B. Sc.:- Statistics [ B. Sc. I and II ]
B. Com.:- Statistics[ B. Com. II ]

Course Outcomes: B.Sc.Statistics

The following outcomes have been achieved:-

Paper 1DSC – 7A DESCRIPTIVE STATISTICS – I

CO1: The students are able to understand some basic concepts in Statistics.

CO2: The students are able to compute various measures of central tendencies, dispersion, moments, skewness and kurtosis.

CO3: They are able to analyze data pertaining to attributes and to interpret the results to think critically and logically.

Paper 2DSC – 8AELEMENTARY PROBABILITY THEORY

The students are able to understand some basic concepts in probability viz.

CO1:To distinguish between random and non-random experiments.

CO2: To find the probabilities of various events.

CO3: To understand concept of conditional probability and independence of events

Paper 3DSC – 7B DESCRIPTIVE STATISTICS – II

The students are able to understand some basic concepts in statistics, viz

CO1:To compute correlation coefficient, interpret its value.

CO2:To compute regression coefficient, interpret its value and use in regression analysis.

CO3:To compute various index numbers.

Paper 4DSC – 8B -DISCRETE PROBABILITY DISTRIBUTIONS

The students are able to understand some basic concepts of random variable and

discrete probability distribution, viz.

CO1:To apply discrete probability distributions studied in this course in different situations.

CO2:Distinguish between discrete variables and study of their distributions.

CO3: Know some standard discrete probability distributions with real life situations.

CO4: Understand concept of bivariate distributions and computation of related probabilities.

Paper 5: Probability Distributions-I

The students are able to understand some concepts of,

CO1:Standard discrete distribution defined on countably infinite sample space, viz.Poisson, Geometric and Negative Binomial Distribution.

CO2:Continuous univariate random variable.

CO3:Continuous bivariate random variable.

CO4:Transformation of continuous univariate random variable.

· CO5:Transformation of continuous bivariate random variable.

Paper 6 Paper VI: Statistical Methods-I

The students are able to apply the statistical tools in the applied fields, viz,

CO1:Multiple Linear Regression

CO2:Multiple and Partial Correlation

CO3:Demography

CO4:Sampling Theory

Paper 7 Probability Distributions-II

The students are able to understand some concepts of, Standard continuous distribution defined on un-countably infinite sample space, viz.

CO1: Uniform and Exponential Distributions

CO2: Gamma and Beta Distributions

CO3: Normal distribution

CO4:Chi-Square distribution

CO5: Student’s t- distribution

CO6: Snedecor’s F distribution

Paper 8 Paper VIII: Statistical Methods-II

The students are able to apply the statistical tools in the applied fields, viz,

CO1: Time Series Analysis

CO2: Statistical Quality Control

CO3:Testing of Hypothesis

CO4: Exact sample Tests

Practical’s:

Paper-I

At the end of this course students are able-

CO1: To represent statistical data diagrammatically and graphically.

CO2:To compute various measures of central tendency, dispersion, moments, skewness and kurtosis.

CO3:To compute correlation coefficient, regression coefficients.

CO4:To understand Consistency, Association and Independence of Attributes.

CO5:To interpret summary Statistics of computer output.

CO6:To know applications of some standard discrete probability distributions.

CO7:To compute the index numbers.

Paper-II

At the end of this course students are able-

CO1:To fit probability distributions and to test goodness-of-fit viz. Discrete Uniform, Binomial, Hypergeometric,Poisson, Geometric,Negative Binomial, Continuous Uniform, Exponential and Normal distribution.

CO2:To draw a random sample from Discrete Uniform, Binomial, Hypergeometric,Poisson, Geometric,Negative Binomial, Continuous Uniform, Exponential and Normal distribution.

CO3:To apply Binomial, Hypergeometric, Poisson, Geometric, Negative Binomial, Continuous Uniform, Exponential and Normal distribution to real life data or simulated data.

Practical 3

At the end of this course students are able-

CO1:To fit straight line and curves of type, second degree, Y = a.b ^X, Y = aX^b and Y = ae^bX

CO2:To fit and analyse Time Series data (methods of measuring trend and seasonal indices).

CO3:To construct and R charts, np and c charts.

CO4:To compute mortality rates, fertility and Reproduction rates

CO5:To apply statistical tests viz, Large sample tests for means, tests for proportions, tests for population correlation coefficients, test for population variance, Test for goodness of fit, tests for independence.

CO6:To apply statistical tests viz, tests based on t distribution (µ = µ ₀, µ₁ = µ₂; paired t-test), Tests based on F distribution. (σ₁= σ₂),

CO7:To use MS-EXCEL for computation of above practical’s.

Programme’s Specific Outcomes

B.Sc. Statistics

PSO1: Serve as Statistician with sound theoretical, practical & computational skill.

PSO2: Work as researcher for formulation & solution of mathematical, scientific, social & industrial problem.

PSO3: Understand the role of statistics in science, society & for National Development.

PSO4: Apply some discrete & continuous probability distribution which are highly useful in modeling real life uncertainties.

PSO5: Investigate the relationship between a variable of interest (the response) & a set of related predictor variable & formulate & fit the appropriate regression model to the given dataset.

Programme’s Outcomes

B.Sc . Statistics

PO1: To understand distinguish between random &non-random experiment

PO2: To apply discrete Probability Distribution studied in the course in different situations.

PO3: Students should know concept of time series. SQC, demography

PO4:.To understand concept of estimation and testing theory.

PO5:.Apply knowledge to solve simple tasks using computer (MS Excel)