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MathTrackX

Statistics

Nicholas Crouch, Dr. Melissa Humphries, Dr. David Butler, Dr. Brendan Harding, and Dr. Danny Stevenson

This course is part six of the MathTrackX XSeries Program which has been designed to provide you with a solid foundation in mathematical fundamentals and how they can be applied in the real world.

This course will build on probability and random variable knowledge gained from previous courses in the MathTrackX XSeries with the study of statistical inference, one of the most important parts of statistics.

This course is part six of the MathTrackX XSeries Program which has been designed to provide you with a solid foundation in mathematical fundamentals and how they can be applied in the real world.

Guided by experts from the School of Mathematics and the Maths Learning Centre at the University of Adelaide, this course will cover random sampling, sample means and proportions, confidence intervals for sample means and proportions and one-sample tests of proportions and means.

Join us as we provide opportunities to develop your skills and confidence in applying mathematics to solve real world problems.

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What's inside

Learning objectives

The concept of a random sample, sources of bias in samples, and procedures to ensure randomness
The concept of the sample proportion as a random variable
The approximate normality of the distribution of proportions for large samples

The concept of an interval estimates for a parameter associated with a random variable
How to define the approximate margin of error for proportions.

The concept of a random sample, sources of bias in samples, and procedures to ensure randomness
The concept of the sample proportion as a random variable
The approximate normality of the distribution of proportions for large samples
The concept of an interval estimates for a parameter associated with a random variable
How to define the approximate margin of error for proportions.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds on skills and knowledge from the MathTrackX XSeries Program, which may enhance knowledge gained in this course

Covers random sampling, sample means and proportions, confidence intervals for sample means and proportions, and one-sample tests of proportions and means, deepening understanding of statistical inference

Taught by experts from the School of Mathematics and the Maths Learning Centre at the University of Adelaide, providing access to recognized instructors in the field

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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 MathTrackX: Statistics with these activities:

Learn about Probability and Random Variables

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Review Probability and Random Variable knowledge by starting this course off by learning these two subfields of statistics.

Browse courses on Probability

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Review textbook notes and sections on Probability and Random Variables
Complete practice questions on Probability and Random Variables
Take a short quiz or test on Probability and Random Variables

Read 'Statistical Inference' by George Casella and Roger L. Berger

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Supplement your learning by reading a comprehensive textbook on statistical inference that covers advanced concepts and provides real-world examples.

View Statistical Inference (Chapman & Hall/CRC Texts... on Amazon

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Purchase or borrow a copy of the book
Read the chapters relevant to the course material
Take notes and highlight important concepts
Complete the exercises and review questions at the end of each chapter

Study Group for Confidence Intervals

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Form a study group with fellow learners to discuss, solve problems, and quiz each other on confidence intervals, a key concept in statistical inference.

Browse courses on Confidence Intervals

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Find a group of peers interested in forming a study group
Establish regular meeting times and a study schedule
Take turns presenting concepts, solving problems, and leading discussions
Provide feedback and support to each other

Four other activities

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Statistical Inference in Python

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Get hands-on experience with statistical inference by exploring tutorials of coding Python programs to perform statistical inference calculations.

Browse courses on Statistical Inference

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Find online tutorials on Statistical Inference in Python
Follow along with the tutorials and complete the coding exercises
Modify the code to explore different scenarios and test your understanding
Document your learning in a notebook or blog post

Become a MathTrackX Mentor

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Strengthen your understanding of the course material by becoming a mentor to other learners in the MathTrackX program.

Browse courses on Teaching

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Apply to become a mentor through the MathTrackX website
Complete the mentor training program
Connect with learners and provide guidance and support
Share your experiences and insights with other mentors

Hypothesis Testing Simulation

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Deepen your understanding of hypothesis testing by simulating different scenarios and visualizing the results using a programming language.

Browse courses on Hypothesis Testing

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Design a simulation to test a hypothesis
Code the simulation in a programming language
Run the simulation multiple times and collect data
Analyze the data and draw conclusions
Present your findings in a report or presentation

Data Visualization Project

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Showcase your understanding of statistical inference by creating a data visualization project that communicates insights from a real-world dataset.

Browse courses on Data Visualization

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Find a dataset that aligns with your interests
Explore the data and identify patterns and trends
Choose appropriate data visualization techniques to represent the data effectively
Create interactive visualizations using tools like Tableau or Power BI
Share your project with others and present your findings

Career center

Learners who complete MathTrackX: Statistics will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists work with huge amounts of data to extract insights that can help businesses make better decisions. They use their knowledge of statistics, mathematics, and computer programming to clean, analyze, and interpret data. Data Scientists may work in a variety of industries, including healthcare, finance, and retail. MathTrackX: Statistics may be useful in preparing you for this career as it helps you build a solid foundation in probability and random variable knowledge, as well as statistical inference.

See salaries and explore the career path for Data Scientist

Business Analyst

Business Analysts use data and analysis to help organizations make better decisions. They work in a variety of industries, including technology, finance, and healthcare. Business Analysts help organizations improve their processes, products, and services. MathTrackX: Statistics may be useful for this career as it will help you build a foundation in statistical inference, which is one of the most important parts of business analysis.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to help organizations make better decisions. They work in a variety of industries, including manufacturing, logistics, and healthcare. With their skills in statistical analysis and problem-solving, Operations Research Analysts help organizations improve efficiency and productivity. MathTrackX: Statistics can help you excel in this field by providing you with a solid foundation in probability, random variables, and statistical inference.

