'Sample data set' presentation slideshows

Week 1 September 1-5

Week 1 September 1-5. Six Mini-Lectures QMM 510 Fall 2014. Getting Started ML 1.1. Chapter 0. self-introductions (Moodle mini-biographies) course format, syllabus, projects grading, communication goals: short run vs long run.

1.06k views • 93 slides

Probabilistic Forecast Distribution Verification Primer Kevin Werner Dave Brandon Steve Shumate

Probabilistic Forecast Distribution Verification Primer Kevin Werner Dave Brandon Steve Shumate Colorado Basin River Forecast Center Salt Lake City, UT. Version 2.1 October 9, 2003. What is a Probabilistic Forecast?.

847 views • 72 slides

Descriptive Statistics

730 views • 55 slides

CHAPTER 3

CHAPTER 3. NUMERICAL DESCRIPTIVE MEASURES. MEASURES OF CENTRAL TENDENCY FOR UNGROUPED DATA. In Chapter 2, we used tables and graphs to summarize a data set. In Chapter 3, we will estimate numerical summary measures to identify important features of a distribution.

514 views • 51 slides

SPSS 2: Central Tendency and Dispersion

SPSS 2: Central Tendency and Dispersion. Frequency Distribution

547 views • 45 slides

Decision trees

439 views • 39 slides

Laboratory in Oceanography: Data and Methods

Laboratory in Oceanography: Data and Methods. Intro to the Statistics Toolbox. MAR599, Spring 2009 Miles A. Sundermeyer. Intro to Statistics Toolbox Statistics Toolbox/Descriptive Statistics. Measures of Central Tendency Geometric Mean: Harmonic Mean:. Intro to Statistics Toolbox

450 views • 32 slides

If n =11 then median is the sixth observation

The median of a given data set is the value which divides the ordered set of values into two equal parts such that the number of values equal to or greater than the median is equal to the number of values less than or equal the median.

325 views • 32 slides

How do you know?: Interpreting and Analyzing Data

How do you know?: Interpreting and Analyzing Data. NCLC 203 New Century College, George Mason University April 6, 2010. We shall not cease from exploration And the end of all our exploring Will be to arrive where we started And know the place for the first time - T.S. Eliot.

452 views • 30 slides

Google Maps Engine Lite (Beta)

Google Maps Engine Lite (Beta). mapsengine.google.com/map?. Login to Google and Create!. mapsengine.google.com. Start with a blank map. Click to edit. Type city, state. Zoom to street level. Import data.

391 views • 23 slides

2.4: measures of variation

354 views • 21 slides

Numerical Descriptive Measures

Numerical Descriptive Measures. Chapter 3. Group data Vs. Ungrouped data.

250 views • 21 slides

2.4 Measures of Variation

279 views • 14 slides

Paul Jen-Hwa Hua, Chih-Ping Wei, Tsang-Hsiang Cheng, Jian-Xun Chen,

Predicting adequacy of vancomycin regimens: A learning-based classification approach to improving clinical decision making. Paul Jen-Hwa Hua, Chih-Ping Wei, Tsang-Hsiang Cheng, Jian-Xun Chen, Decision Support Systems, 2006. (article in press) . Presenter : Wei-Shen Tai

146 views • 14 slides

STAT 110 - Section 5 Lecture 13

STAT 110 - Section 5 Lecture 13. Professor Hao Wang University of South Carolina Spring 2012. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A. Last time. Categorical and quantitative variables

215 views • 12 slides

An Overview of Statistics

An Overview of Statistics. NOTES Coach Bridges. What you should learn:. The definition of data and statistics How to distinguish between a population and a sample How to distinguish between a parameter and statistic

189 views • 8 slides

Enzyme Catalysis with Catalase

Enzyme Catalysis with Catalase. Key Notes From Lab Handout. Enzyme: Catalase (from beef liver) Substrate: H 2 O 2 (hydrogen peroxide) Stop Reaction: use sulfuric acid (H 2 SO 4 ) Quantify Amt. of H 2 O 2 left: titrate in KMnO 4 (potassium permanganate)

249 views • 7 slides