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Emilee McWilliams
Learn how to compute and interpret some of the most powerful statistical measures across a variety of industries. From mean, median and mode to variance and percentiles, make an impact efficiently in businesses and organizations.
Read more
Learn how to compute and interpret some of the most powerful statistical measures across a variety of industries. From mean, median and mode to variance and percentiles, make an impact efficiently in businesses and organizations.
Read more
Learn how to compute and interpret some of the most powerful statistical measures across a variety of industries. From mean, median and mode to variance and percentiles, make an impact efficiently in businesses and organizations.
Interpreting statistics can be confusing or time consuming. In this course, Interpreting Data using Descriptive Statistics with R, you will learn foundational knowledge to efficiently describe a data set using R. First, you will learn how to calculate mean, median, and mode. Next, you will discover variance and standard deviation. Finally, you will explore how to compare datasets using these statistics. When you’re finished with this course, you will have the skills and knowledge of computing these statistics needed to explain a dataset.
This course is no longer available. Find something similar by browsing:
Descriptive Statistics
R Programming
Mean
Standard Deviation
Median
Variance
Mode
Register for this course and see more details by visiting:
OpenCourser.com/course/xae63s/interpreting
What's inside
Syllabus
Course Overview
Understanding Types of Variables and Measurement Scales
Interpreting Measures of Location within R
Measuring Variance with Descriptive Statistics
Read more
Syllabus
Course Overview
Understanding Types of Variables and Measurement Scales
Interpreting Measures of Location within R
Measuring Variance with Descriptive Statistics
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Develops applicable skills for business and organizations
Emphasizes practical techniques that can be immediately applied in work settings
Builds a foundation in descriptive statistics using R
Allows learners to interpret data efficiently and effectively
Provides a strong foundation for further learning in statistics
Taught by Emilee McWilliams, a recognized expert in the field
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Reviews summary
Foundational descriptive statistics with r
According to learners, this course is an excellent foundational introduction to descriptive statistics using R, particularly ideal for beginners or those needing a refresher. Students consistently highlight the instructor's clear and engaging explanations, making complex statistical concepts accessible. The course's strength lies in its practical examples and hands-on R code demonstrations, enabling direct application of learned skills. While it effectively delivers on its promises, some learners note it might be too basic or slow-paced for those with prior statistics or R experience. Occasional feedback suggests absolute R novices might need supplementary foundational R knowledge, although many beginners successfully navigated the R aspects.
Strong emphasis on hands-on R implementation with useful examples.
"The practical examples were extremely helpful. The R implementation made it directly applicable."
"I appreciated the hands-on exercises... The R scripts provided were very helpful."
"I found the module on 'Credit Application Summary' particularly useful for my job."
Concepts are explained clearly with superb instructor delivery.
"The instructor explains complex concepts of descriptive statistics using R in a very clear and engaging way."
"The lectures were well-structured, and the R code demonstrations were easy to follow."
"I finally understand descriptive statistics. The R demonstrations were excellent and the instructor was very clear."
Provides an accessible and strong foundation in descriptive statistics.
"This course is absolutely fantastic for beginners! I had no prior R experience, and now I feel confident interpreting data."
"Excellent foundational course! As someone who needed to brush up on my statistics for work, this was perfect."
"Fantastic course for anyone new to R and statistics. The content is well-organized..."
Some absolute R beginners found the R syntax assumed prior knowledge.
"I struggled a bit with the R examples... As a complete R novice, I had to spend a lot of time looking up basic R commands elsewhere."
"Could use more foundational R teaching."
"While the statistics concepts were explained, the R syntax sometimes felt rushed..."
May be too slow or basic for those with existing knowledge.
"I found some parts a bit too basic, especially the initial modules if you already have a statistics background."
"It's truly for beginners, which isn't always highlighted enough in the description. The depth isn't there for intermediate users."
"A bit too slow-paced for experienced users, but perfect for newcomers."