See salaries and explore the career path for Operations Research Analyst

Statistician

As a Statistician, you will gather, analyze, interpret, and present data in a manner that addresses analytical questions. You work with individuals and institutions to assess and manage risks, advise decision-making, and uncover insights. Individuals who specialize in Statistics may work in healthcare, education, government, banking, and much more. MathTrackX: Statistics may be useful as it will help you build a foundation in statistical inference, which is one of the most important parts of statistics. The course will cover random sampling, sample means and proportions, confidence intervals for sample means and proportions, and one-sample tests of proportions and means.

See salaries and explore the career path for Statistician

Software Engineer

Software Engineers design, develop, and maintain software applications. They work in a variety of industries, including technology, finance, and healthcare. Software Engineers help organizations improve their efficiency and productivity. MathTrackX: Statistics may be useful for this career path since it will help you build a solid foundation in probability, random variables, and statistical inference, which are important for understanding and working with software systems.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts use data to make informed decisions. They work in a variety of industries, including technology, healthcare, and retail. Data Analysts help organizations understand their customers, improve their products and services, and make better decisions about their operations. MathTrackX: Statistics may be useful for this career as it will help you build a foundation in statistical inference, which is one of the most important parts of data analysis.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial Analysts use financial data to make investment recommendations and advise clients on financial planning. They work in a variety of financial institutions, including banks, investment firms, and insurance companies. Financial Analysts help individuals and organizations make informed decisions about their finances. MathTrackX: Statistics will provide you with a solid foundation in probability, random variables, and statistical inference, which are essential skills for Financial Analysts.

See salaries and explore the career path for Financial Analyst

Product Manager

Product Managers are responsible for the development and launch of new products. They work in a variety of industries, including technology, consumer goods, and healthcare. Product Managers help organizations understand their customers and develop products that meet their needs. MathTrackX: Statistics may be useful for this career path since it will help you build a solid foundation in statistical inference, which can be used to analyze market data and make informed decisions about product development.

See salaries and explore the career path for Product Manager

Consultant

Consultants provide advice and services to organizations in a variety of industries. They work independently or for consulting firms. Consultants help organizations improve their performance and achieve their goals. MathTrackX: Statistics may be useful for this career path since it will provide you with a strong foundation in probability, random variables, and statistical inference. These will be helpful when gathering, analyzing, and interpreting data.

See salaries and explore the career path for Consultant

Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. They work in a variety of financial institutions, including investment banks, hedge funds, and asset management companies. Quantitative Analysts help investors make informed decisions about risk and return. MathTrackX: Statistics will provide you with a solid foundation in probability, random variables, and statistical inference, which are essential skills for Quantitative Analysts.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. They work in a variety of industries, including insurance, finance, and healthcare. Actuaries help organizations make informed decisions about risk management, pricing, and product development. MathTrackX: Statistics will provide you with a solid foundation in probability, random variables, and statistical inference, which are essential skills for Actuaries.

See salaries and explore the career path for Actuary

Risk Manager

Risk Managers identify, assess, and manage risks for organizations. They work in a variety of industries, including finance, insurance, and healthcare. Risk Managers help organizations make informed decisions about risk management and mitigation strategies. MathTrackX: Statistics will help you build a solid foundation in probability, random variables, and statistical inference, which are essential skills for Risk Managers.

See salaries and explore the career path for Risk Manager

Market Researcher

Market Researchers analyze market trends to help businesses understand their customers and make better decisions. With the help of surveys, questionnaires, and other data collection methods, Market Researchers gather and interpret data to inform product development and marketing strategies. They work in a variety of industries, including consumer goods, healthcare, and technology. MathTrackX: Statistics can be helpful in this field as it will help you gather data, analyze it, and interpret your findings.

See salaries and explore the career path for Market Researcher

Teacher

Teachers instruct students in a variety of subjects. They work in schools, colleges, and universities. Teachers help students learn and grow. MathTrackX: Statistics may be useful for this career path since it will provide you with a strong foundation in probability, random variables, and statistical inference. This will be helpful when creating lesson plans, grading assignments, and providing feedback to students.

See salaries and explore the career path for Teacher

Researcher

Researchers conduct research in a variety of fields. They work in universities, government agencies, and private companies. Researchers help advance knowledge and develop new technologies. MathTrackX: Statistics may be useful for this career path since it will provide you with a strong foundation in probability, random variables, and statistical inference. This will be helpful when designing and conducting research studies, analyzing data, and drawing conclusions.

See salaries and explore the career path for Researcher

Reading list

We've selected 14 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 MathTrackX: Statistics.

An Introduction to Statistical Learning

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A comprehensive and advanced reference that covers a wide range of statistical methods, providing a more in-depth exploration of the course topics.

MathTrackX

Statistics

What's inside

Learning objectives

Good to know

Save this course

Activities

Career center

Reading list

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