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Description

If you take a lot of exams in school, how do you measure your actual performance? How do you compare yourself to other students? Who is the best basketball/soccer/baseball/… player of all times? If you take a blood test and you have values that are higher than the average, should you be worried? All these things are based on descriptive statistics. It is the art of taking lots of information, down to one small number: either the average/median or standard deviation.

Let us take it to a next step. You are a store manager with only one good in your shop. You have monthly data on the sales and the price. If you increase the price, sales drop by X%. If you decrease the price, sales drop by X%. How wonderful would it be that you drew some sort of line (ps: it’s a regression line) that would fit the data well. Why? Because you get a more educated guess what will happen your sales if you change the price. You are in the area of regression models.

Let us take it (many steps) further. You have data on stock prices and other variables. Can you construct some sort of model that will give you an estimate/prediction of the stock price tomorrow, based on the values of certain variables today. Who wouldn’t want that? You can do this via several methods: predictive analysis, markov swithcing models, nonlinear regression models,… The list is endless and the possibilities are endless (although they are more advanced). It can also be interesting just to see how variables relate to one another (but this is not nearly as profitable as the first example).

Why is statistics important? It is based on two elements: inference and prediction. If you are interested in how variables are connected with each other and how the relations are, you have inference. If you want to predict future values, you are obviously in the area of prediction. That is the reason why one would estimate the function of some sort of data set.

How do you make a decision? We use our gut some, but ideally, we want it to be based on information. Data is important, because sometimes our gut is very very wrong. But also, the more you understand statistics, the better your gut feelings get.

First we have to learn how to gather information. If you gather the information incorrectly, it’s worthless. 

Once you learn how to collect good data, how do we organize it? How do we summarize and describe it in a way that becomes meaningful and easier to deal with? How do we visualize it?

Now that we have our information and we’ve organized it, what conclusions can be drawn? A set of numbers can tell many different stories, how do you make it tell the truth? What are its limitations? What additional information do we need to make our decision?

Sure, there are areas where statistics is used more formally. Namely business, science, and engineering. But really any time there are decisions to be made, whether they’re personal decisions or professional ones, a solid understanding of statistics can ultimately help you make better ones.

The bottom line is that statistics education can be tailored to your unique path. The first step is simply enrolling in a statistics course, whether you’re a high school or college student, and then opening yourself to its power and potential.

So, welcome to this course on Statistics. We will guide you through all the concepts and make sure that you will in Statistics by the end of this course, along with thorough practice.

Let's get started.


Who is the target audience?
  • Anyone who is interested in learning statistics extensively starting from basics.
  • Anyone who wants build their career as a Statistician or a Data Scientist
  • Anyone who wants improve their Statistic and Math knowledge so that it would be useful in whatever field they work in.
Read more
Description

If you take a lot of exams in school, how do you measure your actual performance? How do you compare yourself to other students? Who is the best basketball/soccer/baseball/… player of all times? If you take a blood test and you have values that are higher than the average, should you be worried? All these things are based on descriptive statistics. It is the art of taking lots of information, down to one small number: either the average/median or standard deviation.

Let us take it to a next step. You are a store manager with only one good in your shop. You have monthly data on the sales and the price. If you increase the price, sales drop by X%. If you decrease the price, sales drop by X%. How wonderful would it be that you drew some sort of line (ps: it’s a regression line) that would fit the data well. Why? Because you get a more educated guess what will happen your sales if you change the price. You are in the area of regression models.

Let us take it (many steps) further. You have data on stock prices and other variables. Can you construct some sort of model that will give you an estimate/prediction of the stock price tomorrow, based on the values of certain variables today. Who wouldn’t want that? You can do this via several methods: predictive analysis, markov swithcing models, nonlinear regression models,… The list is endless and the possibilities are endless (although they are more advanced). It can also be interesting just to see how variables relate to one another (but this is not nearly as profitable as the first example).

Why is statistics important? It is based on two elements: inference and prediction. If you are interested in how variables are connected with each other and how the relations are, you have inference. If you want to predict future values, you are obviously in the area of prediction. That is the reason why one would estimate the function of some sort of data set.

How do you make a decision? We use our gut some, but ideally, we want it to be based on information. Data is important, because sometimes our gut is very very wrong. But also, the more you understand statistics, the better your gut feelings get.

First we have to learn how to gather information. If you gather the information incorrectly, it’s worthless. 

Once you learn how to collect good data, how do we organize it? How do we summarize and describe it in a way that becomes meaningful and easier to deal with? How do we visualize it?

Now that we have our information and we’ve organized it, what conclusions can be drawn? A set of numbers can tell many different stories, how do you make it tell the truth? What are its limitations? What additional information do we need to make our decision?

Sure, there are areas where statistics is used more formally. Namely business, science, and engineering. But really any time there are decisions to be made, whether they’re personal decisions or professional ones, a solid understanding of statistics can ultimately help you make better ones.

