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Inferential Statistics Online Courses

Make data-driven decision with Inferential Statistics courses. Master concepts such as hypothesis testing, confidence intervals, and statistical significance to make informed decisions from data at your own convenience with expert support.

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Overview of Learning Inferential Statistics Courses with upGrad

Inferential statistics represent “a branch of statistics that concludes about a population through sample analysis”. It is important because it allows data scientists to predict, test hypotheses, and quantify uncertainty in results. Unlike descriptive statistics, which simply describe or summarize data, inferential statistics help you in making informed decisions with the help of data.

Importance of Learning Inferential Statistics

  • Enables Data-Driven Decisions: Helps you generalize findings from a sample to a larger population.
  • Core Skills in Data Science & Data Analytics: It's essential for model building, A/B testing, and validating business assumptions.
  • Supports Predictive Analysis: Uses statistical inference methods to make predictions and decisions in the face of uncertainty.
  • Sharpens Critical Thinking: Teaches you how to approach problems methodically and question assumptions using data.
  •  High Industry Relevance: Widely used in finance, healthcare, marketing, policy research, and tech-driven industries.
  •  Builds Foundation for Advanced Stats & ML: A must-have before diving into machine learning, regression models, and AI applications.

upGrad is among the best platforms for learning inferential statistics through their Data Science and Analytics programs, which are developed in association with world-class universities and companies. These programs consist of project-based learning, mentorship, and certification. Regardless of whether you’re looking for the best statistics course for data science or an introductory statistics online course, upGrad will set you up with the tools, ideas, and hands-on experience required for success in the analytics field.

Who Should Take Inferential Statistics Online Courses

  •  Beginners Exploring Data Science: For those new to it, an inferential statistics course provides a great basis for statistical thinking.
  •  Professionals Looking to Upskill: Best suited for business, marketing, finance, and tech professionals interested in learning how inferential statistics is applied to decision making.
  •  Career Switchers into Analytics: Moving into data science? These statistics courses prepare you with fundamental tools to analyze data in the world.
  • Future Data Scientists & Analysts: Take the best statistics course for data science to learn how to perform the inferential statistics steps, such as hypothesis testing and confidence intervals.
  • Researchers and Academics: Reinforce your thinking and make logical inferences through the significance of inferential statistics.
  •  Anyone Seeking Flexibility: Learn at your own pace with flexible courses on inferential statistics online offered by some of the United States’ leading universities.

What Will You Learn in upGrad’s Inferential Statistics Online Courses?

upGrad’s data science and analytics courses feature high-quality courses in inferential statistics, and the company partners with leading Indian and global universities to do so. These classes have excellent value if you are a newcomer wanting to learn the basics or a professional seeking to take courses to refine your abilities in statistical analysis.

These inferential statistical skills are provided in top programs such as:

These inferential statistics classes prepare you to deal with issues that are important when analyzing data in the real world:

  • Hypothesis Testing: Discover how to test hypotheses with t-tests, chi-square tests, and ANOVA methods.
  • Confidence Intervals: Learn how confidence levels are used to estimate population parameters.
  • Probability Distributions: Dive into normal, binomial, and Poisson distributions for predictive modeling.
  • Application of Inferential Statistics: Apply statistical inference to make conclusions from datasets and data-driven business, healthcare, and tech industry decisions.
  • Sampling Techniques: Learn how to conduct the steps of inferential statistics, such as sampling design and reducing error.
  • Python & Statistical Libraries: Implement your learning with Python libraries such as SciPy and statsmodels for statistical analysis.
  • Statistical Significance in Business Scenarios: Learn how to understand p-values and statistical significance in actual decision-making situations.
  • Industry-Driven Projects: Use inferential statistics in problem-solving for industries such as marketing, finance, and operations.

Data Science Course Instructors

Learn From The Best

Learn Data Science fundamentals from expert instructors who help you excel in your careers by imparting cutting-edge analytics and machine learning skills.

8

Instructors

10

Industry Experts

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Debabrata Das

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Director, IIITB

Dr. Debabrata Das is Director of IIITB. He has received his PhD from IIT-KGP. His main areas of research are IoT and Wireless Access Network 

IIITB Profile
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Prof. Dhiya Al-Jumeily

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Professor - Artificial Intelligence

A senior member of the IEEE and a chartered IT Professional, he is a fellow of the UK Higher Education ACademy 

LJMU Profile
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Prof. G. Srinivasaraghavan

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Professor

Prof. Srinivasaraghavan has a PhD in Computer Science from IIT-K and 18 years of experience with Infosys and several other MNCs. 