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 Using Descriptive Statistics with R with these
activities:
Review Mean, Median, and Mode
Show steps
Refresh your knowledge of mean, median, and mode to establish a strong foundation for the course.
Browse courses on
Descriptive Statistics
Show steps
-
Review course materials or online resources
Engage in Discussion Forums
Show steps
Join online discussion forums to connect with peers, share insights, and deepen your understanding of descriptive statistics.
Browse courses on
Descriptive Statistics
Show steps
-
Find relevant forums or discussion groups
-
Read and engage in discussions
-
Share your own perspectives and insights
Practice Calculating Statistical Measures
Show steps
Solidify your grasp of statistical measures by completing practice drills that reinforce calculations and interpretations.
Browse courses on
Descriptive Statistics
Show steps
-
Find practice drills or exercises
-
Complete the drills
-
Review your answers
Five other activities
Expand to see all activities and additional details
Show all eight activities
Read "Introductory Statistics with R"
Show steps
Expand your knowledge by reading "Introductory Statistics with R", which provides a comprehensive introduction to statistical concepts and their application with R programming.
View
Introductory Statistics with R (Statistics and...
on Amazon
Show steps
-
Obtain a copy of the book
-
Read and comprehend the chapters relevant to descriptive statistics
-
Complete any exercises or questions provided in the book
Explore Variance and Standard Deviation
Show steps
Enhance your understanding of variance and standard deviation through online tutorials that provide interactive examples and step-by-step explanations.
Browse courses on
Descriptive Statistics
Show steps
-
Identify resources for tutorials
-
Follow guided tutorials on variance and standard deviation
Create a Statistical Analysis Plan
Show steps
Develop a comprehensive statistical analysis plan to demonstrate your understanding of the principles and applications of descriptive statistics.
Browse courses on
Descriptive Statistics
Show steps
-
Define the research questions or business objectives
-
Identify the relevant data sources
-
Develop a data analysis strategy
-
Plan for reporting and communicating the results
Create a Data Visualization Project
Show steps
Develop a data visualization project that demonstrates your understanding of descriptive statistics and their applications in different industries.
Browse courses on
Statistical Measures
Show steps
-
Gather and analyze data
-
Choose an appropriate visualization technique
-
Create the data visualization using R code
-
Interpret and present your findings
Seek Mentorship from Industry Professionals
Show steps
Connect with industry professionals who can provide guidance, support, and insights into the practical applications of descriptive statistics in various industries.
Browse courses on
Descriptive Statistics
Show steps
-
Identify potential mentors through networking or online platforms
-
Reach out to mentors and schedule meetings or calls
-
Prepare questions and actively engage in discussions
Review Mean, Median, and Mode
Show steps
Refresh your knowledge of mean, median, and mode to establish a strong foundation for the course.
Browse courses on
Descriptive Statistics
Show steps
Show steps
Show steps
- Review course materials or online resources
Engage in Discussion Forums
Show steps
Join online discussion forums to connect with peers, share insights, and deepen your understanding of descriptive statistics.
Browse courses on
Descriptive Statistics
Show steps
Show steps
Show steps
- Find relevant forums or discussion groups
- Read and engage in discussions
- Share your own perspectives and insights
Practice Calculating Statistical Measures
Show steps
Solidify your grasp of statistical measures by completing practice drills that reinforce calculations and interpretations.
Browse courses on
Descriptive Statistics
Show steps
Show steps
Show steps
- Find practice drills or exercises
- Complete the drills
- Review your answers
Five other activities
Expand to see all activities and additional details
Show all eight activities
Read "Introductory Statistics with R"
Show steps
Expand your knowledge by reading "Introductory Statistics with R", which provides a comprehensive introduction to statistical concepts and their application with R programming.
