PPT-Summarizing Performance Data

Confidence Intervals Important Easy to Difficult Warning some mathematical content Contents Summarized data Confidence Intervals Independence Assumption Prediction Intervals Which Summarization to Use . Yu David Liu. State University of New York (SUNY). at Binghamton. FOAL 2015. Modular Performance Reasoning of. Data-Intensive Programs. Yu David Liu. State University of New York (SUNY). at Binghamton. Presenters: Emma Packard& Suzanne Fitzgerald. Tracking Student Progress. Data collection. Part 2. 1. 2. HOMEWORK. 3. 4. 5. 6. Data. Data. Data. Requested DATA SHEET Examples. 7. 8. 9. 10. 11. After completing this session, participants will. What’s the difference?. Quoting. When writing about something someone has already written, you may find that you want to copy something word for word.. If you copy word for word and do not put it in quotation marks and tell your reader where it’s from, you are plagiarizing. . Yu David Liu. State University of New York (SUNY). at Binghamton. FOAL 2015. Modular Performance Reasoning of. Data-Intensive Programs. Yu David Liu. State University of New York (SUNY). at Binghamton. Brought to you by. The Writing and Learning Centre. One of the challenges in . effective academic . writing is being able to transition from one idea to . another….. … or . from one argument to another in an essay. . Histograms. Similar to bar charts, but with quantitative data.. No gaps between bars.. Summarizes data visually using frequency count.. Data: Amount spent by 50 customers at a grocery store. 2.32 6.61 6.90 8.04 9.45 10.26 11.34 . Methods. Rcmdr. Features for loading, viewing and analyzing data. Help system. Packages. Data in R. Several formats: vectors, arrays, matrices, lists, . data.frames. Generally we use . data.frames. as they have the advantage of letting us store different kinds of data and linking them by row.. Chairs: Lee Anne . Caylor. (Business) & Chelsea . Orvella. (Labor) Staff: Dave . Pavelchek. (. dpavelchek@wtb.wa.gov. ) . DELIVERABLES. STATUS. OF WORK. MOMENTUM. TAP. Lead the creation of an implementation plan for Next Generation Performance Accountability initiatives outlined in . Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall. 3-. 1. Data Visualization. Data Queries: Using Sorting and Filtering. Statistical Methods for Summarizing Data. Exploring Data Using PivotTables. Sponsored by Cornell Statistical Consulting Unit. Instructors. Emily . Davenport (Cornell University). Erika . Mudrak (. CSCU. ). Lynn Johnson (CSCU). Assistants. Francoise . Vermeylen. Stephen Parry. 8. th. grade English teachers . Paraphrasing and Summarizing. We will run through this PowerPoint as a class today.. Stay with the rest of the class as well as you can.. You’ll need a piece of paper for a few important notes that you’ll take during this lesson.. Presenting. iRaise the Rates. Champions Training Program . MedConcert. Platform. CECity | ACP | QHC | Pfizer. Presentation and Discussion. Confidential – Not for Distribution. The Elephant in the Room: . 2. :. Variance and Standard Deviation. Sample variance. :. (Almost) the average of squared deviations from the sample mean.. Measures of Data Spread. data point . i. sample mean. there are . n. data points. Mayuresh . Kunjir. Modern Data Analytics Frameworks. Process external data. Great for unstructured data. Easy to scale out. Suited for Cloud infrastructure. Fast recovery. Suited for commodity nodes.