The bottom line is that statistics education can be tailored to your unique path. The first step is simply enrolling in a statistics course, whether you’re a high school or college student, and then opening yourself to its power and potential.

So, welcome to this course on Statistics. We will guide you through all the concepts and make sure that you will in Statistics by the end of this course, along with thorough practice.

Let's get started.


Who is the target audience?
  • Anyone who is interested in learning statistics extensively starting from basics.
  • Anyone who wants build their career as a Statistician or a Data Scientist
  • Anyone who wants improve their Statistic and Math knowledge so that it would be useful in whatever field they work in.
  • Student should have basic math knowledge
  • Students who are not from a mathematical background can also take this course, but they just might have to do some prework to easily understand the lectures
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Good to know

Know what's good
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Introduces topics from the basics, great for beginners
Provides a strong foundation for professionals transitioning into data analysis
Helps learners grasp complex statistical concepts through practical applications
Covers a wide range of statistical concepts, enhancing knowledge for both professionals and students
Provides hands-on practice and interactive materials to reinforce learning
May require additional background knowledge in math for some concepts

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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 Learn Statistics from Basics with these activities:
Review basic math skills
Brush up on basic math skills to ensure a strong foundation for understanding statistical concepts.
Browse courses on Math
Show steps
  • Revisit basic arithmetic operations (addition, subtraction, multiplication, division)
  • Practice solving simple algebraic equations
  • Review concepts like exponents, logarithms, and trigonometry
Explore online tutorials on statistics
Supplement course material with online tutorials to reinforce understanding of statistical methods and concepts.
Browse courses on Descriptive Statistics
Show steps
  • Identify reputable online platforms offering statistics tutorials
  • Choose tutorials aligned with course topics and difficulty level
  • Work through tutorials at your own pace, taking notes and practicing examples
Solve practice problems and exercises
Regular practice through solving problems solidifies understanding of statistical concepts and improves problem-solving skills.
Browse courses on Hypothesis Testing
Show steps
  • Access practice problems from textbooks, online resources, or instructor-provided materials
  • Attempt to solve problems independently, referring to course notes and materials for guidance
  • Check your solutions against provided answer keys or consult with instructors/peers for feedback
  • Identify areas of weakness and focus on additional practice in those areas
Four other activities
Expand to see all activities and additional details
Show all seven activities
Write summaries or explanations of statistical concepts
Writing forces you to synthesize and articulate your understanding of statistical concepts, reinforcing your learning.
Browse courses on Mean
Show steps
  • Choose a statistical concept to focus on
  • Research and gather information from course materials and other sources
  • Write a clear and concise summary or explanation of the concept
  • Share your summary with classmates or instructors for feedback
Attend meetups or conferences related to statistics
Networking with professionals in the field provides insights into career paths and exposes you to cutting-edge advancements in statistics.
Show steps
  • Research upcoming meetups or conferences related to statistics
  • Attend the event and actively engage in discussions with attendees
  • Exchange contact information with potential mentors or industry professionals
Develop a small-scale data analysis project
Hands-on experience in data analysis helps you apply statistical techniques and gain practical skills.
Browse courses on Data Visualization
Show steps
  • Identify a dataset and research potential analysis questions
  • Clean and prepare the data for analysis
  • Apply statistical techniques to analyze the data and draw conclusions
  • Visualize the results and present your findings
Participate in statistics competitions or hackathons
Competitions challenge you to apply your statistical skills in a timed and pressured environment, enhancing your problem-solving abilities.
Show steps
  • Identify relevant statistics competitions or hackathons
  • Form a team or work individually to solve the competition problem
  • Implement statistical models and algorithms to analyze data and derive insights
  • Submit your solution and compete against other participants

