Statistics Masterclass for Data Science and Data Analytics from Udemy

Starting a career in Data Science or Business Analysis ?

then this course will help you to Built a Strong Foundation of statistics for Data Science and Business Analytics

This course is Very Practical, Easy to Understand and Every Concept is Explained with an Example .

I have added real life examples to understand the applications of statistics in the field of Data Science...

We'll cover everything that you need to know about statistics and probability for Data Science and Business Analytics .

Including:

1) Levels of Measurement

2) Measures of Central Tendency

3) Population and Sample

4) Population Standard Variance

5) Quartiles and IQR

6) Permutations,Combinations

7) Intersection, Union and Complement

8) Independent and Dependent Events

9) Conditional Probability

10) Bayes’ Theorem

11) Uniform Distribution, Binomial Distribution

12) Poisson Distribution, Normal Distribution, Skewness

13) Standardization and Z Score

14) Central Limit Theorem

15) Hypothesis Testing, Type I and Type II Error

16) Students T-Distribution

17) ANOVA - Analysis of Variance

18) F Distribution

19) Linear Regression and much more...

So What Are You Waiting For ?

Enroll Now and Empower Your Career .

What's inside

Learning objectives

Understand the fundamentals of statistics
Understand the probability for data analysis
Learn how to work with different types of data
Different types of distributions
Apply statistical methods and hypothesis testing to business problems

Understand all the concepts of statistics for data science and analytics
Working of regression analysis
Implement one way and two way anova
Chi-square analysis
Central limit theorem

Understand the fundamentals of statistics
Understand the probability for data analysis
Learn how to work with different types of data
Different types of distributions
Apply statistical methods and hypothesis testing to business problems
Understand all the concepts of statistics for data science and analytics
Working of regression analysis
Implement one way and two way anova
Chi-square analysis
Central limit theorem

Syllabus

Welcome to the Course !

Introduction

Updates on Udemy Reviews

Course FAQ's

Statistics Basic

Data

Levels of Measurement

Measures of Central Tendency

Population and Sample

Measures of Dispersion

Quartiles and IQR

Probability

Introduction to Probability

Permutations

Combinations

Intersection, Union and Complement

Independent and Dependent Events

Conditional Probability

Addition and Multiplication Rules

Bayes’ Theorem

Distributions

Introduction to Distribution

Uniform Distribution

Binomial Distribution

Poisson Distribution

Normal Distribution

Skewness

Standardization and Z Score

Central Limit Theorem

Hypothesis Testing

Hypothesis Testing and Hypothesis Formulation

Null and Alternative Hypothesis

Important Concepts in Hypothesis Testing

Exercise 1

Exercise 2

Type I and Type II Error

Students T-Distribution

Exercises on Students T-Distribution

ANOVA - Analysis of Variance

F Distribution

One-Way ANOVA

Two-Way ANOVA

Two-Way ANOVA Exercise

Two-Way ANOVA with Replication

Regression Analysis

Linear Regression

Exercise on Linear Regression

Multiple Regression

Chi-Square Analysis

Chi-Square Test

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops statistics and probability skills for roles in data science and business analysis

Suitable for beginners looking to establish a solid foundation in statistical concepts

Provides practical examples to illustrate statistical concepts

Utilizes engaging teaching methods to simplify complex topics

Course objective is aligned with the industry standard

Instructor has extensive experience in statistics and data science

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Statistics Masterclass for Data Science and Data Analytics with these activities:

Brush Up on Math Skills

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Refreshes foundational math skills necessary for statistics

Browse courses on Mathematics

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Review basic algebra concepts
Practice solving equations and inequalities

Read Introduction to Probability

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Provides foundational knowledge in probability, the core topic of the course

View Introduction to Probability, Second Edition on Amazon

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Read chapters 1-3
Complete practice problems at the end of each chapter

Follow Tutorials on ANOVA

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Provides additional support and guidance in understanding the complex topic of ANOVA

Browse courses on ANOVA

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Watch video tutorials on ANOVA
Follow along with practice exercises

Five other activities

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Practice Probability Problems

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Reinforces probability concepts through repetition of exercises

Browse courses on Probability

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Solve practice problems from the textbook or online resources

Summarize Statistical Concepts

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Deepens understanding by requiring active recall and explanation

Browse courses on Statistics

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Identify key statistical concepts
Write a summary that explains these concepts in your own words

Analyze Real-World Data

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Provides practical experience in applying statistical methods to solve real-world problems

Browse courses on Data Analysis

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Choose a dataset related to your interests
Explore the data and identify potential research questions
Conduct statistical tests to test your hypotheses
Write a report summarizing your findings

Contribute to Open-Source Statistical Projects

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Provides exposure to real-world statistical applications and fosters collaboration

Browse courses on Open Source

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Identify open-source statistical projects that align with your interests
Join the project's community and contribute to discussions
Fix bugs or implement new features

Build a Statistical Model

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Challenges students to apply their knowledge and skills to a real-world problem

Browse courses on Linear Regression

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Identify a business problem that can be solved using statistical modeling
Collect and clean the necessary data
Build and train a statistical model
Evaluate the performance of the model
Deploy the model to solve the business problem

Career center

Learners who complete Statistics Masterclass for Data Science and Data Analytics will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist is a role that combines machine learning, statistics, and data analysis. The course provides a solid introduction to statistics, probability, and data analysis, as well as teaching students how to use real-world data to solve problems. This combination of skills is essential for a Data Scientist.