IIITB Profile
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Dr. Atif Waraich

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Faculty - Computer Science

A Senior faculty of Engineering and Technology at LJMU who has multiple publications in the health care domain 

LJMU Profile
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Chandrashekar Ramanathan

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Dean Academics

Prof. Chandrashekar has a PhD from Mississippi State University and experience of over 10 years in several multinational organisations. 

IIITB Profile
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Prof. Paulo Lisboa

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Head of Dept - Applied Mathematics

Studied mathematical physics at LU and was the chairman of Industrial Mathematics at KMJU in 1996 and Head of Graduate School in 2002 

LJMU Profile
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Dr. Gabriela Czanner

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Faculty - Engineering and Technology

A Senior lecturer at Department of Applied Mathematics at LJMU. Her research focus is advanced statistics for decision support 

LJMU Profile
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Tricha Anjali

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Ex-Associate Dean

Prof. Anjali has a PhD from Georgia Institute of Technology as well as an integrated MTech (EE) from IIT Bombay. 

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Data Science Projects

Learn by Doing

Our data science online certification programs have projects to apply theoretical knowledge in practical scenarios, helps you to tackle real-world problems.

16+

Industry projects to choose from

Slide 1 of 17

In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to analyse the patterns present in the data. This will ensure that the applicants are capable of repaying the loan are not rejected.

Data Visualisation

Data Analysis

Data Interpretation

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Credit EDA Assignment

In this assignment, you will work for a consumer finance company which specialises in lending various types of loans to urban customers and use EDA to… Know More

Skills learned

Data Cleaning

Data Visualisation

Data Analysis

Data Interpretation

MySQL Queries

Data Manipulation

Data Analysis

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RSVP Case Study

In this assignment, you will work on a movies dataset using SQL to extract exciting insights about popular films and the factors that drive a film. 

Skills learned

MySQL

MySQL Queries

Data Manipulation

Data Analysis

ML Modelling

Model Evaluation

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Bike Sharing Assignment

Build a regression model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue. 

Skills learned

Linear Regression

ML Modelling

Model Evaluation

In this case study, the company requires you to build a machine learning classification model wherein using some demographics and behavioral data of the leads (potential buyers), it will be able to identify the ones most likely to convert.

Decision Trees

Classification

ML Modelling

Model Evaluation

Business Problem Solving

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Lead Scoring Case Study

In this case study, the company requires you to build a machine learning classification model wherein using some demographics and behavioral data of t… Know More

Skills learned

Logistic Regression

Decision Trees

Classification

ML Modelling

Model Evaluation

Business Problem Solving

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a business analyst.

Tree Models

Model Selection

Feature Engineering

Classification

ML Modelling

Model Evaluation

Business Problem Solving

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Model Selection Case Study - Telecom Churn

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customer… Know More

Skills learned

Logistic Regression

Tree Models

Model Selection

Feature Engineering

Classification

ML Modelling

Model Evaluation

Business Problem Solving

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a data scientist.

Tree Models

Boosting

Model Selection

Regularization

Feature Engineering

Classification

ML Modelling

Model Evaluation

Business Problem Solving

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Advanced ML Case Study - Telecom Churn

Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customer… Know More

Skills learned

Logistic Regression

Tree Models

Boosting

Model Selection

Regularization

Feature Engineering

Classification

ML Modelling

Model Evaluation

Business Problem Solving

Lexical Processing

Regex

POS Tagging

Dependency Parsing

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Syntactic Processing Assignment

Use the techniques such as POS tagging and Dependency parsing to extract information from unstructured text data. 

Skills learned

Natural Language Processing

Lexical Processing

Regex

POS Tagging

Dependency Parsing

Sqoop

Redshift

Spark

ETL Pipeline

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ETL Project

Make use of Sqoop, Redshift & Spark to design an ETL data pipeline. 

Skills learned

AWS

Sqoop

Redshift

Spark

ETL Pipeline

Analyse movie data from the past 100 years and find out various insights to determine what makes a movie do well. Use data manipulation, slicing, and various other dataframe operations to successfully find usable insights from the movies.