View
Introductory Statistics with R (Statistics and...
on Amazon
Show steps
Show steps
Show steps
- Obtain a copy of the book
- Read and comprehend the chapters relevant to descriptive statistics
- Complete any exercises or questions provided in the book
Explore Variance and Standard Deviation
Show steps
Enhance your understanding of variance and standard deviation through online tutorials that provide interactive examples and step-by-step explanations.
Browse courses on
Descriptive Statistics
Show steps
Show steps
Show steps
- Identify resources for tutorials
- Follow guided tutorials on variance and standard deviation
Create a Statistical Analysis Plan
Show steps
Develop a comprehensive statistical analysis plan to demonstrate your understanding of the principles and applications of descriptive statistics.
Browse courses on
Descriptive Statistics
Show steps
Show steps
Show steps
- Define the research questions or business objectives
- Identify the relevant data sources
- Develop a data analysis strategy
- Plan for reporting and communicating the results
Create a Data Visualization Project
Show steps
Develop a data visualization project that demonstrates your understanding of descriptive statistics and their applications in different industries.
Browse courses on
Statistical Measures
Show steps
Show steps
Show steps
- Gather and analyze data
- Choose an appropriate visualization technique
- Create the data visualization using R code
- Interpret and present your findings
Seek Mentorship from Industry Professionals
Show steps
Connect with industry professionals who can provide guidance, support, and insights into the practical applications of descriptive statistics in various industries.
Browse courses on
Descriptive Statistics
Show steps
Show steps
Show steps
- Identify potential mentors through networking or online platforms
- Reach out to mentors and schedule meetings or calls
- Prepare questions and actively engage in discussions
Career center
Learners who complete Interpreting Data Using Descriptive Statistics with R will develop knowledge and skills
that may be useful to these careers:
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts leverage mathematical and statistical techniques to analyze data and make predictions. The course, Interpreting Data Using Descriptive Statistics with R, can provide a solid foundation in statistical analysis, enabling you to effectively assess data and draw meaningful conclusions for quantitative modeling and analysis.
Data Scientist
Data Scientist
Data Scientists possess a deep understanding of data analysis and statistical modeling. Completing the course, Interpreting Data Using Descriptive Statistics with R, can enhance your ability to gather, process, and interpret data with confidence, empowering you to make informed decisions and drive insights from complex datasets.
Market Researcher
Market Researcher
Market Researchers play a crucial role in understanding consumer behavior and market trends. By taking the course, Interpreting Data Using Descriptive Statistics with R, you will develop the skills to analyze quantitative data, identify market patterns, and make data-driven recommendations to inform marketing strategies.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to analyze biological and medical data. The course, Interpreting Data Using Descriptive Statistics with R, delves into statistical measures and their interpretation, providing a strong foundation for understanding and communicating statistical findings in the medical field.
Economist
Economist
Economists analyze economic data to understand economic trends and patterns. Taking the course, Interpreting Data Using Descriptive Statistics with R, will enhance your ability to analyze economic data, interpret statistical measures, and draw informed conclusions about economic behavior and policies.
Software Engineer
Software Engineer
Software Engineers specializing in Data Science or Machine Learning require a solid understanding of statistical concepts. The course, Interpreting Data Using Descriptive Statistics with R, introduces key statistical measures and their interpretation, providing a solid foundation for understanding and analyzing data within software applications.
Actuary
Actuary
Actuaries analyze and interpret data to assess risk and uncertainty. This course, Interpreting Data Using Descriptive Statistics with R, will provide you with a comprehensive understanding of statistical measures and their interpretation, enhancing your ability to evaluate data and calculate risks accurately.
Statistician
Statistician
Statisticians design and conduct statistical studies, analyze data, and interpret results. The course, Interpreting Data Using Descriptive Statistics with R, provides foundational knowledge in statistical measures and their interpretation, helping you develop the skills necessary to excel in this field.
Financial Analyst
Financial Analyst
Financial Analysts use statistical techniques to analyze financial data, make forecasts, and provide investment recommendations. By completing the course, Interpreting Data Using Descriptive Statistics with R, you will gain a deeper understanding of statistical measures and their interpretation, enabling you to analyze financial data with confidence and make informed decisions.
