Coming soon
Postgraduate
PROGRAMME OUTCOMES
|
PO 1 |
Gives a platform to students for pursuing higher degree and research. |
|
PO 2 |
Ability to use skills in Statistics and different practicing areas for formulating and tackling data related problems and identifying and applying appropriate principles and methodologies to solve a wide range of problems associated with Statistics and tackle open-ended problems that belong to the other disciplinary-area boundaries |
|
PO 3 |
Students become more computer friendly as they learn various functions of statistical software like Excel, R, SPSS and Python to analyse the statistical data during the programme duration. |
|
PO 4 |
This program offers opportunities in academics, Govt. Service, IAS, Indian Statistical Services, Industries, Banking and Insurance Sectors, CSO and NSSO, Research Personnel/Investigator in Govt. organizations such as NCAER, IAMR, ICMR, Statistical and Economic Bureau & various PSUs, MNC as data analyst, actuarial science. Also Enhances theoretical rigor with technical skills which prepare students to become globally competitive to enter into a promising professional life. |
|
PO 5 |
Ready to deal with the problems related to quality control of product during process and also after the completion of product in industry, removal of outliers, market demand and supply, income and expenditure, comparing the price, quantity and value indices. |
|
PO 6 |
Ability to analyse the cost of transportation of material and product, stocking of material at minimum cost, minimize waiting time and select the priority among different goals to obtain maximum profit in market. |
|
PO 7 |
Get knowledge about the population characteristics and be able to compare by applying an appropriate method of probability and non-probability sampling. If the students opt for the advance paper of sampling then they will be eligible for research, government and non-government projects regarding the conduction of surveys. And If the students opt the advance paper of design they will be eligible for jobs in agricultural departments, and also for higher research. |
|
PO 8 |
Ability to develop a new model on already existing economic theories, model based on time series, market policies for different group of population, vital information and also check and remove the discrepancies of the model and perform forecasting based on them . |
|
PO 9 |
Analyse the behavior of the population and sample data and also obtain the appropriate Univariate, bivariate and multivariate distributions and to compare two or more population parameters using parametric and non-parametric test. |
|
PO 10 |
Ability to generate and compare various national and international life tables and vital events of different groups or places so that they are able to generate new policies for individuals and groups. |
|
PO 11 |
Ability to generate and infer confidence intervals, obtain sample statistic to estimate the population parameters, also check the accuracy of parameters. |
|
PO 12 |
Analyse the reliability of a model, develop new models and connect it with biological behavior of data. If students opt clinical and survival analysis and reliability analysis then they are eligible for jobs in medical field as scientist. |
PROGRAMME SPECIFIC OUTCOMES
|
PSO 1 |
Pursue for various job opportunities in Academics, Government Services, |
|
PSO 2 |
Communicate statistical ideas effectively, in writing as well as |
|
PSO 3 |
Able to apply statistical skills and logical reasoning for problem solving.
|
COURSE ARTICULATION MATRIX: (MAPPING OF COS WITH POS)
|
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
|
CO1 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO2 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO3 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO4 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO5 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO6 |
√ |
√ |
|
√ |
|
|
√ |
|
√ |
|
|
|
|
CO7 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO8 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO9 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO10 |
√ |
√ |
|
√ |
|
|
√ |
|
√ |
|
|
|
|
CO11 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO12 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO13 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO14 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO15 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO16 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO17 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO18 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO19 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO20 |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
|
CO21 |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
|
CO22 |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
|
CO23 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO24 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO25 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO26 |
√ |
√ |
|
√ |
|
|
√ |
|
√ |
|
|
|
|
CO27 |
√ |
√ |
|
√ |
|
|
√ |
|
√ |
|
|
|
|
CO28 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO29 |
√ |
√ |
|
√ |
|
|
|
|
|
|
√ |
|
|
