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B.Stat-102: Principles of Statistics I
Course Code : B.Stat-102
Course Title : Principles of Statistics I
Course Type : Major
Level/Term and Section : B.Sc. Honours Part – I
Academic Session : 2019 – 2020
Course Instructor : x
Pre-requisite (If any) : x
Credit Value : 4
Total Marks : 100 (Examination 80, Tutorial/Terminal 15, and Attendance 5) 

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COURSE DESCRIPTION:
This is a very basic and introductory course of statistics. Stress has been laid on concepts, data processing, exploratory data analysis, statistical tools and techniques of analyzing data. Well known continuous probability distribution are also provided in this course.
COURSE OBJECTIVES (CO):
Students would be able to understand:
1) data, nature of data, how to process and condense the data
2) to apply appropriate statistical tools and techniques to analyze the data
3) well known continuous probability distribution and their properties
4) acquire knowledge on time series.
COURSE LEARNING OUTCOME (CLO):
After successful completion of this course, a student will be able to:
1)
 organize and condense the data to gather knowledge regarding data
2)
 present a systemic account of the statistical procedures which have .very wide applications in various field
3)
 know the applications of statistical ideas , tools and techniques in real  life problem to interpret the data
4)
 know well known continuous probability distribution and their applications .in various field
5)
 identify the pattern and trends and isolate the influencing factors of the time series data for future planning and control.
COURSE PLAN / SCHEDULE:  
CLO Topics to be covered Teaching-Learning Strategies  Assessment Techniques  No. of Lectures
1
Introduction to Statistics: Origin, history, meaning, classification and scope, limitations, uses and abuses of statistics. Basic concepts: population, sample, parameter, statistic, variable and attribute.
 Lecturing with Multimedia Projector, Interactive Board and Q/A session Assignment, Class Tests, Presentation, Final Exam.
5
2
Data Processing: Meaning, types of data, organization and presentation of data: classification and tabulation, frequency distribution, graphical representation of qualitative and quantitative data, stem and leaf display.
10
3
Descriptive Statistics: Central tendency, dispersion, moments, skewness and kurtosis, five number summary with their properties and applications.
22
4
Continuous Distribution: Normal, Uniform, Exponential, Logarithmic, Beta, Gamma, Cauchy, Laplace and Weibull, Pearson’s system of curves.
15
5
 Time Series: Basic concepts, Operators, different components with their measurement and uses.
8
Assessment Strategy Evaluation Policy (Grading System) and make-up procedures: According to the ordinance.

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Main Books Recommended:
Cramér, H. (2016). Mathematical methods of statistics. Princeton university press.,
Larsen, R. J., & Marx, M. L. (2014). Introduction to mathematical statistics and its applications. Pearson.
Weiss, N. A., & C. A. Weiss (2012). Introductory statistics. Pearson Education.
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 References:
Bartoszynski, R., & M. Niewiadomska-Bugaj (2007). Probability and statistical inference. John Wiley & Sons.
Behrens, J. T., & Yu, C. H. (2003). Exploratory data analysis. Handbook of psychology. [ Tukey, Pearson and Peng]
Bulmer, M. G. (2012). Principles of statistics. Courier Dover Publications.
Casella, G., & R. L. Berger (2002). Statistical inference (Vol. 2). Pacific Grove, CA: Duxbury.
Cox, D. R., & C. A. Donnelly (2011). Principles of applied statistics. Cambridge University Press.
Kardaun, O. J. (2005). Classical Methods of Statistics. Springer-Verlag Berlin Heidelberg.
Ott, R. L., & Longnecker, M. T. (2015). An introduction to statistical methods and data analysis. Nelson Education.
Triola, M. F., Goodman, W. M. LaBute, G., Law, R., & L. MacKay (2006). Elementary statistics. Pearson/Addison-Wesley.