Career center

Learners who complete Learn Statistics from Basics will develop knowledge and skills that may be useful to these careers:
Statistician
Statisticians collect, analyze, interpret, and present data. They work in a variety of industries, applying statistical methods to solve problems and make informed decisions. A course on "Learn Statistics from Basics" provides a comprehensive understanding of statistical concepts, data analysis techniques, and statistical modeling, which are fundamental to success as a Statistician.
Data Scientist
Data Scientists use their expertise in statistics, programming, and machine learning to extract insights from data. They work with large datasets, develop predictive models, and create visualizations to help organizations make data-driven decisions. A course on "Learn Statistics from Basics" provides a strong foundation in statistical concepts, data analysis techniques, and machine learning algorithms, which are essential for success in data science.
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns, and extract meaningful insights. They use statistical techniques and programming tools to uncover hidden patterns in data and communicate findings to stakeholders. A course on "Learn Statistics from Basics" provides a solid foundation in statistical concepts and data analysis techniques, which are essential for success in this role.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to optimize decision-making and improve efficiency in complex systems. They work in a variety of industries, applying statistical techniques to solve problems and make data-driven decisions. A course on "Learn Statistics from Basics" provides a strong foundation in statistical concepts and optimization techniques, which are essential for success in operations research.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze and predict financial markets. They develop and implement trading strategies, manage risk, and provide insights to investors and portfolio managers. A course on "Learn Statistics from Basics" provides a strong foundation in statistical methods and financial modeling techniques, which are essential for success in quantitative finance.
Epidemiologist
Epidemiologists investigate the causes and patterns of disease outbreaks and other health-related events. They use statistical methods to analyze data, identify risk factors, and develop prevention and control strategies. A course on "Learn Statistics from Basics" provides a solid foundation in statistical concepts and epidemiological methods, which are essential for success in epidemiology.
Actuary
Actuaries assess and manage risk and uncertainty, using mathematical and statistical models to evaluate the probability and financial impact of future events, especially those involving mortality and longevity. A strong foundation in statistics is crucial for actuaries, and a course on "Learn Statistics from Basics" provides a comprehensive understanding of statistical concepts, probability theory, and risk management techniques, which are essential for actuarial work.
Biostatistician
Biostatisticians apply statistical methods to solve problems in the field of medicine and public health. They design and conduct studies, analyze data, and interpret results to provide insights into disease risk factors, treatment effectiveness, and other health-related issues. A course on "Learn Statistics from Basics" provides a solid foundation in statistical concepts and biostatistical methods, which are essential for success in biostatistics.
Financial Analyst
Financial Analysts evaluate and make recommendations on investments. They analyze financial data and trends, build financial models, and provide insights to clients and stakeholders. A course on "Learn Statistics from Basics" provides a strong foundation in statistical methods and financial analysis techniques, which are essential for understanding financial markets and making informed investment decisions.
Risk Manager
Risk Managers identify, assess, and mitigate risks that could impact an organization's financial performance, reputation, or operations. They use statistical techniques to analyze data, quantify risks, and develop strategies to manage and reduce risks. A course on "Learn Statistics from Basics" provides a strong foundation in statistical concepts and risk management techniques, which are essential for success in risk management.
Market Researcher
Market Researchers conduct research to gather and analyze data about consumer behavior, market trends, and industry dynamics. They use statistical techniques to analyze data, identify patterns, and provide insights that help businesses make informed decisions. A course on "Learn Statistics from Basics" provides a solid foundation in statistical methods and market research techniques, which are essential for conducting effective market research and understanding consumer behavior.
Business Analyst
Business Analysts use data and statistical techniques to analyze business processes, identify inefficiencies, and develop solutions to improve performance. A course on "Learn Statistics from Basics" provides a solid foundation in statistical concepts and data analysis techniques, which are essential for success in business analysis.
Economist
Economists study the production, distribution, and consumption of goods and services. They use statistical techniques to analyze economic data, identify trends, and develop economic models. A course on "Learn Statistics from Basics" provides a solid foundation in statistical concepts and economic analysis techniques, which are essential for success in economics.
Software Engineer
Software Engineers design, develop, and maintain software systems. They use statistical techniques to analyze data, improve performance, and identify potential issues. A course on "Learn Statistics from Basics" provides a solid foundation in statistical concepts and data analysis techniques, which can be applied to improve software design and development processes.
Teacher
As a Teacher, your primary role is to impart knowledge to students. You instruct students of various ages in different subjects, using a variety of teaching methods such as lectures, discussions, and hands-on activities. Several essential skills are required for teaching, including communication, patience, and the ability to motivate and inspire students. Taking a course on "Learn Statistics from Basics" may be useful for understanding complex data and information and conveying it to students in a clear and engaging manner.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Learn Statistics from Basics.
Presents advanced statistical learning concepts and techniques, including data mining, statistical modeling, and prediction. is suitable for advanced learners and researchers in the field.
Provides a comprehensive overview of statistical learning methods and their applications in various domains. is useful as a textbook for advanced learners and a reference for practitioners.
Explores the statistical foundations of machine learning algorithms and provides insights into their applications. is highly relevant for learners interested in the intersection of statistics and machine learning.
Offers a concise and rigorous introduction to statistical inference. is suitable for advanced learners and provides a solid foundation for further study in statistics.
Introduces Bayesian statistical modeling and its applications using R and Stan. is particularly useful for learners interested in Bayesian statistics and its practical implementation.
Covers the fundamental principles of probability theory and provides numerous examples and exercises. serves as a solid foundation for understanding statistical concepts.
Provides a comprehensive introduction to causal inference and its applications in various fields. is highly recommended for learners interested in understanding the principles of causality.
Offers a comprehensive introduction to data science using Python. covers both statistical and machine learning concepts, providing a practical foundation for learners interested in data analysis.
Provides practical guidance on using R for statistical analysis. is particularly useful for learners who wish to apply statistical methods using real-world data.
Covers a wide range of statistical techniques and their applications using the S-PLUS software. is suitable for both beginners and advanced learners.
Provides a comprehensive overview of statistical methods specifically tailored for psychology students and researchers.

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