The DST offers Statistics for the Physical Science students and IS & MF students for their general degree degree program

## Physical Science

Level I Course Units

Semester | Course Module | Credits | Hours |
---|---|---|---|

Sem I | |||

ST1006 | Introduction to Probability & Statistics | 2 | 30 L |

ST1007 | Statistics Practicals | 1 | 30 P |

ST1002 | Statistical Data Management I | 1 | 15 L |

Sem II | |||

ST1003 | Statistical Theory | 2 | 30L/30P |

ST1004 | Introduction to Surveys, Sampling & Medical Statistics | 2 | 30L |

ST1005 | Statistical Data Management II | 1 | 15L |

## Level II Course Units

Semester | Course Module | Credits | Hours |
---|---|---|---|

Sem I | |||

ST2001 | Basic Elements of Inference | 2 | 30L |

ST2002 | Hypothesis Testing / Data Analysis-I | 2 | 15L/15P |

ST2004 | Analysis of Variance & Design of Experiments | 1 | 30L |

Sem II | |||

ST2003 | Introduction to Non Parametric Methods | 2 | 30L/30P |

ST2005 | Hypothesis Testing / Data Analysis-II | 2 | 15L/15P |

## Level III Course Units

Semester | Course Module | Credits | Hours |
---|---|---|---|

Sem I | |||

ST3003 | Marketing Research | 2 | 30L |

ST3006 | Regression Analysis | 2 | 30L |

ST3007 | Operational Research | 3 | 45L |

Sem II | |||

ST3004 | Time Series and Forecasting | 2 | 30L |

ST3067 | Quality Control | 2 | 30L |

**Combinations**

- P1
*– Physics,Chemistry, Applied Math., Computer Science* - P2
*– Physics, Applied Math., Statistics, Computer Science* - P3
*– Physics, Applied Math., Pure Math., Computer Science* - P4
*– Chemistry, Applied Math., Statistics, Computer Science* - P5
*– Chemistry, Applied Math., Pure Math., Computer Science* - P6
*– Applied Math., Statistics, Pure Math., Computer Science*

**ST 1006: Introduction to Probability and Statistics (15L, 1C)**

Dependencies: AM 1001

**Syllabus:** Descriptive Statistics: Types of data (qualitative, quantitative, continuous, discrete, etc.); scales of measurement (nominal, ordinal, interval, ratio, etc.); data summarization : frequency table, cum. frequency table, histogram, bar chart, pie chart, percentiles, quartiles, 5 –number summary, Box plot, outliers; measures of location: mean, trimmed mean, median, mode; measures of dispersion: range, inter quartile range, variance, standard deviation; coefficient of variation, skewness, kurtosis, Probability: Probability definitions; counting rules, permutations and combinations, finite sample space, events, probability rules, conditional probability, independence, multiplication rule, Bayes’ theorem, One dimensional random variables; probability density function and probability (mass) function, cum. distribution function, expected value, variance, associated theorems, and moment generating function, distribution of functions of random variables. Discrete distributions: Uniform, Bernoulli, Binomial, Poisson, and applications; continuous distributions: Uniform, Exponential, Normal; central limit theorem with applications.

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** Introductory Statistics (Perm S. Mann), Concise Course in A-Level Statistics (J. Crawshaw, J. Chambers),

Statistics for Business and Economics (Joseph G. Van Matre, Glenn H. Gillreath)

**ST 1002: Statistical Data Management I (15L, 1C)**

**Syllabus:** Data collection: Importance of data collection, reasons of collecting data for a specific purpose,major steps in the data transformation process,Entering data: Data entry formats, types of data, exporting/importing data, handling data using spread sheets Data Organization: Variables and measurements: Accuracy of measurements (quality of scientific data), rounding numbers, levels of measurements, describe the form of the most significant relationships, primary and secondary data, advantages of using secondary data, Manipulation of data: Coding, sorting and ranking of data, calculations using data, merging files, Stacking/concatenating data sets, Organizing the data: Tabular display: The data array, frequency distributions, proportion and percentage distributions, cumulative distributions Presenting data in graphs: Frequency polygons, histograms, line charts, bar charts, pie charts, Scatter plots, Box plots, Examples using small data sets

**Evaluation Criteria: **End-of-semester examination and assignments

**Suggested Readings: ** Statistics: An Introduction (Roger E. Kirk)

**ST 1004: Introduction to Surveys, Sampling and Medical Statistics (30L, 2C)**

**Syllabus:**Planning of a survey, Questionnaire designing, Problems arising in the execution of a survey.Relationship between census and samples; steps involved in developing a sample survey, types of sampling methods, principles governing the design of questionnaires; major components of questionnaires. Mortality, Crude death rate, Standardization, Morbidity, Prevalence, Incidence, Life tables.

