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B.Sc. Statistics Program Outcomes

B.Sc Statistics program provides excellent preparation for carrier not only for mathematical sciences, also  in biological research, biotechnology, law, conservation, public policy, and science writing  as well as the health professions, including medicine, veterinary medicine and public health. 

          Students will learn about the concepts of Central tendency like..mean, median,mode, geometric    mean,harmonic mean.

           Students can identify the data without any difficulties.  They will know about the differences between concepts of Dispersion and Flatness.

           Its very easy to know about the Bi-variate data through the Statistics concepts By the Methods  Of Karl-Pearson's, Spear-man's Rank correlation

 By studying the Statistics  course they can Understand the Bi variate random variable, correlation and regression ,Partial correlation, and Exact sampling distributions. 

• Also learn about Sampling techniques, Analysis of variance ,time series,Indian statistical system,

Importance of Statistical Quality Control, Acceptance sampling, Linear programming problem and Reliability .

• It will be easy for students to find the Design of experiments ,Index numbers, Vital statistics, Demand analysis, Transportation problem, Assignment problem ,Sequencing problem and Game theory  by using the magical concepts of Statistics. 

Course Outcomes

Semester-I

      Descriptive Statistics:

• how to collect the primary and secondary data and Measures these data & also edit primary and secondary data

• To learn Basic concepts in probability

• Students learn the Basic Properties of probability based on axiomatic definition

• Basic Definitions of moment generating function, cumulant generating function (c.g.f), probability generating function (p.g.f)and characteristic function (c.f)

•     Semester-II           

• Probability Distribution: 

• In Uniform Bernoulli Distributions students will come to know how to calculate Mean, Variance, Movements and some properties with some examples.

• In Discrete Distributions students will learn about the limits of distributions generating functions like moment generating functions, cumulative generating function, probability generating function and characteristic function and their real life applications.

• In Continuous Distributions students will learn about parent distribution and how to get moments up-to forth order and difference between even and odd order movements.

• In Exponential and Gamma distribution students will learn about MGF, CGF, CF and also reproductive property, weak law of large numbers central limit theorem, limiting case methods where ever exists

•   Semester-III

• Statistical methods:

• In Bi variate Data Students will learn about Scattered Diagram and Principal of Least Squares, Concepts of correlation and its properties for both grouped and un-grouped data also to know about ratio of correlation and Spear-man's rank Correlation

• Students will learn about concepts of partial and multiple correlation coefficients, analysis of categorical data, independence and associations of attributes and yule's correlation coefficient, Pearson and Tcheprow coefficients

• Students will learn about population, random sample and basic definition, Exact sampling distribution like chi-square, t and f distributions and their inter relationships. To learn about good estimators with examples

• Students will learn Neyman's Factorization theorem, Derivations of Sufficient Statistics in case of Poisson, Binomial, normal and Exponential distribution. Estimation by method of moments, maximum likelihood estimators and also concept of interval estimation, confidence intervals

•   Semester-IV

• Statistical Inference:

• Learn about statistical hypothesis, null and alternative hypothesis by using a information (clue), critical region, types of errors, Neyman Pearson's Fundamental Lemma

• Students will have an idea about large sample test for single mean and its types also difference of proportions and standard deviation. Fisher's Z transformation for population, Correlation Coefficient

• Tests of Chi-square for specified variance, goodness of fit and test for independence of attributes test of significance based on students T test

• Students will have an idea about non parametric tests and their advantages and disadvantages , comparision with parametric tests. Measurements on scale, nominal, ordinal, interval and ratio methods. One sample run test and Wilcox-on-signed rank test, median test, U test, Wald Wolfowitz's run test.

•   Semester-V

• Sampling Theory, Time series, Index numbers, and Demand Analysis:

• Students will learn about sample surveys by using concepts of population sampling unit statistic and sample frame and also able to know standard error, differences between census and sample survey and advantages of limitations of sampling

• Stratified random sampling with proportional and Nay man allocation, systematic sampling, time series and its components

• Growth Curves and modified exponential curves and logistic curve, determination of seasonal indices.

• Introduction to demand and supply, price elasticity of demand and supply, methods of Leontief's, Pigou's methods of determining demand curve from time series data and index numbers

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• SQC and reliability:

• Importance of SQC in industry, statistical basis of Shewartz, construction of control charts for variable

• Control charts for attributes and their interpretation, Natural tolerance limits, process capability

• Concepts of acceptance sampling plans producers risk and consumers risk and Single and double sampling plans, OC curves and ASN functions.

• Reliability introduction and hazard function, exponential distribution its memory less property, system reliability series and parallel series with simple examples

•   Semester-VI

• Design of experiments, vital statistics and official statistics and business forecasting:

• Concepts of Gauss-Mark off linear Model and also statement of Cochran's theorem and ANOVA, one-way, two-way classifications

• Latin square design including one missing observation and also functions and organisation of CSO and NSSO

• Agricultural statistics, area and yield statistics , role of forecasting business, methods of forecasting

• Introduction to vital statistics and its sources, registration method and census method measurement of population and growth, crude rate of natural increase - pearl's vital index

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• Operations research:

• Learning of Scope of operations research, convex sets and their properties and to learn about general LPP and how to write simplex algorithm

• Learn about concepts of artificial variables big - M method, concept of Degeneresy and resolving it

• Transportation problem and to know about initial basic feasible solution by various methods and balanced and unbalanced transportation problems

• Hungarian method and travelling salesman problem and its solutions, optimal sequence of N jobs on 2 and 3 machines without passing