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    independently in statistics‚ discrete geometry‚ political science and optimization. The motivation and the necessity in statistics to generalize the median and the rank is very natural‚ as the mean is not considered to be a robust measure of central location. It is enough to place one outlier to change the mean. In contrast‚ the median in one dimension is very robust as half of the observations need to be changed to corrupt the value of the median. In nonparametric statistics‚ several data depth

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    characteristic of statistics. ANSWER 1 Various characteristics of statistics as summarized as under : 1. Statistics deals with an aggregate of facts. A single figure cannot be analyzed. 2. Statistics gets affected to a great extent by multiplicity of causes The Statistics of the yield of a crop is the result of several factors‚ such as the fertility of soil‚ amount of rainfall‚ the quality of seed used‚ the quality and quantity of fertilizer used. 3. Statistics are numerically expressed

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    in more than one treatment. Note that I’m using the word "treatment" to refer to levels of the independent variable‚ rather than "group". It’s probably always better to use the word "treatment"‚ as opposed to group. The term "group" can be very misleading when you are using a within-subjects design because the same "group" of people is often in more than one treatment. As an example of a within-subjects design‚ let’s say that we are interested in the effect of different types of exercise on memory

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    aggregates

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    to use statistics in your research This chapter explains the importance of statistics‚ and why you need to use statistics to analyse your data. What is statistics? Put simply‚ statistics is a range of procedures for gathering‚ organising‚ analysing and presenting quantitative data. ‘Data’ is the term for facts that have been obtained and subsequently recorded‚ and‚ for statisticians‚ ‘data’ usually refers to quantitative data that are numbers. Essentially therefore‚ statistics is a scientific

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    University of Perpetual Help System Dalta Molino Campus Molino III‚ Bacoor City Probability and Statistics LAGERA‚ Einar John A. Table of Contents Simple Correlation Analysis ................................................................................................. 1 Introduction .................................................................................................................................................................. 1 What is Correlation? ...........

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    without missing responses ..................................................................... 7 Section 2: Frequencies without descriptive & with missing responses ...................................... 8 Section 3: Frequencies with descriptive statistics ...................................................................... 9 Ordinal data ............................................................................................................................. 9 Interval/Ratio data ..........

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    Lin21477_ch01_001-020.qxd 8/26/11 2:10 PM Page 1 What Is Statistics? 1 Learning Objectives Goals When you have completed this chapter‚ you will be able to: LO 1-1 List ways that 1 Organize data into a frequency distribution. statistics is used. FPO LO 1-2 Know the differences 2 Portray a frequency distribution in a histogram‚ frequency between descriptive and polygon‚ and cumulative freinferential statistics. quency polygon. LO 1-3 Understand the differ3 Present data a

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    CHAPTER ONE 1.0 INTRODUCTION The students industrial work experience (SIWES) is a skill training program designed to expose and prepare students of higher institution for the working environment they are likely to meet after graduation. SIWES was established by industrial training fund (ITF) in 1973 to solve the problem of lack of adequate practical skills‚ in preparation for employment in industries by Nigeria graduates. The SIWES program runs in the Nigeria universities in conjunction

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    California State University‚ Sacramento Serge Lee‚ Ph.D. Division of Social Work Mariposa Hall‚ 4025 leesc@csus.edu A Quick Guide to SPSS Windows[1] Introduction SPSS for Windows provides a powerful statistical analysis and data management system in a graphical environment‚ using descriptive menus and simple dialog boxes to do most of the work for you. Most tasks can be accomplished simply by pointing and clicking the mouse. In addition to the simple point-and-click

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     [pic]‚ or [pic]. The hypothesis that Σmodel = Σresidual implies that the product A∼I[2] . Invariance considerations imply the MANOVA statistic should be a measure of magnitude of the singular value decomposition of this matrix product‚ but there is no unique choice owing to the multi-dimensional nature of the alternative hypothesis. The most common[3][4] statistics are summaries based on the roots (or eigenvalues) λp of the A matrix: ▪ Samuel Stanley Wilks ’ |ΛWilks =|∏ |(1 / (1 + λp))|

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