CO30 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO31 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO32 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO33 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO34 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO35 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO36 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO37 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO38 |
√ |
√ |
|
√ |
|
|
√ |
|
|
|
|
|
|
CO39 |
√ |
√ |
|
√ |
|
|
√ |
|
|
|
|
|
|
CO40 |
√ |
√ |
|
√ |
|
|
√ |
|
|
|
|
|
|
CO41 |
√ |
√ |
|
√ |
|
|
√ |
|
|
|
|
|
|
CO42 |
√ |
√ |
|
√ |
|
|
√ |
|
|
|
|
|
|
CO43 |
√ |
√ |
|
√ |
|
|
√ |
|
|
|
|
|
|
CO44 |
√ |
√ |
|
√ |
|
|
√ |
|
|
|
|
|
|
CO45 |
√ |
√ |
|
√ |
|
|
√ |
|
|
|
|
|
|
CO46 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO47 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO48 |
√ |
√ |
√ |
√ |
|
|
√ |
|
|
|
|
|
|
CO49 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO50 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO51 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO52 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO53 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO54 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO55 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO56 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO57 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO58 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO57 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO58 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO59 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO60 |
√ |
√ |
|
√ |
|
|
|
|
√ |
|
√ |
|
|
CO61 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO62 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO63 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO64 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO65 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO66 |
√ |
√ |
|
√ |
|
|
|
√ |
|
√ |
|
|
|
CO67 |
√ |
√ |
|
√ |
|
|
|
√ |
|
√ |
|
|
|
CO68 |
√ |
√ |
|
√ |
|
|
|
√ |
|
√ |
|
|
|
CO69 |
√ |
√ |
|
√ |
|
|
|
√ |
|
√ |
|
|
|
CO70 |
√ |
√ |
|
√ |
|
|
|
√ |
|
√ |
|
|
|
CO71 |
√ |
√ |
|
√ |
|
|
|
√ |
|
√ |
|
|
|
CO72 |
√ |
√ |
|
√ |
|
|
|
√ |
|
√ |
|
|
|
CO73 |
√ |
√ |
|
√ |
|
|
|
√ |
|
√ |
|
|
|
CO74 |
√ |
√ |
|
√ |
|
|
|
|
|
√ |
|
√ |
|
CO75 |
√ |
√ |
|
√ |
|
|
|
|
|
√ |
|
√ |
|
CO76 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
√ |
|
CO77 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
√ |
|
CO78 |
√ |
√ |
√ |
√ |
|
|
|
|
√ |
|
|
|
|
CO79 |
√ |
√ |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
CO80 |
√ |
√ |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
CO81 |
√ |
√ |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
CO82 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO83 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO84 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO85 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO86 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO87 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO86 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO88 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO89 |
√ |
√ |
|
√ |
√ |
|
|
|
|
|
|
|
|
CO90 |
√ |
√ |
|
√ |
√ |
|
|
|
|
|
|
|
|
CO91 |
√ |
√ |
|
√ |
√ |
|
|
|
|
|
|
|
|
CO92 |
√ |
√ |
|
√ |
√ |
|
|
|
|
|
|
|
|
CO93 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO94 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO95 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO96 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO97 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO98 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO99 |
√ |
√ |
|
|
|
|
|
√ |
|
|
|
|
|
CO100 |
√ |
√ |
|
√ |
|
|
|
√ |
|
|
|
|
|
CO101 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO102 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO103 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO103 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO104 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO105 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO106 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO107 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO108 |
√ |
√ |
|
√ |
|
√ |
|
|
|
|
|
|
|
CO109 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
√ |
|
CO110 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
√ |
|
CO111 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
√ |
|
CO112 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
√ |
|
CO113 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
√ |
|
CO114 |
√ |
√ |
|
√ |
|
|
|
|
|
|
√ |
|
|
CO115 |
√ |
√ |
|
√ |
|
|
|
|
|
|
√ |
|
|
CO116 |
√ |
√ |
|
√ |
|
|
|
|
|
|
√ |
|
|
CO117 |
√ |
√ |
|
√ |
|
|
|
|
|
|
√ |
|
|
CO118 |
√ |
√ |
|
√ |
|
|
|
|
|
|
√ |
|
|
CO119 |
√ |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
CO120 |
√ |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
CO121 |
√ |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
CO122 |
√ |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
CO123 |
√ |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
CO124 |
√ |
√ |
√ |
√ |
√ |
|
|
|
|
|
|
|
|
CO125 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO126 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
|
CO127 |
√ |
√ |
|
√ |
|
|
|
|
|
|
|
|
