We may earn an affiliate commission when you visit our partners.
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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/yoee95/interpreting
Here's a deal for you
We found an offer that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
What's inside
Syllabus
Course Overview
Thinking Like a Statistician
Testing a Hypothesis
Comparing Categorical Values with Frequency Analysis
Read more
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
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
Save this course
Save Interpreting Data with Statistical Models to your list so you can find it easily later:
Save
Save
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
Show steps
Reinforces foundational understanding of graphical representations of data, which is essential for understanding later concepts in the course.
Browse courses on
Scatterplots
Show steps
-
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
Show steps
Provides a comprehensive and accessible introduction to statistical concepts, complementing the course material.
View
Statistics All-in-One For Dummies
on Amazon
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
Show steps
Provides access to experts who can offer personalized advice, address specific questions, and broaden perspectives.
Browse courses on
Statistics
Show steps
-
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
Expand to see all activities and additional details
Show all eight activities
Follow tutorials on hypothesis testing
Show steps
Provides additional guidance and practice with a challenging concept, strengthening understanding and application skills.
Browse courses on
Hypothesis Testing
Show steps
-
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
Show steps
Provides repeated practice and reinforcement of ANOVA concepts, enhancing problem-solving abilities and confidence.
Browse courses on
ANOVA
Show steps
-
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
Show steps
Offers practical experience in applying statistical methods, enhancing real-world problem-solving skills and understanding.
Browse courses on
Data Analysis
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
Show steps
Reinforces learning by actively engaging with course materials, improving retention and understanding.
Browse courses on
Review
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
Show steps
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.
Review scatterplots and line graphs
Show steps
Reinforces foundational understanding of graphical representations of data, which is essential for understanding later concepts in the course.
Browse courses on
Scatterplots
Show steps
Show steps
Show steps
- 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
Show steps
Provides a comprehensive and accessible introduction to statistical concepts, complementing the course material.
View
Statistics All-in-One For Dummies
on Amazon
Show steps
Show steps
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
Show steps
Provides access to experts who can offer personalized advice, address specific questions, and broaden perspectives.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- 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
Expand to see all activities and additional details
Show all eight activities
Follow tutorials on hypothesis testing
Show steps
Provides additional guidance and practice with a challenging concept, strengthening understanding and application skills.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- 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
Show steps
Provides repeated practice and reinforcement of ANOVA concepts, enhancing problem-solving abilities and confidence.
Browse courses on
ANOVA
Show steps
Show steps
Show steps
- 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
Show steps
Offers practical experience in applying statistical methods, enhancing real-world problem-solving skills and understanding.
Browse courses on
Data Analysis
Show steps
Show steps
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
Show steps
Reinforces learning by actively engaging with course materials, improving retention and understanding.
Browse courses on
Review
Show steps
Show steps
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
Show steps
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
Show steps
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
For more career information including salaries, visit:
OpenCourser.com/course/yoee95/interpreting
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.
Save
Covers the probailistic and causal approach to statistical reasoning, and is useful for a deep understanding of how to perform statistical inference
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.
Covers the theory and practice of causal inference, focusing on graphical models.
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.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/yoee95/interpreting
Share
Similar courses
Here are nine courses similar to
Interpreting Data with Statistical Models.
Basic Statistics
OpenCourser.com/course/fdzatn/basic
Basic Statistics
121: Introduction to Statisti
OpenCourser.com/course/oe2nd8/sayloracademy
121: Introduction to Statisti
Statistics for Sales and Marketing
OpenCourser.com/course/4dark8/statistics
Statistics for Sales and Marketing
Interpreting Data Using Statistical Models in R
OpenCourser.com/course/0tbrrh/interpreting
Interpreting Data Using Statistical Models in R
Statistical Inference and Modeling for High-throughput Experiments
OpenCourser.com/course/u8twob/statistical
Statistical Inference and Modeling for High-throughput...
Introduction to Statistics & Data Analysis in Public Health
OpenCourser.com/course/cvzj31/introduction
Introduction to Statistics & Data Analysis in Public...
How to Describe Data
OpenCourser.com/course/fv5372/how
How to Describe Data
Calculate Basic Descriptive Statistics in Google Sheets
OpenCourser.com/course/6bc1yw/calculate
Calculate Basic Descriptive Statistics in Google Sheets
Statistics and R
OpenCourser.com/course/bl35nn/statistics
Statistics and R
Time
168 hours
Level
Introductory
Via
Pluralsight
Instructor
Axel Sirota
Language
English
Good to know
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
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser