MATH 231-Biostatics.pdf - KENYA METHODIST UNIVERSITY Distance Learning Material MATH 231 BIOSTATISTICS by COURSE INSTRUCTOR Prof Peter A Kamau Tel 0721

MATH 231-Biostatics.pdf - KENYA METHODIST UNIVERSITY...

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1 KENYA METHODIST UNIVERSITY Distance Learning Material MATH 231 BIOSTATISTICS by COURSE INSTRUCTOR: Prof Peter A. Kamau Tel: 0721 847 866 © 2009 Published by Kenya Methodist University P.O. Box 267 60200, Meru Tel: 254 064 30301, 31146
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2 1. COURSE DESCRIPTION The course is a general overview of the hypothesis testing procedures 2. OBJECTIVES The aim of this course is to equip the students with the basic knowledge in Statistical procedures. Special emphasis will be given to the use of statistical packages (SPSS, SAS) in data analysis COURSE OUTLINE 1. Probability Distributions Discrete Probility Distributions n(Bionomial, Poisson) Normal Probability Distribution 2. Hypothesis; Definition Hypothesis Testing Procedures Hypothesis Testing for Proportions 3. Z - test 4. T - test One sample test Independent sample test Paired test Chi-Square test 5. Regression and Correlation Analysis Correlation Analysis Regression Analysis 6. F- test Analysis of Variance (ANOVA) 7. Assessment There will be two forms of assessments i Continuous Assessment Tests 30% (CAT) x 2 on times to be decided. ii End of Semester Examination. 70% NB: Late submission of assignments will result to deduction of marks.
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3 TABLE OF CONTENTS 1.0 INTRODUCTION 1 2.0 COLLECTION OF DATA 3 3.0 DATA ORGANIZING 7 4.0 MEASURES OF CENTRE & DISPERSION OF A DATA SET Measures of Centre of a Data 14 Measures of dispersion of a Data 18 Mean and Standard Deviation of a Grouped Data 21 Coefficient of Variation (CV) 27 Skewness 27 Standard Error 28 5.0 CORRELATION & REGRESSION ANALYSIS Correlation Coefficient (r) 29 Linear Regression 33 Coefficient of Determination 35 Standard Error of Estimate (SE) 35 Multiple and Partial Correlation 36 6.0 ELEMENTARY PROBABILITY Probability of an Event 39 Permutations and Combinations 41 Discrete Probability Distributions 44 Normal Distributions 50 Approximating a Binomial Distribution 61 8.0 REVISION EXERCISES 9.0 BIBLIOGRAPHY 68 APPENDIX 69
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4 1.0 INTRODUCTION Statistics is the study of how to collect, organize, analyze and interpret numerical information. Statistics is a rather broad definition and it is useful to consider the subject by discussing the major divisions within the fields: Descriptive Statistics refers to the statistical methods of describing and organization of data e.g. mean, median, mode, range, variance and standard deviation. Inferential Statistics refers to the methods of using a sample to obtain information about a population or making conclusions about a population from the sample statistics. It is therefore important to remember that the main role of inferential statistics is to draw conclusions about a population based on information obtained from a sample. Population refers to all measurements of interest. For example, the weights of all pineapples in a field.
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