Data Processing

Data Visualisation

Data Analysis

Dashboarding

Data Storytelling

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IPL Visualization Assignment

Analyse movie data from the past 100 years and find out various insights to determine what makes a movie do well. Use data manipulation, slicing, and … Know More

Skills learned

Tableau/Power BI

Data Processing

Data Visualisation

Data Analysis

Dashboarding

Data Storytelling

Linear Regression

ML Model Evaluation

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Advanced Regression

Build a regularized regression model to understand the most important variables to predict 

Skills learned

ML Modeling

Linear Regression

ML Model Evaluation

Hadoop

MapReduce Programming

mrjob

Linux

Sqoop

Apache HBase

SQL

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MapReduce Programming Assignment

Perform MapReduce Programming in a big data environment on a large dataset. 

Skills learned

AWS

Hadoop

MapReduce Programming

mrjob

Linux

Sqoop

Apache HBase

SQL

Big Data with Spark

PySpark

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Big Data Case Study

Understand how a big data project in the industry is taken up and solved through a comprehensive big data case study on cloud. 

Skills learned

AWS

Big Data with Spark

PySpark

Python

Data Analysis

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SQL & Python Lab

Solve intensive programming questions in a competitive lab environment to showcase and evaluate your SQL and Python coding skills. 

Skills learned

SQL

Python

Data Analysis

Understand the factors that drive the Airbnb business and help the team leads tackle problems and bottlenecks through extensive data analysis on UI tools.

Data Storytelling techniques

Data Visualisation

Tableau

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Airbnb Case Study

Understand the factors that drive the Airbnb business and help the team leads tackle problems and bottlenecks through extensive data analysis on UI to… Know More

Skills learned

Data Analysis

Data Storytelling techniques

Data Visualisation

Tableau

Spark

Spark Streaming

Apache Kafka

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Retail Project

Build an end-to-end real-time data processing application using Spark Streaming and Kafka. 

Skills learned

AWS

Spark

Spark Streaming

Apache Kafka

Domain understanding

Data Analysis

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Business Case Study

Understand how data projects are taken up in the industry and implement the steps required to successfully manage and complete a data project. 

Skills learned

Business Problem Solving

Domain understanding

Data Analysis

In this assignment, you will build a complete neural network using Numpy. You will implement all the steps required to build a network - feedforward, loss computation, backpropagation, weight updates etc. You will use the MNIST dataset to train your model to classify handwritten digits between 0-9.

Neural Networks

PyTorch

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NN Assignment

In this assignment, you will build a complete neural network using Numpy. You will implement all the steps required to build a network - feedforward, … Know More

Skills learned

Deep Learning

Neural Networks

PyTorch

Career Paths After Completing an Inferential Statistics Course

Inferential statistics is practiced  in sectors like healthcare, finance, e-commerce, and consulting.Mastering these techniques empowers you to make informed, data-driven decisions and predictions based on sample data.

If you're on the hunt for a well-organized, expert-led online statistics course, upGrad’s top statistics courses for data science strike a perfect balance between theoretical knowledge and real-world relevance. These courses delve into key inferential statistics concepts such as hypothesis testing, confidence intervals, regression analysis, and much more.

upGrad’s Top Data Analysis Courses Featuring Inferential Statistics Skills:

1. IIIT Bangalore’s Executive Diploma in Data Science & AI 

 This is a 12-month comprehensive program designed specifically for working professionals. It covers both descriptive and inferential statistics, along with Python, SQL, and machine learning, equipping you to create end-to-end data solutions.

2. Business Analytics & Consulting Program with PwC India

Perfect for those eager to master the application of inferential statistics in real-world consulting scenarios. This 3-month course emphasizes hands-on problem-solving in business contexts.

3. Professional Certificate Program in AI and Data Science with PwC via upGrad 

This bootcamp is crafted for immediate impact in the industry. You’ll learn to apply inferential statistics using tools like Python and SQL, while also developing predictive models and tackling real business challenges.

These inferential statistics courses are perfect for anyone who wants to grasp not just what the data reveals, but also the reasoning behind it-and how to make trustworthy predictions based on sampled information.

