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BSc Statistics: Course details, Syllabus and Subjects

Bachelor of Statistics course is a three-year undergraduate programme that covers a wide range of topics, including survey sampling, numerical analysis, probability and statistical methods, and other subjects that are essential to evaluating statistical data and resolving statistical problems.

Descriptive statistics, quantitative analysis, probability distributions, population demographics, and other areas are among the topics covered in the core and elective sections of the B.Sc Statistics syllabus.

What is BSc Statistics?

An undergraduate degree programme in statistics with an emphasis on statistical theory, methods, and applications is called a B.Sc Statistics programme. A bachelor's degree in statistics teaches students how to gather, evaluate, comprehend, and present data so they can make defensible decisions in a variety of domains, including business, economics, social sciences, medicine, and more.

Mathematical statistics, probability theory, regression modelling, experimental design, multivariate analysis, and computational statistics are common subjects included in a B.Sc Statistics programme. In order to analyse data effectively, students also learn how to use statistical software programmes like R, Python, SAS, or SPSS.

Graduates with a bachelor's degree in statistics can work in a variety of sectors, such as finance, healthcare, research, econometrics, government, marketing and actuarial analysis, as statisticians, data analysts, research analysts, or actuarial analysts. 

BSc Statistics Course Highlights

The following are the highlights of a B.Sc Statistics programme:

  • Essential statistical theories: Students study basic statistical ideas such as mathematical statistics, probability theory, and data analysis techniques. The programme places a strong emphasis on developing students' practical abilities through hands-on experience with statistical software tools such as R, Python, or SAS. This allows students to analyse real-world data sets and acquire valuable knowledge.
  • Specialised electives: To customise their education to particular job trajectories, students can select optional courses according to their interests, such as time series analysis, biostatistics, econometrics, or machine learning.
  • Research projects: A lot of programmes include research projects or internships where students work with industry partners or academic institutes to analyse data or apply statistical methods to solve real-world problems.
  • Interdisciplinary approach: Students pursuing a bachelor's degree in statistics can apply statistical methods to a variety of disciplines, including business, economics, psychology, and biology. These programmes frequently incorporate integrated courses.
  • Faculty expertise: Students gain from studying under experienced teachers with deep expertise in statistical theory, technique, and applications. These professors often offer helpful mentoring and advice.
  • Career preparation: The curriculum prepares students for graduate-level work in statistics or related subjects as well as careers as statisticians, data analysts, research analysts, or statisticians in a variety of businesses.
  • Critical thinking skills: Through assignments and projects, students gain the analytical, critical thinking, and problem-solving abilities necessary to solve complicated problems and make decisions based on data.

BSc Statistics Subjects

The B.Sc Statistics syllabus has been laid out semester by semester in the table below.

SEMESTER

SUBJECTS

Semester 1

  • Inequalities
  • Equations theories, Fundamental theorem of algebra and its consequences.
  • Demoivre’s theorem

Semester 2

  • Review of Differential Equations
  • Differential Calculus
  • Review of integration and definite integrals

Semester 3

  • The expectation of random variables and their properties
  • Random Variables
  • Probability Theory
  • Measures of location (or central tendency) and dispersion
  • Statistical Methods

Semester 4

  • Time Series
  • Mathematical Finance
  • Utility and Production Functions
  • Demand Analysis
  • Index Numbers

Semester 5

  • Fundamental theorem of algebra and its consequences
  • Stratified random sampling
  • Basic sampling methods
  • Sample Surveys

Semester 6

  • General Linear models
  • Numerical integration
  • Inverse interpolation
  • Numerical Analysis

BSc Statistics Syllabus

The following topics are primarily covered in the syllabus of the B.Sc Statistics course:

Subjects

Topic

Biostatistics

The function of survival time, progressive, random censoring, risk theory, stochastic epidemic models, planning and design of clinical trials.

Eco metrics

The objective behind eco metric models, general linear model, autocorrelation, forecasting.

Stochastic processes

Definition, classification and illustration of stochastic processes, Markov chain definition, Poisson process.

