'Minimum maximum' diaporamas de présentation

Post 16 Learning Aims in the School Census

Post 16 Learning Aims in the School Census. Objectives. DfE Specification School Census Autumn 2013 Revision of Key Post 16 Data Issues Links with Exams Organiser Dealing with QANs Checking Post 16 Data Autumn 2014 Heads Up Training Opportunities. DfE Specification.

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LEARNING OBJECTIVES

LEARNING OBJECTIVES . To learn the common secondary storage devices and their basic characteristics. To learn the common input devices and their basic characteristics. To learn the common output devices and their basic characteristics.

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Descriptive Statistics: Numerical Measures Exploratory Data Analysis

Descriptive Statistics: Numerical Measures Exploratory Data Analysis. Chapter 3 BA 201. Exploratory Analysis. Five-Number Summary. 1. Smallest Value. 2. First Quartile. 3. Median. 4. Third Quartile. 5. Largest Value. Five-Number Summary. Apartment Rents. Lowest Value = 425.

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Applications of Derivatives

Applications of Derivatives. Section 4.1 Section 5.2. Applications of Derivatives. Derivatives allow you to sketch the shape of functions. Applications of Derivatives. Ex: Amount of cargo unloaded at a port related to the number of trucks. Applications of Derivatives.

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Grade Center

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HOME PROGRAM BASICS

HOME PROGRAM BASICS. www.hud.gov/homeprogram/ Kathleen M. Bialas OGC/HHQ/HUD . HISTORY AND GOALS. Housing block grant program created by the Cranston-Gonzalez National Affordable Housing Act of 1990 FY 2007 appropriation -- $1.73 billion. ALLOCATION OF FUNDS.

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Unit Two - Words 11 - 20 Grade Six

groundless hypocrite incomprehensible manipulate maximum mimic ruffle serene sheepish stamina. More Context Clues. Definition. Context Clues. Synonyms. Definition . Antonyms. Unit Two - Words 11 - 20 Grade Six .

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Overview and Goals

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Regional Processing

Regional Processing. There goes the neighborhood. Rank Filtering. Rank filtering is a nonlinear process that is based on a statistical analysis of neighborhood samples.

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Blackboard 9.1

Blackboard 9.1. Designer & Developer Orientation. The Grade Center. Introduction

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Median/Order Statistics Algorithms

Median/Order Statistics Algorithms. Minimum and Maximum Selection in expected linear time Selection in worst-case linear time. Minimum and Maximum. How many comparisons are sufficient to find minimum/maximum? How many comparisons are sufficient to find both minimum AND maximum?

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3.4 Linear Programming

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Non-linear Filters

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The Historical Paper

The Historical Paper. Please note that the Historical Paper category is only open to individuals, not groups. Creating the Historical Paper. The Historical Paper should begin with an introduction stating the thesis of the work.

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Notes # ___ 6.1 & 6.2 Graphing Quadratic Functions

Notes # ___ 6.1 & 6.2 Graphing Quadratic Functions. Properties of Quadratic Graphs. The graph of a quadratic function is a parabola . Parabolas are SYMMETRIC. 6 Characteristics of Parabolas. axis of symmetry vertex y-intercept symmetric point Direction of opening

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Sampling Variability

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83 = 66% 94 = 75%

83 = 66% 94 = 75%. Descriptives Exam1 N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound .00 225 84.4389 17.69338 1.17956 82.1144 86.7633 40.00 125.00 1.00 538 93.2598 17.70926 .76350 91.7599 94.7596 40.00 125.00

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