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B-SC in Statistics at Swami Ramanand Teerth Marathwada University
Nanded, Maharashtra
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About the Specialization
What is Statistics at Swami Ramanand Teerth Marathwada University Nanded?
This Statistics program at Swami Ramanand Teerth Marathwada University, Nanded, focuses on equipping students with a robust foundation in statistical theory, methods, and applications. The curriculum is designed to meet the growing demand for data-driven decision-making across various sectors in the Indian economy. It emphasizes both theoretical understanding and practical skills, making graduates highly competent for analytical roles.
Who Should Apply?
This program is ideal for 10+2 science graduates with a strong aptitude for mathematics and an interest in data analysis. It targets fresh graduates seeking entry into analytical, research, or data science roles. It also suits individuals passionate about understanding patterns in data, aspiring to contribute to evidence-based policymaking, or pursuing higher studies in statistics or related fields.
Why Choose This Course?
Graduates of this program can expect to pursue rewarding career paths in areas like data analysis, market research, quality control, biostatistics, and actuarial science in India. Entry-level salaries typically range from INR 3-6 lakhs per annum, with significant growth trajectories for experienced professionals reaching INR 10-20 lakhs+. The skills acquired align with certifications in data science tools and statistical software, enhancing employability.
Student Success Practices
Foundation Stage
Master Core Statistical Concepts- (Semester 1-2)
Dedicate time to thoroughly understand fundamental concepts of descriptive statistics, probability, and basic distributions. Regular problem-solving and conceptual clarity are crucial for building a strong base. Form study groups to discuss challenging topics and solve diverse problems together.
Tools & Resources
Textbooks by S.C. Gupta, V.K. Kapoor, Khan Academy Statistics courses, Online problem sets on GeeksforGeeks for basic statistics
Career Connection
A solid foundation in these concepts is indispensable for all advanced statistical applications, crucial for any data-related role and further academic pursuits.
Develop Programming Skills for Statistics- (Semester 1-2)
Start learning basic statistical software like R or Python alongside your theoretical studies. Practice implementing statistical formulas and data manipulations. This early exposure will bridge the gap between theory and practical application, a highly valued skill in the Indian job market.
Tools & Resources
RStudio for R programming, Anaconda for Python (with Pandas, NumPy, SciPy), Online tutorials on DataCamp or Coursera for R/Python basics
Career Connection
Proficiency in statistical programming languages is a key differentiator for entry-level data analyst and statistician positions, essential for automating tasks and handling large datasets.
Engage Actively in Practical Sessions- (Semester 1-2)
Utilize practical lab sessions to gain hands-on experience with data analysis and interpretation. Ensure you understand the ''''why'''' behind each step and can articulate your findings. Take initiative to experiment with different datasets beyond the prescribed curriculum.
Tools & Resources
Lab manuals, Datasets provided in class, Open-source datasets from Kaggle or government statistics portals
Career Connection
Practical competence in applying statistical tools directly translates into job readiness, demonstrating your ability to work with real-world data and derive actionable insights.
Intermediate Stage
Deep Dive into Inferential Statistics and Sampling- (Semester 3-4)
Focus on thoroughly understanding hypothesis testing, estimation, and various sampling techniques. Practice interpreting results and making informed decisions based on sample data. Participate in discussions on real-world survey methodologies and their limitations.
Tools & Resources
Statistical Inference by George Casella and Roger L. Berger, Online courses on inferential statistics, NPTEL lectures
Career Connection
These skills are vital for market research, quality assurance, and any role requiring drawing conclusions from samples, highly sought after in Indian analytical firms.
Undertake Mini-Projects and Internships- (Semester 3-5)
Seek out opportunities for mini-projects in your college or local companies to apply your knowledge of statistical inference and sampling. Look for internships during summer breaks with research firms, banks, or manufacturing units. This provides invaluable industry exposure and builds your resume.
