'Ordered data' diaporamas de présentation

Example :

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Revision Tips

Revision Tips. G. Check the side of the slide to see what level you are working at!. F. E. D. C. B. A. A*. WEBSITES. Website: www.mymaths.co.uk School and personal logins and passwords have been given out. Website: http://www.samlearning.com/ Centre Mk14SC2

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Data Summary Using Descriptive Measures

Data Summary Using Descriptive Measures. Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing. Types of Descriptive Measures. Central Tendency Variation Position Shape. Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur

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Visualizing Linguistic Data: From Principles to Toolkits for Doing it Yourself

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Textual Data; Visual Variables

Textual Data; Visual Variables. Administration. Sprechstunden T 14-15, Th 16-17 (on the web site) Online collaboration tools? e.g. wikis. Languages. What languages do people know, and to what extent? (Basic, Intermediate, Advanced) CuC: Advanced: English

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DESCRIPTIVE STATISTICS

DESCRIPTIVE STATISTICS. DESCRIPTIVE STATISTICS. Descriptive statistics are summary measures which define some important characteristics of data. Measures of location Measures of central tendency Measures of position Measures of dispersion (variation). Measure s of Location.

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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.

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STATISTICS

STATISTICS. Grade IX. Sutarman Indonesian International School Yangon. Release 1 2006. END. SUBTOPICS :. Table Frequency Aritmetic Mean Mode Median Quartile Data Representation. Consider the following case :.

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Data Mining Basics: Data

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N.D. Analysis We are NOT going to analyze N otre D ame, just N umerical ( Quantitative ) D ata.

N.D. Analysis We are NOT going to analyze N otre D ame, just N umerical ( Quantitative ) D ata. There are essentially two ways to represent and analyze quantitative data, visually computationally We already have seen the four main ways to represent numerical data visually.

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Measures of Location

Measures of Location. Prepared by: Josefina V. Almeda Professor and College Secretary School of Statistics University of the Philippines, Diliman August 2009. Learning Objectives. After the session, participants should be able to: To list and define the most common measures of location

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Parallel Overlap Assembly for the Construction Of Computational DNA Libraries

Parallel Overlap Assembly for the Construction Of Computational DNA Libraries. Presented by Nayeong Jeong. Introduction POA algorithm Example and application of POA Overlap size Conclusion. Introduction. What is POA ? P arallel O verlap A ssembly.

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Parallel Overlap Assembly for the Construction Of Computational DNA Libraries

Parallel Overlap Assembly for the Construction Of Computational DNA Libraries. Presented by Nayeong Jeong. Introduction POA algorithm Example and application of POA Overlap size Conclusion. Introduction. What is POA ? P arallel O verlap A ssembly.

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Statistics 3

Statistics 3. Project Maths Miss Cullen. How do I represent data. Remember... Categorical Data: Pie Charts and Bar Charts are used Numerical Data: Discrete: bar chart, pie chart, line plot, stem and leaf are used Continuous: histograms are used. What is a Stem and Leaf?.

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Sec. 2-7: Using Measures of Central Tendency

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MMMR VOCAB

MMMR VOCAB. Mean - the sum of the data divided by the number of data items. {the average} Median- the middle number in a set of ordered data. {*the set must be in order from least to greatest!} Mo de- the data item(s) that appears most often.

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