**Evaluation Criteria:**End-of-semester examination and assignments

**Suggested Readings:**Elements of Sampling Theory (Vic Barnet), Sampling Techniques (William Cocharn),Statistical Methods in Medical (Armitage)

**ST 1005: Statistical Data Management II (15L, 1C)**

**Dependencies:** ST1002

**Syllabus:** Data analysis based on basic distributions; introduction to random numbers; generation ofrandom numbers; methods of simulation; application of Central Limit Theorem; outlier detection; identification of distributions. Demonstration using a real data set

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** Statistics: An Introduction (Roger E. Kirk)

**ST1007: Basic Statistics Practical**

**Dependencies:** ST1006

**Syllabus:** The aim of this course is to familiarize the students with practical aspects of the theory courseST1006. This would include data analysis, exercises and familiarize with a statistical package.

**Evaluation Criteria:** Take-Home and In-Class practical assignments

**ST1003: Stastical Theory (30L, 3C)**

**Dependencies:** AM 1001

**Syllabus:** Distribution of functions of a random variable; Geometric, Negative Binomial, and Hypergeometric distributions; Gamma, Chi-squared, and Beta distributions; relationships between distributions; two –dimensional random variables: joint distribution (discrete, continuous), marginal and conditional distributions, independence, Bivariate normal distribution, covariance, correlation, conditional expectation, expectation of functions of random variables; bivariate transformations (discrete and continuous); some important distributions: t and F. Order statistics.

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** An Outline of Statistical Theory (Goon, Gupta and Dasgupta), Fundamentals of mathematical Statistics (Gupta and Kapoor)

**ST 2001 : Basic elements of inference (30L, 2C)**

**Dependencies:** AM 1001

**Syllabus:** Definitions of population, sample, parameter, statistic, and estimation; sampling distribution; point estimation, bias, error; interval estimation; margin of error, confidence intervals for mean and proportions, one sided and two sided tests, testing a two sided hypothesis using confidence intervals, level of significance (P-value), type I and type II errors associated with decision making, randomization test and exact p-value, determination of sample size, large sample tests for proportions.

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** Introduction to Statistics: Concepts and Application (A. Sweeney and William), A Concise course in A-level Statistics (J. Crawshaw, J. Chambers)

**ST 2002 : Hypothesis Testing / Data Analysis I (15L/30P, 2C)**

**Syllabus:** Inferences about the mean of a normal population single sample Problems, point & interval estimation Single sample Problems, Point & interval estimation of hypothesis tests when s is known and when s is unknown. The distribution, Concepts of degrees of freedom Two sample problems, independent sample with (a) known Population Variances & (b) unknown but equal variances, Pooled variance, paired samples, confidence limits and hypothesis tests for the differences between the two population means.

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** Fundamental of Mathematical Statistics (S.C. Gupta, V.K.K. Kapoor), Introduction to Mathematical Statistics (Robert V. Hogg and Allen T. Craig)

**ST 2003 : Introduction to non–parametric methods (30L, 2C)**

**Dependencies:** ST 1001

**Syllabus:** Introduction, one sample tests, randomization tests Wilcoxon’s one sample tests, Sign test, Sign Rank tests, Mann Whitney test, Simple Contingency tables, testing for independence, Fishers exact test, K.S.test, Kruskal-Wallis test, Friedman’s test

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** Non Parametric Statistics (Sidney Siegal, N. john Castellan), Practical Non Parametric Statistics (William Conover), Non Parametric Statistical Test Based On Ranks (Lehnmann)

**ST 2004: Analysis of variance & Design of Experiments (30L, 2C)**

**Dependencies:** ST 1001

**Syllabus:** Principles of design, Replication and randomization, Model for a completely randomized design, Analysis of ariance for One – Way Classification, standard errors for specific comparisons.