Tools & Resources
University career services, LinkedIn for internship search, Networking with faculty and alumni
Career Connection
Practical project experience and internships are crucial for placements in India, showcasing your ability to apply academic knowledge in a professional setting and solving business problems.
Enhance Data Visualization and Reporting- (Semester 3-5)
Learn to effectively visualize data and communicate statistical findings through clear, concise reports. Master tools like Tableau or Power BI. Present your project work clearly, emphasizing the insights derived from data.
Tools & Resources
Tableau Public, Microsoft Power BI Desktop, Online courses on data visualization best practices, Creating effective presentations (e.g., using Canva or PowerPoint)
Career Connection
Strong communication and data visualization skills are critical for roles that involve presenting analytical results to non-technical stakeholders, increasing your value in any organization.
Advanced Stage
Specialize in Advanced Statistical Modeling- (Semester 6)
Concentrate on gaining expertise in advanced topics like econometrics, time series analysis, and multivariate techniques. Work on complex datasets requiring these methods, focusing on model building, validation, and forecasting. Understand their practical implications in various sectors.
Tools & Resources
Advanced textbooks on Econometrics/Time Series (e.g., Gujarati, Box & Jenkins), Specialized R/Python libraries (e.g., statsmodels, forecast, sklearn), Research papers and case studies
Career Connection
These specialized skills are highly valued for roles in financial modeling, risk analysis, market forecasting, and research & development within Indian industries.
Prepare a Strong Portfolio and Resume- (Semester 6)
Compile all your projects, practical assignments, and internship experiences into a well-structured portfolio. Tailor your resume to highlight your statistical skills, software proficiency, and problem-solving abilities for specific job roles. Practice interview questions related to statistical concepts and case studies.
Tools & Resources
GitHub for project display, Canva for resume design, Mock interviews with peers or career counselors, Glassdoor for company-specific interview insights
Career Connection
A compelling portfolio and resume are essential for securing placements in top companies in India, providing tangible evidence of your capabilities to potential employers.
Network and Stay Updated with Industry Trends- (Semester 6)
Attend webinars, workshops, and industry seminars related to data science and statistics. Connect with professionals on platforms like LinkedIn to understand current industry trends, emerging technologies, and job market demands. Continuous learning is key in this rapidly evolving field.
Tools & Resources
LinkedIn for professional networking, Coursera, edX for advanced certifications, Industry blogs and journals (e.g., Analytics India Magazine), Professional associations like the Indian Statistical Institute
Career Connection
Proactive networking and staying current with trends significantly boost your chances of landing desirable roles and fostering long-term career growth in the competitive Indian job market.
Program Structure and Curriculum
Eligibility:
- No eligibility criteria specified
Duration: 3 years / 6 semesters
Credits: 68 (for Statistics specialization subjects only) Credits
Assessment: Internal: 20%, External: 80%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| STC-101 | Descriptive Statistics I | Core | 4 | Introduction to Statistics, Data Collection and Presentation, Measures of Central Tendency, Measures of Dispersion, Moments, Skewness, Kurtosis |
| STC-102 | Probability and Probability Distributions I | Core | 4 | Basic Concepts of Probability, Axiomatic Approach, Conditional Probability, Bayes'''' Theorem, Random Variables, PMF, PDF, Expectation and Variance |
| STP-103 | Practical Paper I (Based on STC-101 and STC-102) | Practical | 2 | Diagrammatic/Graphical Representation, Measures of Central Tendency and Dispersion, Moments, Skewness, Kurtosis calculations, Probability Calculations, PMF/PDF Analysis |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| STC-201 | Descriptive Statistics II | Core | 4 | Correlation and its Measures, Linear Regression, Multiple and Partial Correlation, Association of Attributes, Contingency Tables |
