Course Contents

PART A: (PHARMACEUTICAL MATHEMATICS) (40 MARKS) 1. ALGEBRA: (a) Solution of Linear and Quadratic Equations: Equations reducible to Quadratic Form. Solution of simultaneous Equations. (b) Arithmetic, Geometric and Harmonic Progressions: Arithmetic, Geometric and Harmonic Means. (c) Permutations and Combinations: (d) Binomial Theorem: Simple application. 2. TRIGONOMETRY: Measurement of Angles in Radian and Degrees. Definitions of circular functions. Derivation of circular function for simple cases. 3. ANALYTICAL GEOMETRY: Coordinates of point in a plane. Distance between two points in a plane. Locus, Equations of straight line, Equation of Parabola, Circle and Ellips. 4. DIFFERENTIAL CALCULUS: Functions, variations in functions, limits, differential coefficient, differentiation of algebraic, trigonometric, exponential and logarithmic functions, partial derivatives. Maxima and minima values. Points of inflexion. 79 5. INTEGRAL CALCULUS: Concept of integration, Rules of integration, Integration of algebraic, exponential, logarithmic and trigonometric functions by using different techniques and numerical integration. PART B: (BIOSTATISTICS) (60 MARKS) 1. DESCRIPTION OF STATISTICS: Descriptive Statistics: What is Statistics? Importance of Statistics. What is Biostatistics? Application of Statistics in Biological and Pharmaceutical Sciences. How samples are selected? 2 ORGANIZING and DISPLAYING DATA: Vriables, Quantitative and Qualitative Variables, Univariate Data, Bivariate Data, Random Variables, Frequency Table, Diagrams, Pictograms, Simple Bar Charts, Multiple Bar Charts, Histograms. 3. SUMMARIZING DATA and VARIATION: The Mean, The Median, The Mode, The Mean Deviation, The Variance and Standard Deviation, Coefficient of Variation. 4. CURVE FITTING: Fitting a Straight Line. Fitting of Parabolic or High Degree Curve. 5. PROBABILITY: Definitions, Probability Rules, Probability Distributions (Binomial & Normal Distributions). 6. SIMPLE REGRESSION AND CORRELATION: Introduction. Simple Linear Regression Model. Correlation co-efficient. 7. TEST OF HYPOTHESIS AND SIGNIFICANCE: Statistical Hypothesis. Level of Significance. Test of Significance. Confidence Intervals, Test involving Binomial and Normal Distributions. 8. STUDENT “t”, “F” and Chi-Square Distributions: Test of Significance based on ―t‖, ―F‖ and Chi-Square distributions. 9. ANALYSIS OF VARIANCE: One-way Classification, Two-way Classification, Partitioning of Sum of Squares and Degrees of Freedom, Multiple Compression Tests such as LSD, The analysis of Variance Models. 10. STATISTICAL PACKAGE: An understanding of data analysis by using different statistical tests using various statistical software’s like SPSS, Minitab, Statistica etc.