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Axel Sirota

Data is everywhere and we always hear about statistics, even if we do not realize it! Over this course we will shape up our statistical knowledge; going from zero to hero analyzing complex patterns of everyday real-world problems.

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Data is everywhere and we always hear about statistics, even if we do not realize it! Over this course we will shape up our statistical knowledge; going from zero to hero analyzing complex patterns of everyday real-world problems.

Data is everywhere, from the newspaper you read on the subway to the report you are using to analyze yesterday's stock market performance. In this course, Interpreting Data with Statistical Models, you will gain the ability to effectively understand how to tackle problems that appear at your work, understand which is the right statistical analysis to use, and how to interpret the results to obtain insights. First, you will learn the very basics of statistics. Next, you will discover hypothesis testing to compare variables. Finally, you will explore how to make multiple comparisons and detect functional relationships with ANOVA and Regression. When you’re finished with this course, you will have the skills and knowledge of data analysis and statistical models needed to make your data speak for itself.

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What's inside

Syllabus

Course Overview
Thinking Like a Statistician
Testing a Hypothesis
Comparing Categorical Values with Frequency Analysis
Read more
Analyzing Experiments with ANOVA
Comparing Groups and Effects with ANOVA
Predicting Linear Relationships with Regression
Predicting Non-linear Relationships with Regression

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Students can learn the basics of statistics, which is a cornerstone of data analysis
Provides a comprehensive introduction to data analysis using statistical models
Learners with no prior statistics knowledge can begin with this course
Students can expect to gain a solid foundation in data analysis concepts and techniques

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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 Interpreting Data with Statistical Models with these activities:
Review scatterplots and line graphs
Reinforces foundational understanding of graphical representations of data, which is essential for understanding later concepts in the course.
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  • Review definitions and examples of scatterplots and line graphs.
  • Practice identifying the independent and dependent variables in scatterplots.
  • Practice interpreting the slope and y-intercept of line graphs.
Read 'Statistics for Dummies' by Deborah Rumsey
Provides a comprehensive and accessible introduction to statistical concepts, complementing the course material.
Show steps
  • Read through the book, taking notes and highlighting key points.
  • Attempt the practice exercises and review the solutions.
  • Summarize the main concepts and apply them to real-world examples.
Seek guidance from experienced statisticians
Provides access to experts who can offer personalized advice, address specific questions, and broaden perspectives.
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  • Identify potential mentors through professional networks or organizations.
  • Reach out to mentors and request guidance on specific topics or career paths.
  • Schedule regular meetings or discussions to benefit from their insights and support.
Five other activities
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Follow tutorials on hypothesis testing
Provides additional guidance and practice with a challenging concept, strengthening understanding and application skills.
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  • Find tutorials on hypothesis testing using credible sources.
  • Follow the steps outlined in the tutorials to conduct hypothesis tests.
  • Apply the concepts to real-world scenarios and interpret the results.
Solve practice problems on ANOVA
Provides repeated practice and reinforcement of ANOVA concepts, enhancing problem-solving abilities and confidence.
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  • Find practice problems on ANOVA from textbooks or online resources.
  • Solve the problems step-by-step, checking for accuracy.
  • Analyze the results and identify patterns or common errors.
Participate in a data analysis project
Offers practical experience in applying statistical methods, enhancing real-world problem-solving skills and understanding.
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Show steps
  • Identify volunteer opportunities related to data analysis.
  • Contact organizations and inquire about their data-related projects.
  • Collaborate with professionals to contribute to data collection, analysis, and interpretation.
  • Present findings and recommendations to stakeholders.
Compile and review comprehensive notes from course materials
Reinforces learning by actively engaging with course materials, improving retention and understanding.
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Show steps
  • Gather all relevant notes, assignments, quizzes, and exams.
  • Organize and consolidate the materials into a cohesive document.
  • Review the compiled materials regularly to reinforce concepts.
Create a presentation on regression analysis
Encourages a deeper understanding of regression analysis by requiring students to explain the concepts and applications to others.
Browse courses on Regression Analysis
Show steps
  • Gather information and data on regression analysis.
  • Develop a clear and engaging presentation outline.
  • Create visual aids and examples to illustrate the concepts.
  • Practice delivering the presentation and gather feedback.

