Mastering Data Representations: A Comprehensive Guide for Students

Feb 28, 2025

40 likes | 107 Views

Explore various data representations and enhance your understanding through this comprehensive guide designed for students. This resource covers essential concepts and techniques to equip learners with the knowledge needed to analyze and interpret data effectively.

Share Presentation

Embed Code

lester

Download Presentation

Mastering Data Representations: A Comprehensive Guide for Students

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Data repesentaions Jakayla 6th period

Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Tan, Steinbach, Kumar (edited by S. Parthasarathy 3/2007). What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object

619 views • 42 slides

Data Mining: Data

What is Data?. Collection of data objects and their attributesAn attribute is a property or characteristic of an objectExamples: eye color of a person, temperature, etc.Attribute is also known as variable, field, characteristic, or featureA collection of attributes describe an objectObject is

1.05k views • 61 slides

Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 CSE 572 Data Mining Instructor: Jieping Ye Department of Computer Science and Engineering Arizona State University. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object

1.01k views • 67 slides

Data, Data Everywhere

Data, Data Everywhere. “Did you know” Video. Vendor Panel. Iowa Health System. Represented by Joy Grosser. Vendor SecurITy. Represented by John Hendricks. Dewey, Cheatem , and Howe. Represented by Tony Langenstein. Vendor Panel. Like taking candy from a baby. Iowa Health System.

358 views • 21 slides

Data, Data, and more Data

Agenda. Performance Measurement DefinedThe Logic Model

465 views • 33 slides

Data, Data, and more Data

Data, Data, and more Data. Paraeducator Recertification Presented by: Lisa Andreasen April 17, 2013. Purpose of Presentation . Why do we need so much data? What kinds of data are there? What is a paraeducators role in data collection? What’s okay and what’s not Collecting behavior data

901 views • 29 slides

Data Data Data

Data Data Data. R E A D I N G. Coaches Academy 2012-2013. BITE SIZE. BITE SIZE. Activity #1: District Heat Map Activity #2: Data Tool Activity #3: SE/Test Item Connection. District Heat Map. Here’s How It Works…. Work with your shoulder partner

369 views • 25 slides

Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Tan, Steinbach, Kumar. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object Examples: eye color of a person, temperature, etc.

1.11k views • 79 slides

Data ! Data! Data!

Data ! Data! Data! Find, Understand and Use Data to Develop Comprehensive School Counseling Programs. 2013-14 Fall RESA Training for School Counselors Linda H. Brannan NCDPI Consultant K-12 Student Support Services linda.brannan@dpi.nc.gov. School Counseling Wikispace.

1.85k views • 154 slides

Data, Data Everywhere….

Data, Data Everywhere…. September 8, 2011 The Coalition for Academic Scientific Computation José-Marie Griffiths, PhD Vice President for Academic Affairs Bryant University, Smithfield, Rhode Island. Concerns of Research Administrators.

548 views • 33 slides

Faster data – Better data – Cheaper data

Vision of the Future NATO codification system as the foundation for the eOTD, ISO 22745 and ISO 8000. “ What is impossible to do right now, but, if you could do it, would fundamentally change your business? ” 1990 Joel Arthur Barker Codification at source !

204 views • 2 slides

DATA? What DATA?

DATA? What DATA?. Valentine Community Schools April 3 , 2012. A little bit of history…. Valentine Community Schools is a relatively new district due to consolidation in 2006 Covers approximately 2,500 square miles Multiple rural attendance centers and three buildings in Valentine.

646 views • 51 slides

Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to PCA (Principal Component Analysis). What is PCA?. Stands for “Principal Component Analysis” Useful technique in many applications such as face recognition, image compression, finding patterns in data of high dimension

474 views • 15 slides

Data Mining: Data

Data Mining: Data. Lecture 3 TIES445 Data mining Nov-Dec 2007 Sami Äyrämö. Data quality. GIGO – Garbage In, Garbage Out Effectiveness of DM exercise depends on the quality of data Data quality concerns individual measurements (records and fields) collections of observations

231 views • 5 slides

Data Mining: Data

Data Mining: Data. Introduction to Data Mining by Tan, Steinbach, Kumar. What is Data?. Collection of data objects and their attributes An attribute is a property or characteristic of an object Examples: eye color of a person, temperature, etc.

1.18k views • 68 slides

Data Mining: Data

Data Mining: Data. Lecture Notes for Chapter 2 Introduction to Data Mining by Minqi Zhou. Precap –What’s Data Mining?. Many Definitions Non-trivial extraction of implicit, previously unknown and potentially useful information from data

1.13k views • 79 slides

Data Begets Data

Data Begets Data. The Multiplier Effect Government Accountability Office Montana Visit June 25, 2014 Prepared by the Montana State Library Geographic Information Program ( with a little help from our friends). Agenda. Introduction – Stu Kirkpatrick (1:00 p.m.)

215 views • 9 slides

Data, Data, Everywhere...

Data, Data, Everywhere. Jeff S. Holmes Motorola Fort Worth, TX. The Issues. Lots of In-Process Data Collected Defect Inspection Size Time Software Metrics Measurement Systems Inaccurate Cumbersome NOT ENGINEERED!. The Effects. Estimation Accuracy Schedules Staffing Quality

171 views • 4 slides

Data, Data, and More Data

Data, Data, and More Data. Kyle Roskoski. Data. This is a summary of what environmental data we have access to for the year 1998-2000 (Some data through 2003) Two people have been measuring and recording environmental data. Warren Heilman and Jaak Sober.

533 views • 27 slides

Data Mining: Data

524 views • 42 slides

Data Mining: Data

811 views • 68 slides

More Related