Statistics
Roadmap

Statistics Fundamentals
|
Data Collection & Sampling
|
Descriptive Statistics
|
Probability & Random Variables
|
Inferential Statistics
|
Hypothesis Testing & Regression Analysis
|
Statistical Tools & Real-World Applications
Foundation Course in Digital Marketing

Course Description

Ready to build a strong foundation in Statistics for Data, Business and Research?

This Statistics Course is designed for students, freshers and working professionals who want to understand data properly – not just formulas. You’ll learn how to collect, summarize, analyze and interpret data using statistical concepts that are heavily used in Data Analytics, Data Science, Finance, Marketing, Operations, Research and many other domains.

We start from the basics – types of data, central tendency, dispersion – and gradually move to probability, distributions, correlation, regression, hypothesis testing and practical decision-making with data. Everything is taught in simple language with real-life examples and exercises.

By the end of this course, you’ll be able to confidently work with statistics in Excel / tools, read reports, understand charts and support real business decisions. It is a perfect base for Data Analyst, Data Science, Research and MBA / Professional programs.

Comprehensive Curriculum

Descriptive & Inferential Statistics Fundamentals
Probability, Distributions & Sampling Concepts
Correlation, Regression & Relationship Analysis
Hypothesis Testing & Decision-Making with Data
Practical Case Studies using Real-World Data

What You’ll Learn from this Statistics Course?

Basics of data & variables – types of data, scales of measurement, population vs sample.
Descriptive statistics – mean, median, mode, range, variance, standard deviation & interpretation in business context.
Probability concepts – events, outcomes, basic rules, conditional probability (simple examples).
Distributions – normal distribution (bell curve), binomial & other basic distributions (conceptual level).
Correlation & regression – understanding relationships between variables, simple linear regression (basic).
Hypothesis testing – idea of null/alternative hypothesis, confidence levels, p-value and simple test interpretation (Z/t/chi-square – concept).

Why You Should Learn This?

Statistics is the language of data. Any role that uses data – from Data Analytics, Data Science, Marketing, Finance, HR, Operations to Academic Research – depends on statistics to make sense of numbers.

Without statistics, people only see raw data. With statistics, you can summarize trends, test ideas, compare options and support decisions using facts instead of guesswork.

At Skills Boost, we make statistics simple, visual and practical. Instead of only teaching formulas, we connect each concept to real-life scenarios – sales, campaigns, survey data, quality checks, etc..

With live classes, hands-on Excel/statistics exercises, practice sheets, mini projects and interview-oriented discussion, you will be comfortable using statistics in reports, dashboards, analysis and further advanced courses like Data Analytics and Data Science.

Program Curriculum

Basics of Statistics & Data Types

Descriptive Statistics & Data Summarization

Probability & Random Variables

Distributions & Sampling Concepts

Correlation & Regression Analysis

Hypothesis Testing & Confidence Intervals

Statistics with Excel / Tools (Practical)

Projects, Case Studies & Career Preparation

Tools You will learn.

Microsoft Excel for Statistics & Analysis
Spreadsheet / Data Handling Tools
Basic Data Visualization Tools & Charts
Simple Statistical Functions in Tools
Presentation Tools (PPT / Slides) for Insights
Documentation & Reporting Tools
CSV / Data Import-Export Tools
Basic Analytics / BI Tools (Concept Level)

Hiring Partners

Analytics & Data Teams (Across Industries)
Research & Survey Organizations
Consulting & Strategy Firms (Analysis Roles)
Marketing & Insights Teams (Campaign Analysis)
Financial & Risk Analysis Teams
Academic / EdTech / Research Support Roles
Startups & Product Teams (Experiment & A/B Testing Support)
Freelance & Remote Analytics Work (Global Clients)

Learning Outcomes

After successfully completing this Statistics course, learners will be ready for multiple data & analysis roles. Students can become…

Statistics Executive

Statistics & Data Analysis Executive

Junior Analyst

Junior Data / Business Analyst

Research Analyst

Research & Survey Data Analyst

MIS

MIS & Reporting Analyst (with Stats)

Insights

Marketing / Business Insights Executive

Academic Support

Academic / Research Support (Statistics)

Freelancer

Freelance Data & Survey Analyst

Next Step

Ready for Data Analytics / Data Science Programs

Fee Structure

Statistics Mastery Program

Duration: 2–3 Months (Practical Training)
Class Duration: 1.5 Hours per Session
Batch Size: Limited to 15 Students
Certification: Industry Recognized Certificate
β‚Ή15,000
β‚Ή7,999
Limited Time Offer
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Course Details

  • Duration: 3 Months
  • Timing: 7:00 PM - 9:00 PM
  • Batch Size: 25 Students

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Turn data into decisions. Build your career as a Data Analyst today!.

Mr. Ankit Kumar

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Become a Sr. Digital Marketer and lead brands to success with powerful strategies and data-driven decisions.

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Sr. Faculty Data Science

Sr. Faculty in Data Science at Skills Boost, helping learners master data-driven skills with real-world insights.

Mrs. Kavita

Digital Marketing Specialist

Kavita is a Digital Marketing Specialist at Skills Boost, skilled in SEO, SMM, and PPC, helping brands grow their online presence.

Ready to up skill yourself with Skills Boost

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Digital Marketing Mastery Course

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