Top Career Paths After Completing Data Analysis Courses

Completing a data analysis or inferential statistics course with upGrad can pave the way to several high-growth roles:

  • Data Analyst: ₹4 to ₹9 LPA
  • Business Analyst: ₹6 to ₹13 LPA
  • Data Scientist: ₹7 to ₹17 LPA
  • Data Engineer: ₹6 to ₹14 LPA
  • Product Analyst: ₹8 to ₹16 LPA
  • Analytics Consultant: ₹11 to ₹18 LPA
  • Statistician: ₹3 to ₹8 LPA 
  • Quantitative Analyst (Quant): ₹12.5 - 24 LPA

Source: Glassdoor

Placements in Data Science Courses

Our Placement Numbers

Excel in data-driven careers with our certification in Data Science, boasting a high rate of successful student placements. Get hired by top companies.

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Average Salary Hike
₹1.23 Cr
Highest Salary Offered
6000+
Career Transitions
300+
Hiring Partners

Top Recruiters

Tech Mahindra
Amazon
Tata
Wipro
Microsoft
TCS
Infosys
Flipkart
IBM
HDFC Bank
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Success Stories

What Our Learners Have To Say

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upGrad's student mentor played a very importany role in my learning journey

upGrad's student mentors played a crucial part in my learning journey. I followed them and they helped a lot in clarifying my queries related to my online data science course. They also gave me placement assistance as a part of my data science course, where they perfectly guide you on how to start a career as a Data Analyst.

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Abhinay Bandaru

Product Analyst, Head Infotech

3 Years of Experience

The upGrad's placement drive helped me to secure a job in MNC

My online data science course's content was so well-structured that it helped me grasp concepts that were entirely new to me. Thanks to upGrad's placement drive, I was able to secure a job at Kantar Analytics.

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Bhagvathi

Data Analyst, Kantar

1 Year of Experience

Additional benifits of upGrad helped a lot in terms of gaining practical exposure

upGrad's online data science courses are truly amazing. The mentorship through industry veterans, BaseCamps, and student mentors makes the programme extremely engaging. I Would definitely endorse the data science programme for its rich content and comprehensive approach to Data Science.

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Moulik Srivastava

Technology Project Manager & Commercial Strategy Associate, Victory Farms

5 Years of Experience

Being online, it was like a university experience

Learning with upGrad for my data science course was like going back to University for me. Their data science certification, career support and mentorship calls really helped me switch to a career in the field of Data Science.

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Data Scientist, Scaler

7 Years of Experience

Structured and easy curriculumn

The curriculum of the data science online course is very structured and easy to consume. The mock calls and encouraging words from the CEO before my interview were extremely encouraging. One of the best online data science course there is in the market

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Aishwarya Ramachandran

News Analyst, Thomson Reuters

6 Years of Experience

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Begin your Data Science journey with our free introduction to data analytics courses, a perfect starting point for analytical upskilling.

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Uncover the basics of NLP and other topics like RegEx for building tools for Spam Detection, Phonetic Hashing and Spell Correction in this introductory course

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Learn about vectors, linear transformations, matrices, eigenvalues and eigenvectors in Linear Algebra as you build a solid foundation for analytics with this course

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Improve your understanding of SQL as you learn about window functions, partitioning, query optimisation, case statements, stored functions & more in this course

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Learn all about database design and the basics of MySQL using MySQL Workbench in this beginner-friendly course

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Learn about the various types of hypotheses, Decision-making criteria, critical value and p-value methods for testing Hypothesis.

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This data analytics course will help you learn how to use a random sample data to describe and make inference about the population.

15 Hours

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Unsupervised Learning: Clustering

Learn the fundamentals of clustering in unsupervised learning as you introduce yourself to Clustering, K-Means Clustering Hierarchical Clustering, and its execution

11 Hours

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Logistic Regression for Beginners

The course covers the concept of Logistic Regression and its applications in the industry.

17 Hours

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Linear Regression - Step by Step Guide

Learn the basics of simple and multiple linear regression, and their relevance in various industries.

21 Hours

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Learn Python Libraries: NumPy, Matplotlib and Pandas

Learn about the three most important and popular Python libraries for handling data: NumPy, Matplotlib and Pandas.