| STC-202 | Probability and Probability Distributions II | Core | 4 | Generating Functions, Bivariate Probability Distributions, Standard Discrete Distributions (Binomial, Poisson), Standard Continuous Distributions (Uniform, Normal), Central Limit Theorem |
| STP-203 | Practical Paper II (Based on STC-201 and STC-202) | Practical | 2 | Computation of Correlation Coefficients, Fitting of Regression Lines, Analysis of Association of Attributes, Fitting of Discrete and Continuous Distributions, Parameter Estimation |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| STC-301 | Sampling Distributions and Exact Tests | Core | 4 | Sampling Distributions (t, Chi-square, F), Hypothesis Testing Concepts (Null, Alternative, Errors), Large Sample Tests (Z-test), Exact Small Sample Tests (t-test, Chi-square test), F-test for Variance Equality |
| STC-302 | Sampling Methods | Core | 4 | Census vs Sample Survey, Simple Random Sampling (SRS), Stratified Random Sampling, Systematic Sampling, Ratio and Regression Estimators |
| STP-303 | Practical Paper III (Based on STC-301 and STC-302) | Practical | 2 | Application of Large Sample Tests, Application of Exact Small Sample Tests, Estimation under SRS and Stratified Sampling, Comparison of Sampling Schemes, Ratio and Regression Estimation Problems |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| STC-401 | Statistical Inference | Core | 4 | Point Estimation, Properties of Estimators (Unbiasedness, Consistency), Efficiency, Sufficiency, Methods of Estimation (MLE, Method of Moments), Interval Estimation |
| STC-402 | Design of Experiments | Core | 4 | Basic Principles of DOE, Completely Randomized Design (CRD), Randomized Block Design (RBD), Latin Square Design (LSD), Factorial Experiments, ANOVA |
| STP-403 | Practical Paper IV (Based on STC-401 and STC-402) | Practical | 2 | Point and Interval Estimation problems, Testing Hypotheses using ANOVA, Analysis of CRD, RBD, and LSD, Estimation of Treatment Effects, Design Efficiency Comparison |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| STC-501 | Non-Parametric Tests and Reliability Theory | Core | 4 | Introduction to Non-Parametric Tests, Sign Test, Wilcoxon Signed-Rank Test, Mann-Whitney U Test, Kruskal-Wallis Test, Reliability Concepts, Hazard Rate, Mean Time To Failure (MTTF) |
| STC-502 | Official Statistics and Demographic Methods | Core | 4 | Indian Statistical System, NSSO, Census of India, National Income Statistics, Agricultural and Industrial Statistics, Price Statistics, Demographic Rates, Life Table Construction and Interpretation |
| STC-503 | Statistical Process Control | Core | 4 | Quality Control Concepts, Statistical Process Control (SPC), Control Charts for Variables (X-bar, R, S charts), Control Charts for Attributes (p, np, c, u charts), Acceptance Sampling Plans |
| STP-504 | Practical Paper V (Based on STC-501, STC-502, STC-503) | Practical | 2 | Application of Non-Parametric Tests, Analysis of Demographic Data, Construction of Life Tables, Construction and Interpretation of Control Charts, Implementation of Sampling Plans |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| STC-601 | Econometrics | Core | 4 | Introduction to Econometrics, Simple and Multiple Linear Regression Models, Assumptions of Classical Linear Regression, Problems in Regression (Multicollinearity, Heteroscedasticity), Autocorrelation, Dummy Variables |
| STC-602 | Time Series Analysis | Core | 4 | Components of Time Series, Measurement of Trend and Seasonal Variation, Cyclical and Irregular Variation, Autocorrelation and Partial Autocorrelation, Moving Average and Exponential Smoothing |
| STC-603 | Multivariate Analysis | Core | 4 | Multivariate Normal Distribution, Principal Component Analysis, Factor Analysis, Discriminant Analysis, Cluster Analysis |
| STP-604 | Practical Paper VI (Based on STC-601, STC-602, STC-603) | Practical | 2 | Econometric Model Building and Estimation, Time Series Decomposition and Forecasting, Application of Principal Component Analysis, Discriminant and Cluster Analysis, Hypothesis Testing in Multivariate Context |