Data Analyst
Data Analyst
Data Analysts clean, organize, and interpret data to identify patterns and trends. Taking the course, Interpreting Data Using Descriptive Statistics with R, can enhance your understanding of statistical measures and their interpretation, enabling you to effectively analyze data and draw meaningful insights.
Business Analyst
Business Analyst
Business Analysts leverage data to identify opportunities, improve processes, and make informed decisions. The course, Interpreting Data Using Descriptive Statistics with R, can provide a foundation in statistical analysis, helping you interpret data, understand its implications, and communicate findings effectively.
Statistician Assistant
Statistician Assistant
Statistician Assistants assist statisticians in data analysis and interpretation. Completing the course, Interpreting Data Using Descriptive Statistics with R, can provide a solid understanding of statistical measures and their interpretation, equipping you to support statisticians effectively.
Quality Control Analyst
Quality Control Analyst
Quality Control Analysts monitor and analyze data to ensure product and service quality. This course, Interpreting Data Using Descriptive Statistics with R, can provide you with a foundation in statistical measures and their interpretation, which is crucial for evaluating quality data and making informed decisions.
Market Research Analyst
Market Research Analyst
Market Research Analysts conduct surveys, focus groups, and other research to gather data about consumer behavior and market trends. The course, Interpreting Data Using Descriptive Statistics with R, can provide a foundation in statistical analysis, helping you analyze market research data, draw insights, and make informed recommendations.
Policy Analyst
Policy Analyst
Policy Analysts research and analyze data to inform policy decisions. This course, Interpreting Data Using Descriptive Statistics with R, can provide you with a foundation in statistical analysis, enabling you to understand and interpret data, draw conclusions, and make policy recommendations based on evidence.
For more career information including salaries, visit:
OpenCourser.com/course/xae63s/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 Using Descriptive Statistics with R.
Provides a comprehensive introduction to statistics using R, covering both descriptive and inferential statistics. It offers a practical guide to implementing statistical techniques in R, complementing the course content.
Save
Serves as a comprehensive resource for using R in data science, including a detailed walkthrough on using R for descriptive statistics. It can be used as a reference throughout the course and beyond.
This classic textbook provides a comprehensive and rigorous introduction to statistical methods used in the social sciences, including descriptive statistics. It offers a deeper dive into the underlying concepts and applications of these statistics.
Provides a comprehensive and rigorous introduction to mathematical statistics, covering topics beyond the scope of the course. It valuable resource for those seeking a deeper understanding of the mathematical foundations of statistics.
Provides a rigorous introduction to probability and statistical inference, building upon the concepts covered in the course. It valuable resource for those seeking a more theoretical understanding of statistics.
Provides a gentle introduction to the concepts of descriptive and inferential statistics, making it a great foundation to build upon the concepts discussed in the course.
Provides an introduction to machine learning using R, covering topics such as supervised and unsupervised learning. While it may not be directly related to the course content, it offers valuable insights into how statistics is applied in the field of machine learning.
Focuses on statistical methods used in biology, providing practical examples and case studies. It can be a valuable resource for those interested in applying statistics in the life sciences.
Provides an introduction to statistics specifically tailored for healthcare professionals. It offers practical examples and case studies relevant to the healthcare field.
Introduces Bayesian data analysis, which is an alternative approach to statistical inference. While it may not be directly covered in the course, it offers a valuable perspective for those interested in exploring advanced statistical methods.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/xae63s/interpreting
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Similar courses
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Time
84 hours
Level
Introductory
Via
Pluralsight
Instructor
Emilee McWilliams
Language
English
This course belongs to a
collection
called
Interpreting Data with R. It's comprised of two courses:
- Finding Relationships in Data with R
- Interpreting Data Using Descriptive Statistics with R (viewing)
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