See salaries and explore the career path for Data Scientist

Data Analyst

Many Data Analysts use statistics to find trends and patterns in data. This course can help build a strong foundation of statistics and probability for Data Analytics. Additionally, the course describes how to work with different types of data and discusses important statistical methods such as Hypothesis Testing. These topics are all very relevant to the work of a Data Analyst.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine Learning Engineers use statistical models to build predictive models and make predictions on new data. This course provides a solid foundation in statistics and probability, which is essential for this role. The course also covers machine learning algorithms, which are used to train models to make predictions.

See salaries and explore the career path for Machine Learning Engineer

Business Analyst

A Business Analyst will need to make recommendations to business leaders to improve the organization's efficiency or profitability. The course teaches hypothesis testing which is a useful skill for evaluating new policies or products for a business. Additionally, the course teaches methods like regression analysis and ANOVA which are common tools for a Business Analyst to use.

See salaries and explore the career path for Business Analyst

Quantitative Analyst

Working as a Quantitative Analyst requires understanding probability as well as many statistical methods. The course covers distributions like the normal distribution and binomial distribution as well as diving into important statistical methods like hypothesis testing. These topics are all relevant to the work of a Quantitative Analyst. This course may be helpful to a Quantitative Analyst by strengthening their understanding of the theory behind statistical methods and by demonstrating the real life applications of statistics.

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Data Engineer

A Data Engineer is responsible for managing and processing large datasets. This course provides a foundation in statistics and probability, as well as teaches students how to use data engineering tools. This combination of skills is essential for a Data Engineer.

See salaries and explore the career path for Data Engineer

Biostatistician

A Biostatistician will need to understand the fundamentals of statistics as well as how to apply statistical methods to the field of medicine. This course covers the fundamentals of statistics and probability as well as discussing how to test hypotheses. These topics are all very relevant to the field of Biostatistics.

See salaries and explore the career path for Biostatistician

Financial Analyst

Financial Analysts use statistical methods to evaluate the performance of companies and their investments. This course provides a foundation in statistics and probability, as well as teaches students how to use financial data to make predictions. This combination of skills is essential for a Financial Analyst.

See salaries and explore the career path for Financial Analyst

Risk Analyst

Understanding probability is imperative to being a Risk Analyst. This course covers many important probability topics as well as important statistical tests. A risk analyst will use these tests to assess the likelihood of adverse events happening as well as their severity. This course may be helpful to a Risk Analyst by strengthening their understanding of probability and statistical analysis.

See salaries and explore the career path for Risk Analyst

Operations Research Analyst

Operations Research Analysts use statistical and mathematical techniques to improve the efficiency of organizations. This course provides a foundation in statistics and probability, which is essential for this role. The course also covers optimization techniques, which are used to find the best solution to a problem.

See salaries and explore the career path for Operations Research Analyst

Insurance Analyst

Insurance Analysts evaluate risk and exposure to determine the amount of insurance coverage necessary for an individual or group. The course covers important probability topics as well as probability distributions. An Insurance Analyst will use these concepts when determining the premiums for insurance policies.

See salaries and explore the career path for Insurance Analyst

Actuary

Actuaries use mathematics, statistics, and financial theory to assess risk and uncertainty. Understanding probability is essential to this role. This course covers many important probability topics that are relevant to the work of an Actuary. Additionally, the course discusses statistical methods like regression analysis which is also relevant to the field.

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Market Research Analyst

Market Research Analysts collect, analyze, and interpret data about customers, markets, and products. This course teaches students how to collect and analyze data, as well as how to interpret the results. Hypothesis testing is also covered, and this is useful for testing the effectiveness of new marketing campaigns.

See salaries and explore the career path for Market Research Analyst

Software Developer

Software Developers use statistical methods to improve the performance and reliability of their software. This course provides a foundation in statistics and probability, which is essential for this role. The course also covers topics like testing and optimization, which are used to ensure that software meets performance requirements.

See salaries and explore the career path for Software Developer

Statistician

A Statistician will need to understand the fundamentals of statistics including probability. One important job of a statistician is to design experiments. Many of the fundamentals of probability and statistical analysis are useful in setting up an experiment that will provide statistically valid results. This course may be helpful to a Statistician by strengthening their foundation of statistics and understand the application of statistical methods for solving real-world problems.

See salaries and explore the career path for Statistician