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Interpreting Data Using Descriptive Statistics with R

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.

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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.

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What's inside

Syllabus

Course Overview
Understanding Types of Variables and Measurement Scales
Interpreting Measures of Location within R
Measuring Variance with Descriptive Statistics
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Creating Credit Application Summary for Month over Month Data
Applying Standard Error and Confidence Estimates to a Sample Mean

Good to know

Know what's good
, what to watch for
, 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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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
Refresh your knowledge of mean, median, and mode to establish a strong foundation for the course.
Browse courses on Descriptive Statistics
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  • Review course materials or online resources
Engage in Discussion Forums
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
Solidify your grasp of statistical measures by completing practice drills that reinforce calculations and interpretations.
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  • Find practice drills or exercises
  • Complete the drills
  • Review your answers
Five other activities
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Show all eight activities
Read "Introductory Statistics with R"
Expand your knowledge by reading "Introductory Statistics with R", which provides a comprehensive introduction to statistical concepts and their application with R programming.
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  • 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
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
Develop a comprehensive statistical analysis plan to demonstrate your understanding of the principles and applications of descriptive statistics.
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  • 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
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
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

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 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 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 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
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
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 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
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
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 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 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 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 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 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 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 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.

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.
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 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.
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.

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