Description
Course Name: Diploma in Statistics
Course Id: DIS/Q1001.
Eligibility: Completion of 10+2 (higher Secondary) or equivalent.
Objective: A Diploma in Statistics is an excellent choice for individuals interested in developing strong analytical skills and a deep understanding of statistical methods. Whether you’re looking to enhance your career in data analysis, research, or any field that involves quantitative data, this diploma provides a solid foundation in statistical theory and practical skills.
Duration: 370 Hrs (Equivalent to One Year).
Total Credits: 18.
How You will Get Diploma Certificate:
Step 1- Select your Course for Certification.
Step 2- Click on Enroll Now.
Step 3- Proceed to Enroll Now.
Step 4- Fill Your Billing Details and Proceed to Pay.
Step 5- You Will be Redirected to Payment Gateway, Pay Course and Exam Fee by Following Options.
Card(Debit/Credit), Wallet, Paytm, Net banking, UPI and Google pay.
Step 6- After Payment You will get Study Material Login id and Password on your email id.
Step 7- After Completion of Course Study give Online Examination.
Step 8- After Online Examination you will get Diploma Certificate soft copy(Scan Copy) and Hard Copy(Original With Seal and Sign).
Step 9- After Certification you will receive Prospect Job Opportunities as per your Interest Area.
Online Examination Detail:
- Duration- 120 minutes.
- No. of Questions- 60. (Multiple Choice Questions).
- 10 Questions from each module, each carry 10 marks.
- Maximum Marks- 600, Passing Marks- 40%.
- There is no negative marking in this module.
How Students will be Graded: | ||
S.No. | Marks | Grade |
1 | 91-100 | O (Outstanding) |
2 | 81-90 | A+ (Excellent) |
3 | 71-80 | A (Very Good) |
4 | 61-70 | B (Good) |
5 | 51-60 | C (Average) |
6 | 41-50 | P (Pass) |
7 | 0-40 | F (Fail) |
Benefits of Certification:
- Government Authorized Assessment Agency Certification.
- Certificate Valid for Lifetime.
- Lifetime Verification of Certificate.
- Free Job Assistance as per your Interest Area.
Diploma in Statistics
General nature and scope of statistical methods-Introduction, Definition, Statistics are aggregate of facts, Statistics are affected to a marked extent by a multiplicity of causes, Statistics are numerically expressed, enumerated or estimated, Statistics are numerated or estimated according to reasonable standard of accuracy, Statistics should be collected in a systematic manner for a predetermined purpose, Statistics should be capable of being placed in relation to each other, To simplify unwieldy and complex data.
Elementary ideas about statistical populations- Introduction, What Are Statistics, Importance of Statistics, Descriptive Statistics, Inferential Statistics, Variables, Percentiles, Levels of Measurement, Distributions, Summation Notation, Linear Transformations, Logarithms, Graphing Distributions, Graphing Qualitative Variables, Graphing Quantitative Variables, Stem and Leaf Displays, Histograms, Frequency Polygons, Summarizing Distributions, What is Central Tendency, Measures of Central Tendency.
Elementary idea of probability- Introduction, Probability, Conditional Probability and Independence, Counting, Random Variables: Distribution and Expectation, Random Vectors: Independence and Dependence, Generating Functions and Their Applications, Continuous Random Variables, Jointly Continuous Random Variables, Markov Chains.
Design and analysis of experiments- Principles and Techniques, Planning Experiments, Designs with One Source of Variation, Inferences for Contrasts and Treatment Means, Checking Model Assumptions, Experiments with Two Crossed Treatment Factors, Several Crossed Treatment Factors, Polynomial Regression, Analysis of Covariance, Complete Block Designs, Incomplete Block Designs, Designs with Two Blocking Factors, Confounded Two-Level Factorial Experiments.
Elementary theory of index numbers- Introduction, Laspeyres and Paasche indices, Symmetric Averages of Fixed-Basket Price Indices, Walsh index and theory of “pure” price index, Conclusions, Annual Weights and Monthly, Price Indices, Lowe index and midyear indices, young index, Divisia Index and Discrete, Approximations, Discrete approximations to, continuous-time Divisia index.