Career center

Learners who complete Interpreting Data with Statistical Models will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist uses data to solve business problems. You will use statistical models to analyze data, identify trends, and make predictions. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models to solve real-world problems. You will use statistical models to train and evaluate machine learning models. Interpreting Data with Statistical Models will help you build a strong foundation in statistics, which is essential for success in this role.
Business Analyst
A Business Analyst uses data to identify and solve business problems. You will use statistical models to analyze data, identify trends, and make recommendations to stakeholders. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Operations Research Analyst
An Operations Research Analyst uses data to improve business efficiency. You will use statistical models to analyze data, identify trends, and make recommendations to stakeholders. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Statistician
A Statistician designs, conducts, analyzes, and interprets the results of statistical studies and surveys. Using mathematical skills, you will likely apply statistical theory and methods to solve practical problems in business, government, and industry. Taking Interpreting Data with Statistical Models will help you build a foundation for collecting, analyzing, and interpreting data. This is a core skill for a Statistician who works with a wide range of data sets to identify trends and patterns.
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to identify trends and patterns. You will use statistical models to interpret data and communicate your findings to stakeholders. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Financial Analyst
A Financial Analyst uses data to make investment decisions. You will use statistical models to analyze financial data, identify trends, and make recommendations to clients. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Risk Analyst
A Risk Analyst uses data to identify and mitigate risks. You will use statistical models to analyze data, identify trends, and make recommendations to stakeholders. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Consultant
A Consultant uses data to solve business problems. You will use statistical models to analyze data, identify trends, and make recommendations to clients. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Quantitative Analyst
A Quantitative Analyst uses data to make investment decisions. You will use statistical models to analyze financial data, identify trends, and make recommendations to clients. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Actuary
An Actuary uses data to assess and manage risks. You will use statistical models to analyze data, identify trends, and make recommendations to clients. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Epidemiologist
An Epidemiologist uses data to investigate and control the spread of disease. You will use statistical models to analyze data, identify trends, and make recommendations to policymakers. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Economist
An Economist uses data to analyze economic trends and make policy recommendations. You will use statistical models to analyze data, identify trends, and make recommendations to policymakers. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Biostatistician
A Biostatistician uses data to design and analyze medical studies. You will use statistical models to analyze data, identify trends, and make recommendations to researchers and policymakers. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.
Market Researcher
A Market Researcher uses data to understand consumer behavior. You will use statistical models to analyze market data, identify trends, and make recommendations to clients. Interpreting Data with Statistical Models will provide you with the skills needed to succeed in this role, including hypothesis testing, ANOVA, and regression.

Reading list

We've selected ten 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 Interpreting Data with Statistical Models.
Covers a wide range of statistical learning methods, from supervised learning to unsupervised learning, including regression, classification, and clustering. It provides a good overview of the field and is commonly used as a textbook at academic institutions.
More advanced treatment of statistical learning methods. It covers a wide range of topics, including supervised learning, unsupervised learning, and feature engineering. It valuable reference for those who want to learn more about the field.
Covers Bayesian statstical modelling, with a focus on Stan as an implementation language
Provides a practical overview of data science for business. It covers a wide range of topics, including data mining, data analysis, and data visualization. It valuable resource for those who want to learn more about how to use data to make better decisions.
This classic book introduces the philosophy and methodology of science, covering topics such as induction and falsification.
Provides a comprehensive overview of statistical methods used in the social sciences. It covers a wide range of topics, including descriptive statistics, inferential statistics, and regression analysis. It valuable reference for those who want to learn more about how to use statistical methods to analyze data in the social sciences.
Provides an overview of statistical methods that are commonly used in ecology. It covers a wide range of topics, including descriptive statistics, inferential statistics, and regression analysis. It valuable resource for those who want to learn more about how to use statistical methods to analyze data in ecology.
Provides a comprehensive overview of statistical methods that are commonly used in bioinformatics. It covers a wide range of topics, including descriptive statistics, inferential statistics, and regression analysis. It valuable resource for those who want to learn more about how to use statistical methods to analyze data in bioinformatics.

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