
Premium Corporation Business Limited liability company
for Multinational Enterprise: A Philosophical Overview Part One: Review Question #1 Multinational Corporations have always been and are currently now under harsh criticism. They are mainly condemned for exploiting resources and workers of third world countries‚ taking jobs away from the US industry‚ and destroying local cultures. Although there are negatives of multinational corporations‚ there are also positives. Business done overseas provides jobs for the people of the host country‚ improving
Premium Corporation Multinational corporation Human rights
Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific
Premium Data warehouse
Big Data‚ Data Mining and Business Intelligence Techniques 2 What is Data? • Data is information in a form suitable for use with a computer. • There are two types of data ▫ Structured ▫ Unstructured • The total volume of data is growing 59% every year. • The number of files grow at 88% every year. 3 What is Big Data? Exa Analytics on Big Data at Rest Up to 10‚000 Times larger Peta Data Scale Giga Data at Rest Tera Data Scale Mega Traditional Data Warehouse
Premium Data analysis Business intelligence Data
assumptions are made based on judgment Methodologies This case study analysis is based on secondary data. The data analysis was conducted using following procedure: * Qualitative Analysis Industry analysis is conducted through porter’s five forces model and company analysis through SWOT analysis‚ country risk analysis through ICRG model. * Quantitative analysis The data are analyzed using simple tools like ratio analysis‚ free cash flow to firm
Premium Takeover Stock market Weighted average cost of capital
Data Anomalies Normalization is the process of splitting relations into well-structured relations that allow users to inset‚ delete‚ and update tuples without introducing database inconsistencies. Without normalization many problems can occur when trying to load an integrated conceptual model into the DBMS. These problems arise from relations that are generated directly from user views are called anomalies. There are three types of anomalies: update‚ deletion and insertion anomalies. An update anomaly
Premium Relation Relational model Database normalization
Data collection is any process of preparing and collecting data‚ for example‚ as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record‚ to make decisions about important issues‚ or to pass information on to others. Data are primarily collected to provide information regarding a specific topic. Data collection usually takes place early on in an improvement project‚ and is often formalized through a data collection plan which often
Premium Scientific method Qualitative research Sampling