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# BIOMATHEMATICS & BIOSTATISTICS-1

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### Specific References

According to New CBCS Syllabus w.e.f. 2019-20

# Biomathematics & Biostatistics-1

Author: Gamaji Deore, Ramdas Sonawane, Dr. Sujata Tapare, Surekha Deshmukh

Price: 200/-

ISBN: 978-93-5016-455-6

Quantity
In Stock

Contents

1. Fundamentals Mathematical Calculations

1. Introduction

2. Exponents and Powers

2.1 Fractional Indices

2.2 Laws of Indices

3. Logarithms

4. Permutations and Combinations

4.1 Fundamental Principle of Counting (The Multiplication Principle)

4.2 Permutations

4.3 Combinations

5. Co-ordinate Geometry

5.1 Area of the Triangle and Quadrilateral

5.2 Slope of a Line

5.3 Conic Sections

2. Matrices and Vector Spaces

1. Matrices

1.1 Definitions

1.2 Types of Matrices

1.3 Operations on Matrices

1.4 Equality of Matrices

1.5 Transpose of a Matrix

1.7 Multiplication of Matrices

1.8 Determinant of Matrix

2.2 Vector Spaces

2.1 Introduction

2.2 Euclidean N-Space

2.3 General Vector Space

2.4 Subspaces

2.5 Linear Combination

2.6 Linear Independence and Dependence

2.7 Dot Product and Cross Product

3. Introduction to Statistics

1. Need of Statistics in Biology

2. Data Condensation and Graphical Methods

2.1 Attributes and Variables

2.2 Parameters

2.3 Classification

2.4 Frequency Distribution

2.5 Cumulative Frequency Distribution

2.6 Relative Frequency Distribution

3. Population and Sample

3.1 Population

3.2 Sample

4. Types and Methods of Sampling

5. Limitations of Sampling

6. Graphical Representation of Frequency Distribution

6.1 Histogram

6.2 Ogive or Cumulative Frequency Curve

7. Diagrams

7.1 Simple Bar Diagram

7.2 Sub-divided Bar Diagram

7.3 Multiple Bar Diagram

7.4 Pie Diagram

4. Descriptive Biostatistics

1. Measures of Central Tendency

1.1 Objectives and Requisites of a Good Average

1.2 Arithmetic Mean

1.3 Median

1.4 Mode

1.5 Partition Values

1.6 Appropriate Choice of an Average

2. Measures of Variability

2.1 Range

2.2 Quartile Deviation

2.3 Mean Deviation

2.4 Variance and Standard Deviation

3. Correlation

3.1 Bivariate Data

3.2 Correlation

3.3 Karl Pearson’s Coefficient of Correlation

4. Regression

4.1 Linear Regression

4.2 Fitting of Straight Line Using Least Square Method

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