Statistical methods in Psychology and Education- Introduction, Some Scaling Procedures, Scaling Individual Test Items of Difficulty, Scaling of Test scores in several Tests, Percentile scaling, T- Scaling, Method of equivalent scores, Scaling of Rating or ranking to term of normal curve, Scaling of Qualitative answers to a questionnaires, Scaling of Judgements of a Number of Products- Product scale, Norms and reference groups.
Job Opportunities after completion of Diploma in Statistics course:
After completing a Diploma in Statistics program, graduates acquire analytical, mathematical, and problem-solving skills that enable them to work in various sectors such as business, healthcare, finance, and research. They can apply statistical techniques to interpret data, make forecasts, and support decision-making.
Career Options for Diploma in Statistics Graduates
1. Data Analyst
- Role: Analyze and interpret data to identify trends and patterns.
- Responsibilities:
- Preparing reports and visualizations.
- Using statistical software to process data.
- Assisting organizations in data-driven decision-making.
- Industries: IT, marketing, e-commerce, finance.
2. Statistical Assistant
- Role: Support senior statisticians in data collection and analysis.
- Responsibilities:
- Conducting surveys and experiments.
- Cleaning and organizing raw data.
- Assisting in preparing research reports.
- Industries: Government research, academia, healthcare.
3. Market Research Analyst
- Role: Study market conditions to assess potential sales of products or services.
- Responsibilities:
- Gathering and analyzing customer and competitor data.
- Designing surveys and focus groups.
- Creating reports to guide marketing strategies.
- Industries: Advertising, consumer goods, consultancy.
4. Operations Analyst
- Role: Use statistical methods to improve business operations.
- Responsibilities:
- Optimizing workflows and resource allocation.
- Analyzing operational performance metrics.
- Recommending efficiency improvements.
- Industries: Logistics, retail, manufacturing.
5. Financial Analyst (Quantitative)
- Role: Use statistics to predict financial outcomes and risks.
- Responsibilities:
- Developing statistical models for investment forecasting.
- Analyzing stock market trends.
- Assisting in budgeting and financial planning.
- Industries: Banking, insurance, investment firms.
6. Risk Analyst
- Role: Assess and quantify risks using statistical techniques.
- Responsibilities:
- Evaluating data to predict potential losses.
- Preparing risk mitigation plans.
- Working with insurance and investment teams.
- Industries: Insurance, finance, consultancy.
7. Actuarial Assistant
- Role: Help actuaries calculate insurance premiums and pension benefits.
- Responsibilities:
- Conducting statistical analysis of historical data.
- Assisting in preparing actuarial reports.
- Using statistical tools to forecast financial risks.
- Industries: Insurance, government, consulting.
8. Biostatistician (Entry-Level)
- Role: Apply statistical methods to biological and medical research.
- Responsibilities:
- Analyzing clinical trial data.
- Supporting research on public health issues.
- Collaborating with medical researchers.
- Industries: Healthcare, pharmaceuticals, NGOs.
9. Research Assistant
- Role: Assist in academic or industrial research projects.
- Responsibilities:
- Collecting, organizing, and analyzing experimental data.
- Creating statistical models for research findings.
- Contributing to technical publications.
- Industries: Universities, think tanks, R&D firms.
10. Quality Control Analyst
- Role: Ensure product quality by analyzing production data.
- Responsibilities:
- Conducting statistical quality control tests.
- Identifying defects and recommending improvements.
- Monitoring production processes.
- Industries: Manufacturing, FMCG, automotive.
Industries and Work Environments:
- Government Departments: Census, public health, economic planning.
- Healthcare: Biostatistics and clinical trials.
- Finance: Risk analysis, portfolio management.
- Education and Research: Statistical teaching and research projects.
- Corporate Sector: Business intelligence and operational analysis.
Salary Range in India:
- Entry-Level (0-2 years): ₹2.5 LPA – ₹4.5 LPA.
- Mid-Level (2-5 years): ₹4.5 LPA – ₹7 LPA.
- Senior-Level (5+ years): ₹7 LPA – ₹12 LPA or more.
Conclusion:
A Diploma in Statistics equips graduates with versatile skills to work in data-driven industries. The increasing demand for data analysis in decision-making across sectors ensures ample opportunities for career growth in this field.