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** Experimental Design (W.G. Cochrn and G.M. Cox), The Design of Experiments (R. Mead), Statistical methods in agriculture and Experiment Biology (R. Mead and R.M. Curnow

**ST 2005: Hypothesis testing /Data Analysis II (15L/30P, 2C)**

**Syllabus:** Hypothesis testing for variance being equal to a specified value in the case of single sample and being equal to variance of a second population in the case of a two sample problem F distribution. Types of errors associated with hypothesis testing, Type I and Type II errors, Power of the test, power curves. Testing for parameters in the Poisson and Binomial distributions, Comparison of two Binomial probabilities, Chi – Square test.

**Evaluation Criteria:** Take-Home and In-Class practical assignments

**Suggested Readings:** Fundamental of Mathematical Statistics (S.C. Gupta, V.K.K. Kapoor), Introduction To Mathematical Statistics (Robert V. Hogg and Allen T. Craig)

**ST 3003 : Marketing Research (30L, 2C)**

**Syllabus:**Introduction, The Marketing Research Process, Defining the problem with exploratory research, Survey research: Methods of communication with respondents, Test marketing, Measurements and Attitude scaling, Questionnaire design, Sampling procedures, Data analysis, report writing and presentation: Stochastic models of brand choice, Applications of General Linear Models in marketing, Conjoint analysis, Correspondence analysis, Advertising media models, Marketing response models.

**Evaluation Criteria:**End-of-semester examination and assignments

**Suggested Readings:**Marketing Research (D.R. Lehmann, S. Gupta, J.H. Steckel), Marketing Research, (Melvin Crask, Richard J. Fox, Roy Stout), Marketing Research (David A. Aakar)

**ST 3006 : Regression Analysis (30L, 2C)**

**Dependencies:** ST1004, ST2004

**Syllabus:** Introduction to regression, Correlation, Uses of regression, Simple linear regression model, Parameter estimation, inferences about the model, model diagnostics and prediction, Multiple regressions, Qualitative variables as predictors, Model building

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** Applied Regression Analysis (Draper & Smith), Applied Linear Regression (Sanford Weisberg)

**ST 3007 : Operational Research (45L, 3C)**

**Dependencies:** AM 2003, AM 2004

**Syllabus:** Integer programming and solution techniques, Zero-one programming and solution techniques, Transportation models, Assignment models and their solution techniques. Project planning and evaluation techniques, Deterministic inventory models with shortages and without shortages, Queuing models, Different queuing systems and disciplines.

**Evaluation Criteria: **End-of-semester examination and assignments

**Suggested Readings:** Operational Research an Introduction (Hamdy A. Taha), Operational research (Harvey M. Wagner)

**ST 3004 : Time Series and Forecasting (30L, 2C)**

**Syllabus:** Introduction: Areas of applicaton, Objectives of time series analysis, Componenet of time series, Descriptive analysis. Distributional properties: Independence, Autocorrelation, Stationary. Probability models to time series: Random walk, Autoregressive model. Moving Average model, mixed models, parameter estimation, Diagnostics. Forecasting: Optimal forecasts, Forecasts for ARMA models, Exponential Smoothing forecasting method.

**Evaluation Criteria:** End-of-semester examination and assignments

**Suggested Readings:** Forecasting Methods and Applications (Makridakis, S. Weelwright, S. C. and Hyndman, R. J.), The analysis of Time Series: An Introduction (Chatfield, C), Forecasting and Control (Box, G. E. P., Jenkins, G. M. and Reinsell)

**ST 3067 : Quality Control (30L, 2C)**

**Syllabus:** Sampling plans of attribute type; OC curve scheme, Dodge and Romig approach, Decision theory approach, Double sampling plans, Sampling inspection by variables, Sequential sampling plans, Control charts; Variable type control charts, Attribute type control charts.

**Evaluation Criteria:** Examinations and assignments

**Suggested Readings:** Statistical Quality Control (Mahajan, M), Statistical Quality Control, (Gupta, R.C.), Quality Control and Industrial Statistics (Duncan, A.J.)