Linear Model

General linear model, analysis of variance, straight line relationship between two variables.

Statistical inference

Estimation, interval estimation, testing hypothesis.

C language

History and features of C language, control statement, String function use, Storage class, files

Applied Statistics

Index number, Demand Analysis, Utility and production functions, mathematical finance, time series, statistical quality control, sampling inspection plan, Indian official Statistics, Visual statistics, demography, educational and psychological statistics

Sample Survey

Sample survey, Basic sampling method, stratified random sampling

Data Science

Data analysis, visualisation, regression, predictive modelling, interpretation

Abstract mathematics

Linear transformation, theorem of intermediate value, extreme value, inverse function

Probability Analysis

Sample spaces, independence, continuous probability, distributions

Proof and Problem-solving.

Mathematical analysis, proofreading techniques, hands-on different types of problem

Calculus

Functions, limits, Derivatives, exponents, logarithms, differentiation, integration

Algebra

Vectors, Matrices, Equitation systems, Eigenvalues, linear independence, spans, orthogonally

Specialisation in B.Sc Statistics

With a B.Sc in Statistics specialisation, students enhance their knowledge and proficiency in specific areas of statistics through specialised coursework and electives, such as:

  1. Statistical Biology: The field of biostatics develops biologically relevant statistical skills. In this sense, a three-year honours programme in statistical biology leads to a bachelor's degree. However, a broad range of mathematical and statistical techniques and their applications in biology are covered in this course's curriculum.
  2. Computational Biology: Numerous medical subjects are covered by the study of biology, such as cellular functions, illness treatment, and human anatomy. The objective of computational biology is to use mathematical and computational methods to solve complicated biological and biomedical problems.
  3. Quantitative Finance:  The use of mathematics, statistics, scientific computers, and finance to financial trading and investment activities is known as quantitative finance. This is done through computer programming. However, the training offers the chance to train as a quantitative analyst.
  4. Data Science: The modelling, evaluating, and interpreting of actual data—which is necessary for business, research, and the economy—are taught in this degree programme, together with practical experience. The theoretical and practical elements of modern statistics are also covered. The degree programme covers basic statistics, probability, and mathematics during the first two years.
  5. Decision Analytics: This course was developed with the fundamentals of modern data analytics in mind. However, this training provides a sophisticated fact-finding approach to handling difficult circumstances and making decisions. Both theoretical and practical current statistics are covered in the course.
  6. Statistics and Applied Mathematics: This course is intended to address real-world problems of a scientific or decision-making character using logic and mathematics. It helps students develop into self-sufficient learners who are prepared for prosperous careers in research, business, and academia.
  7. Bioinformatics:  Bioinformatics, the study of gathering and analysing complex biological data, including genetic coding, is offered as a bachelor's degree programme. It is a field where the interface of biology, computers, and statistics is used in organism biology, molecular biology, and biomedicine.
  8. Financial Mathematics: An undergraduate degree which results in a bachelor's degree in financial mathematics provides employment in banking and business. The curriculum for this course emphasises applying mathematical principles to financial situations in order to develop mathematical abilities.

Jobs after B.Sc Statistics

After earning a bachelor's degree in statistics, you have two options: continue your studies or launch your career. Following the course, those who choose to seek full-time work opportunities can primarily find themselves in fields such as finance, banking, education, research and development, etc.

Job Position

Salary Offered per year (INR)

Credit Control Executive

5,00,000

Analyst- Broking

5,50,000

Financial Accountant

6,00,000

Project Assistant

3,50,000

Assistant Audit Officer

4,00,000

Research Officer

6,00,000

Research Associate 

5,00,000

Senior Analyst

6,50,000

Analyst

6,00,000

Financial Analyst

8,00,000

Data Analyst

7,00,000

Takeaway

Are you prepared to use your B.Sc in Statistics to turn data into insights? We at AECC are available to help you on your path to becoming a statistics expert. Contact us today and look into top courses that lead to an exciting profession in statistics.

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