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B.Stat-104: Basic Mathematics and Statistical Indices
Course Code : B.Stat-104
Course Title : Basic Mathematics and Statistical Indices
Course Type : Related
Level/Term and Section : B.Sc. Honours Part – I
Academic Session : 2019 – 2020
Course Instructor : x
Pre-requisite (If any) : x
Credit Value : 2
Total Marks : 50 (Examination 40, Tutorial/Terminal 7.5, and Attendance 2.5) 

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COURSE DESCRIPTION:
Statistics is the art of using data to make numerical conjectures about problems. This is an introductory course in statistics designed to provide students with the basic concepts of bivariate data analysis. Topics covered include correlation analysis, which is used to quantify the association between two random variables, regression analysis which is a related technique to access the relationship between an outcome variable, analysis of attributes, and bivariate distribution.
COURSE OBJECTIVES (CO):
1)
 The bachelor knows and is able to apply basics of bivariate data.
2)
 Students will understand the feathers of various correlations.
3)
 Students will apply appropriate correlation according to the nature of data.
4)
 Students will understand the features of simple regression.
5)
 Students will understand the concepts and tools of bivariate normal distribution.
COURSE LEARNING OUTCOME (CLO):
Upon successful completion of this course, a student will be able to
1)
 explain the concepts and tools of bivariate data
2)
 understand method and concept of simple, multiple, partial and rank correlations and interpret the outcomes of correlation coefficients
3)
 calculate and interpret the association between two attributes
4)
 develop an understanding of the theoretical basis for linear regression analysis and know the basic assumptions behind regression analysis
5)
 understand about bivariate probability distribution and its properties.
COURSE PLAN / SCHEDULE:  
CLO
Topics to be covered
Teaching-Learning Strategies 
Assessment Techniques 
No. of Lectures
1
 Bivariate data, scatter diagram, Bivariate table, Conditional means and variances, Marginal distributions. Lecturing with Multimedia Projector, Interactive Board and Q/A session Assignment, Class Tests, Presentation, Final Exam.
10
2
 Simple Correlation, Correlation ratio, Rank correlation, Spearman rank correlation, Partial and multiple correlation, Spurious correlation and Non-sense correlation.
15
3
 Two variable linear regression, Estimation of parameters with properties, Residual analysis, Three variables regression (without matrix approach).
10
4
 Basic ideas, classification, Order of classes and class frequencies, Ultimate class frequencies, Positive attributes, Consistency, Incomplete data, Association of attributes, Independence, Complete association and disassociation, Measures of association, Coefficient of association and colligation, Partial association, Analysis of 2 x 2 and r x c contingency table, Yate’s correction.
15
5
 Concept of bivariate probability distribution, Marginal and conditional distributions, Expected values and variances, Moments and cumulants. Moment and cumulant generating functions, Derivation of bivariate normal distribution and study of its properties, Normal regression.
10
Assessment Strategy Evaluation Policy (Grading System) and make-up procedures: According to the ordinance.

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Main Books Recommended:
1) Ayres, F. (1965): Theory and Problems of Modern Algebra, Schaum’s Outline Series, McGraw-Hill Book Company.
2) Anton, H. (2000): Calculus with Analytic Geometry, Wiley, N.Y. [Donevska, Price]
3) Fuller, G. (1977): College Algebra, D. Van Nostrand Company, New York, USA. [Dawkins, Spiegel, Kaufmann,  Anton]
4) Horn, V. Robert (1993): Statistical Indicators for the Economic and Social Sciences, Cambridge University Press.
5) World Health Organization. (2015). Global reference list of 100 core health indicators. [Mustafizur Rahman]

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Reference:
6) Bangladesh Bureau of Statistics (2016): Monthly Release on Consumer price Index, Inflation Rate and Wage Index in Bangladesh, Bangladesh Bureau of Statistics, Ministry of Planning.
7) Stoer, J., & Bulirsch, R. (2013). Introduction to numerical analysis (Vol. 12). Springer Science & Business Media.
8) Littlewood, D. E. (1977): University Algebra, Oxford University Press, Oxford
9) Van Der Waerden,BL (1966): Modern Algebra, Frederick Ungar publishing Co., New York.