Pre-MBA Statistics from Coursera

Welcome to the Pre-MBA Statistics course! By the end of this course, you will be able to describe how statistics can be used to summarize, analyze, and interpret data. This course introduces you to some aspects of descriptive and inferential statistics. You will learn to distinguish between various data types and describe the operations that you can execute with each type of data and the right tools to use. The course also discusses the concepts of probability, which form the backbone of statistical analysis. In particular, the course explores how data behaves and provides insight into its analysis. Further, it discusses how data can be sampled and the pros and cons of these methods. The course also delves deeper into the behavior of large data sets based on well-established statistical results. This also enables you to identify the pitfalls of incorrectly using statistical laws. Lastly, you will learn how to estimate population parameters based on limited data and check the correctness of hypotheses about populations from limited data.

This course is open to students from all disciplines holding a bachelor’s degree. A rudimentary knowledge of Mathematics would help grasp the concepts better.

What's inside

Syllabus

Types of Data

In this module, you will learn about various types of data. You will gain insight into the types of data based on how they can be organized and the amount of inference possible from each of them. The module also analyzes the unique characteristics of diverse types of data. Lastly, you will also learn operations with usability and interpretability of various kinds of data.

Probability

In this module, you will learn about the basics of probability and the concept of random variables. This provides a relatively more formal approach to how data behaves and how uncertainties are modeled mathematically. Finally, the module discusses random variables and the special mathematical entities that model numerical data well and help in inferences.

Sampling

In this module, you will learn about different types of sampling methods used in surveys. Such sampling can be completely randomized or non-randomized. You will learn the pros and cons of these techniques and identify the right method to use in the situation you have in hand. You will also analyze the presentation of two important results: the law of large numbers and the central limit theorems.

Point and Interval Estimation

The task of collecting data from all members of a population is often expensive and sometimes impossible. You can, however, easily collect sample data from a population. In this module, you will learn to make inferences about the characteristics of the population from which you have collected sample data. In this module, you will learn about point estimation and then be able to construct a point estimate of the mean and standard deviation of data in the population. If the data you are interested in is expressed as a proportion, you can construct a point estimate of that proportion. The module also discusses interval estimation. You will learn how to build a confidence interval or a range around a point estimate so that you are appropriately confident that the population parameter will fall within that interval regardless of the sample from which the point estimate was obtained.

Hypothesis Testing

Given a sample of values and a claim that the sample comes from a population with certain characteristics, after going through this module, you will be able to construct tests that will justify or reject such a claim. You will learn the logic behind constructing and executing tests for means and proportions. You will also learn about tests to compare the properties of two populations based on samples from both populations.

Peer Review Assignment

This is a peer-review assignment based on the concepts taught in the Pre-MBA Statistics course. In this assignment, you will be able to apply the skills learned in the course in a realistic situation.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by an author of multiple publications in statistics and a co-author of a textbook on statistical inference

Examines statistical concepts highly relevant in data analysis and business

Covers probability and mathematical modeling, foundational building blocks for data science

Requires rudimentary knowledge of mathematics for better comprehension

Assumes students have no background in statistics, which may not be the case for all learners

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 Pre-MBA Statistics with these activities:

Read 'Probability and Statistics for Engineers and Scientists'

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Review a comprehensive textbook to enhance your understanding of probability and statistics concepts.

View Probability & Statistics for Engineers &... on Amazon

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Read the assigned chapters and take notes.
Solve the practice problems at the end of each chapter.

Organize Course Notes and Materials

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Maintain a well-organized system for your course notes and materials to enhance your ability to revisit and reinforce concepts.

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Create a dedicated folder or notebook for the course.
File and organize notes, assignments, quizzes, and exams by topic or module.
Review and revise your notes regularly to strengthen your understanding.

Review Mathematical Concepts

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Refresh your foundational mathematical skills to prepare for the upcoming statistical concepts.

Browse courses on Probability

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Revise basic probability concepts and distributions.
Review elementary statistics, such as mean, median, and variance.
Practice solving mathematical problems involving basic calculus.

Five other activities

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Discuss Statistical Concepts

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Engage in peer discussions to clarify statistical concepts and reinforce your understanding.

Browse courses on Probability

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Form a study group with classmates.
Choose a statistical topic to discuss.
Prepare talking points and questions.
Meet regularly to discuss the topic, share insights, and solve problems together.

Explore Probability Concepts

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Explore probability concepts to gain a deeper understanding of foundational statistical principles.

Browse courses on Probability

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Find online tutorials on probability.
Follow along with the tutorials, taking notes and solving practice problems.
Discuss your findings with classmates or a tutor.

Practice Data Analysis

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Engage in hands-on data analysis exercises to develop proficiency in applying statistical techniques.

Browse courses on Descriptive Statistics

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Find datasets online or create your own.
Use statistical software to analyze the data, calculating measures of central tendency and dispersion.
Interpret the results and draw conclusions.

Develop a Statistical Model

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Apply your statistical knowledge to create a statistical model for a real-world problem.

