Neater interview notes (not in a chronological order‚ bits missing‚ please edit =D ) Gerry Rayner Secondary/Tertiary study -Found transition from secondary to tertiary education “abysmal”. Started BSc but dropped out after 1 year. -Worked in telecommunications for several years but got sick of it‚ returned to study Science as a mature aged student. -Completed BSc (honours) in early 1990’s as mature aged student. Had large time gap between completing Honours and PhD (in this gap he worked
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used each presented each day (random set each day). Procedural: 2 tapping sequences learned per day. Different sequences each day. Statistical approach If 2 groups t-test between each group‚ for significant difference 4 groups ANOVA test- Analysis of Variance 2-way‚ x2 F-Test within groups -parametric‚ more
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Effectivity of Green Finger Pepper and Ethanol as an Alternative Insecticide A research project (to be) presented to the faculty of Cordillera Regional Science High School in partial fulfillment of the course Ib Cordillera Regional Science High School Wangal‚ La Trinidad‚ Benguet Bonnie B. Macay Danielle Dawayen Casserine Dumpilo Researchers Mrs. Xylene Grail Kinomis Research Adviser 2013 CHAPTER I INTRODUCTION Background of the Study Black ants are one of the common insects
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pains‚ and pains caused by arthritis and even hangover using Pandan (Pandanus Amryllifolius) | Central Problem | Sub-Problems | There will be no side effects or suspicios things/results that will occur when we do the experiment. | One-away analysis of variance (ANOVA) or F-test | | | This study aims to reduce pains or diseases in the Philippines through inventing a medicine or cure made out of pandan. It also aims to see the results of the tests and to know the different kinds of side effects
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estimation‚ review testing procedures and increase channels for effective communication. I should have set up a two-way ANOVA with a schedule variance as factor A and number of defects as factor B which I then would have been able to conclude that there was a difference in the means due to a schedule variance‚ number of defects‚ and the interaction of schedule variance and number of defects. With ANOVA‚ you have a more flexible as well as a more powerful technique that can be applied to more complex research
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18 2 Reliability 22 3 Exploratory factor analysis 24 4
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EXPERIMENTAL PSYCHOLOGY SEMESTER V ISA II A REVIEW OF EXPERIMENTAL DESIGNS IN PSYCHOLOGY Page | 2 INDEX Sr. No. Content Page No. 1 Introduction : Research Designs 4 2 Uses and Importance of Research Designs 4 3 Types of Research Designs 6 4 Exemplifying Research Problem into Research 15 5 Conclusion 18 6 References 19 Page | 3 INTRODUCTION: Research Designs - Its Uses and Importance The design is the structure
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SPSS Basics for One-way ANOVA As an illustration of the process‚ consider the data given in Example 11-8‚ pp. 593 – 595‚ of Bluman’s Elementary Statistics: A Brief Version. Problem Statement: A researcher wishes to try three different techniques to lower the blood pressure of individuals diagnosed with high blood pressure. The subjects are randomly assigned to three groups; the first group takes medication‚ the second group exercises‚ and the third group follows a special diet. After four weeks
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BM0421 Business Research Analysis Student Name: Qiumi Lv Student Number: W14006495 Word Count: 3112 Contents 1. Part 1 (a)………………………………………………………………….........….…...2 2. Part 1 (b)…………………………………………………………………………..…....2 3. Part 1 (c)………………………………………………………………………………...3 1. The Research Method and Questionnaire………………………………..….....3 2. The design decisions……………………………………………………………...3 4. Part 2……………………………………………….……………………………….......5 1. (i)..………………………………………………………………………….….....….5 2. (ii).…………………………………………………………………………
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father of “Modern Portfolio theory”‚ developed the mean-variance analysis‚ which focuses on creating portfolios of assets that minimizes the variance of returns i.e. risk‚ given a level of desired return‚ or maximizes the returns given a level of risk tolerance. This theory aids the process of portfolio construction by providing a quantitative take on it. It integrates the field of quantitative analysis with portfolio management. Mean variance analysis has found wide applications both inside and outside
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