15 Hours

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Learn Basic Python Programming

Solve coding questions based on Lists, Strings and other data structures like tuples, sets and dictionary to improve your problem solving abilities with Python

12 Hours

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Programming with Python: Introduction for Beginners

Learn about control statements, basic data structures, and OOP concepts in Python programming with this beginner-friendly course

13 Hours

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Learn to formulate key business strategies, optimise resources and take key decisions to solve any business problem in this introductory course

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Learn the real-world applications of data analytics by analysing data patterns, documenting insights, and visualising data to tell a story

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Learner Support and Services

How Will upGrad Supports You

Industry Mentors

    Receive unparalleled guidance from industry mentors, teaching assistants, and graders

    Receive one-on-one feedback from our seasoned data science faculty on submissions and personalized feedback to improvement

    Our Data Science Syllabus is designed to provide you with ample of industry relevant knowledge with examples

Why Choose upGrad for Inferential Statistics Online Courses?

upGrad provides various courses in the domain of data science, and such includes inferential statistics too. Here’s a comparison table showing why upGrad stands out for inferential statistics online courses when compared to other institutes. 

Feature/Criteria

upGrad

Other Institutes

Course Structure

Comprehensive inferential statistics course integrated with real-world case studies and applications

Mostly theoretical; lacks real-world application of inferential statistics

University Collaborations

Top Indian and global universities like IIIT Bangalore, LJMU, OP Jindal

Limited or local institute tie-ups

Certifications

Industry-recognized certifications in statistics courses and data science

Generic certifications with lesser brand value

Industry Projects

Includes hands-on capstone projects focused on inferential statistics steps

Fewer projects or mostly academic in nature

Career Support

1:1 mentorship, resume building, and career assistance

Minimal or no dedicated career support

Tools & Languages

Training on tools like Python, SQL, Tableau for application of inferential statistics

Limited tool exposure, mostly Excel or R

Faculty Expertise

Taught by top academicians and industry experts

Faculty with less industry experience

Learning Format

100% statistics online course with flexibility for working professionals

Fixed schedules and less flexibility

Specialization

Covers all core topics including importance of inferential statistics, data visualization, and hypothesis testing

Focused on only basic statistical methods

Best For

Freshers, professionals, and career switchers looking for the best statistics course for data science

Mainly suitable for academic learners only

Frequently Asked Questions about Inferential Statistics

1. Am I allowed to finish the inferential statistics course on my own terms?

Yes! This online course in statistics has been crafted to accommodate your lifestyle. You can study at your convenience, anytime and anywhere, and take a break whenever required-suited for students and professionals alike.

2. What are the subjects taught in an online inferential statistics course?

An inferential statistics course cover key topics like hypothesis testing, confidence intervals, z-tests, and t-tests, and real-world use of inferential statistics. It also delves into how these techniques enable data-driven decision-making, particularly in areas like data science and business analytics.

3. Does the course emphasize theory or applications in the real world?

Both, but with a focus on real-world learning. The use of inferential statistics is illustrated using case studies, industry data sets, and in-class projects.


4. What is inferential statistics?

Inferential statistics enables you to make educated guesses about a population from a sample. It's a crucial subject in any course on inferential statistics and an important skill in data analysis and research.


5. What are the 4 kinds of inferential statistics?

The four major kinds are:

  • Hypothesis testing
  • Confidence intervals
  • Regression analysis
  • ANOVA (Analysis of Variance)

These are fundamentals of every high-level statistics course.


6. Why is inferential statistics crucial?

It's the foundation of data-driven decision-making. The significance of inferential statistics is that it can handle limited data and yet offer useful insights in the fields of business, healthcare, marketing, and research.


7. How will I enhance my career through this inferential statistics course?

You'll develop practical skills in statistical techniques applied in all industries. These skills lead to careers such as Data Analyst, Statistician, and Market Researcher-making it the best statistics course for data science.


8. Do I get a certificate after completing the course?

Yes. You'll be awarded an industry-approved certificate, validating your expertise to use inferential statistics in actual cases.


9. Is the Inferential Statistics course free?

Yes! upGrad provides this inferential statistics course free of cost, along with a free certification on successful completion. It's an excellent chance to establish good fundamentals in statistics without paying a single rupee.


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  1. The above statistics depend on various factors and individual results may vary. Past performance is no guarantee of future results.

  2. The student assumes full responsibility for all expenses associated with visas, travel, & related costs. upGrad does not .