Browse courses on Hypothesis Testing

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Identify a problem that can be addressed using statistical methods.
Collect and analyze data relevant to the problem.
Develop a statistical model based on the data.
Validate and evaluate the model's effectiveness.

Develop a Data Analytics Dashboard

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Create a data analytics dashboard to visualize and analyze business data, demonstrating your proficiency in applying statistical techniques.

Browse courses on Data Visualization

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Identify a business problem or opportunity that can be addressed using data analytics.
Collect and clean relevant data.
Design and develop a data visualization dashboard using appropriate tools.
Analyze the data and extract insights.
Present your findings and recommendations to stakeholders.

Career center

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

Statistician

Statisticians collect, analyze, and interpret data to provide insights for businesses, governments, and other organizations. They typically work in the fields of research, consulting, and data analysis. This course may be useful for Statisticians because it provides a strong foundation in the fundamental concepts of statistics, such as probability, sampling, and hypothesis testing.

See salaries and explore the career path for Statistician

Data Scientist

Data Scientists combine their knowledge of statistics, mathematics, and computer science to extract valuable insights from large datasets. They work in a variety of industries, including technology, healthcare, and finance. This course may be useful for Data Scientists because it provides a solid foundation in the fundamental concepts of statistics, such as probability, sampling, and hypothesis testing.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts apply their knowledge of statistics and mathematics to analyze data and interpret findings. They could work in a variety of industries, including healthcare, finance, and retail. This course may be useful for Data Analysts because it provides a solid foundation in the fundamental concepts of statistics, such as probability, sampling, and hypothesis testing.

See salaries and explore the career path for Data Analyst

Survey Researcher

Survey Researchers design and conduct surveys to collect data about populations. They use this data to understand public opinion, customer satisfaction, and other social and economic trends. This course may be useful for Survey Researchers because it provides a strong foundation in the principles of sampling and data analysis.

See salaries and explore the career path for Survey Researcher

Risk Analyst

Risk Analysts identify, assess, and mitigate risks for businesses and organizations. They typically work in the finance, insurance, and healthcare industries. This course may be useful for Risk Analysts because it provides a strong foundation in the fundamental concepts of statistics, such as probability, sampling, and hypothesis testing.

See salaries and explore the career path for Risk Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to evaluate and manage risk. They typically work in the finance industry, helping banks and other financial institutions make sound investment decisions. This course may be useful for Quantitative Analysts because it provides a strong foundation in the fundamental concepts of statistics, such as probability, sampling, and hypothesis testing.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. They typically work in the insurance industry, helping insurance companies to determine the appropriate premiums to charge for their policies. This course may be useful for Actuaries because it provides a strong foundation in the fundamental concepts of statistics, such as probability, sampling, and hypothesis testing.

See salaries and explore the career path for Actuary

Market Researcher

Market Researchers gather, analyze, and interpret data about customers, markets, and competitors. They use this information to help businesses make informed decisions about product development, marketing campaigns, and other business strategies. This course may be useful for Market Researchers because it provides a strong foundation in the principles of statistics and data analysis.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to solve complex problems in business and industry. They typically work in the manufacturing, transportation, and healthcare industries. This course may be useful for Operations Research Analysts because it provides a strong foundation in the fundamental concepts of statistics, such as probability, sampling, and hypothesis testing.

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Financial Analyst

Financial Analysts evaluate financial data to make recommendations on investments and other financial decisions. They typically work in the finance industry, advising individuals and organizations on how to manage their money. This course may be useful for Financial Analysts because it provides a foundation in probability and statistical analysis, which are essential for understanding financial markets and making sound investment decisions.

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Epidemiologist

Epidemiologists investigate the causes and distribution of diseases in populations. They typically work in the public health field, helping to prevent and control outbreaks of disease. This course may be useful for Epidemiologists because it provides a strong foundation in the principles of sampling and data analysis.

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Business Analyst

Business Analysts use data to analyze and improve business processes. They typically work in a variety of industries, helping businesses to make informed decisions about how to operate their businesses. This course may be useful for Business Analysts because it provides a strong foundation in the fundamental concepts of statistics, such as probability, sampling, and hypothesis testing.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They typically work in the technology industry, building and maintaining software systems for businesses and consumers. This course may be useful for Software Engineers because it provides a foundation in probability and statistical analysis, which are increasingly being used in software development.

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Biostatistician

Biostatisticians apply statistical methods to solve problems in biology and medicine. They work in a variety of settings, including academia, industry, and government. This course may be useful for Biostatisticians because it provides a strong foundation in the fundamental concepts of statistics, as well as experience in applying statistical methods to real-world problems.

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Data Engineer

Data Engineers design and build the systems and infrastructure that store and process data. They typically work in the technology industry, building and maintaining data pipelines for businesses and consumers. This course may be useful for Data Engineers because it provides a foundation in probability and statistical analysis, which are increasingly being used in data engineering.

See salaries and explore the career path for Data Engineer