This paper is designed to acquaint the students with the fundamental statistical techniques, to understand the role of statistics for analysing and interpreting data meaningfully.
Students will be able to:
Course |
Learning outcomes (at course level |
Learning and teaching strategies |
Assessment Strategies
|
|
---|---|---|---|---|
Paper Code |
Paper Title |
|||
STT-102 |
Basic Statistics and Probability |
CO 6: Define and use the basic terminology of statistics.
CO 7: Classify the data and prepare various diagrams and graphs.
CO 8: Demonstrate the use of exploratory and descriptive data analysis.
CO 9: Learn the concept of elementary probability theory and its application.
CO 10: Identify the problem and apply appropriate laws of probability and Bayes theorem. |
Approach in teaching: Interactive Lectures, Group Discussion, Classroom Assignment Problem Solving Sessions
Learning activities for the students: Assignments Seminar Presentation Subject based Activities |
Classroom Quiz Assignments Class Test Individual Presentation |
Definition, scope, and limitations of statistics, Concept of statistical population. Types of data- Primary and Secondary data, Univariate and Bivariate data. Census and Sample Survey. Qualitative and Quantitative classification, discrete and continuous classification, Geographical and Chronological classification. Construction of frequency tables, frequency distribution for continuous and discrete data, cumulative frequency distributions (inclusive and exclusive methods.
Histogram, Frequency Polygon, Frequency curve and Ogives.
Univariate Data – Measures of Central Tendency – Definition, different measures of Central Tendency, merits and demerits. Measure of Dispersion- Definition, different measures of Dispersion, merits and demerits. Coefficient of variation. Relative dispersions.
Central moments and Non-central moments and their computation from data. Absolute and Factorial moments. Concept of Quartiles, deciles and percentiles. Measure of Skewness and Kurtosis, Sheppard’s, Correction for moments (without proof).
: Set Theory, Power set, De- Morgan Law, Random Experiment, Trial, Events and their types. Classical, Statistical and Axiomatic definition of probability and its properties (simple).Addition theorem of probability and their application.
Multiplication theorems of Probability and their application, Conditional Probability and complete, Independent and pairwise events. Baye’s theorem and its application (simple questions).
Volume I, The World Press PvtLtd , Calcutta
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