mobilizingcs.orgIntroduction to Data Science | High school statistics curriculum

Curriculum IDS Curriculum Technology Suite Partnership Partnership List of Partners Professional Development Professional Development PD Calendar Facilitators IDS News IDS News Publications & Presentations Blog About IDS Contact Us Vision History Contributors Our data. Our lives. 7 Curriculum g IDS Partnership O Technology b Professional Development a Publications, Presentations & News 74 Districts 151 High Schools 42,200 Students(YTD) "After a semester of taking IDS I have learned how to code and answer statistical questions that apply to real life." "IDS has actually made math easy for me to do. It has taught me how to code and use graphs. IDS gives me a better visual on math." "Through charts and graphs it is easier to break down the mathematics of the class." - Students "I had a bad experience managing groups in the past. IDS has helped me manage groups better and be more confident overall." - Teacher "[IDS is] helping me understand math by graphing my own data." "I see this fitting for my future because it uses data and analyzing data in our daily life." - Students "I like the list of Instructional Strategies and discovering how they use them in the curriculum. It inspires me use them in my non-IDS classes!" "IDS has made me excited about teaching again. It is great to work with a class that is applicable and meaningful." - Teachers "IDS has made me more aware of how data is collected in various ways. This class has been really eye opening [on] to collect data." "I see IDS fitting into my future...I am able to put IDS on my college application, and if I would ever want to go into computers as a career I would already know how to code." - Students "This class can benefit me in college, internship and work. I think I might use this code professionally in the future if RStudio advances." "Coding is easier, it makes math easier than before." - Students "Teaching IDS has continued to show me that I am a lifelong learner in the content area of math. Observing my students see math in the tangible real life context with everyday activities involving their electronic devices has allowed me to see the kind of connection and engagement that is not frequently seen in the traditional curriculum of mathematics. Overall, teaching this curriculum has been an eye-opening experience with increased student engagement." - Teacher "IDS has allowed me to view statistics in the world of business, and has showed me how math is applied in the real world today." "One thing I know now that I did not know before is that to code we have to be very precise." - Students "IDS has taught me how to analyze different graphs and frequency tables. Also, I learned about the data cycle and how it’s used in our lives." "I think this class will help [me] with future jobs or get into a better college." - Students "[IDS] has stimulated me as a teacher - especially the coding part. It has made me and my students pay attention [to the] real and true essence and value of data and the data process." - Teacher "IDS has taught me how to code and learn a new style of math. I now know how to code and ask statistical questions. IDS is helping me understand math in a new way by being able to code and use a computer. IDS doesn’t only help with math, but on how to use a computer." - Student "IDS connects real social and current issues with math curriculum. It’s brought more relevance to the math classroom. The IDS curriculum emphasizes that there is more than one way to answer a question - aligning it to the Common Core standards. It’s an amazing class." - Teacher Page Background: Data visualization representing teacher connections at the 2013 Mobilize Summer Institute was created by Amelia McNamara, Ph.D./former Mobilize consultant. The Introduction to Data Science (IDS) Project is the leading national provider of high school data science education materials, professional development, and technological support. By 2025 we intend to be a center for research and development of data education tools and an advocate for educational policy change. IDS has received funding from the following organizations: The National Science Foundation–MOBILIZE Grant California Department of Education–California Mathematics Readiness Challenge Initiative (CMRCI) Grant The College Futures Foundation–Foundations in Data Science (FIDS) Grant © 2022 This material is based upon work supported by the National Science Foundation under Grant Number 0962919. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. @uclaIDS Parent Survey First Name Last Name Email State - Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming Who benefitted from the application of data science - Myself My child Other Your message Δ × Introduction to Data Science - About IDS CLOSE Contact Us Name Email * Message reCAPTCHA If you are human, leave this field blank. Submit Δ × Course Overview Introduction to Data Science – Course Overview Unit Unit Title Unit Description Unit1 Data and Visualizations Introduces students to fundamental notions of data analysis—such as distribution and multivariate associations and emphasizes creating and interpreting visualizations of real-world processes as captured by data Unit2 Distributions, Probability, and Simulations Students use numerical summaries to describe distributions and introduces probability through the lens of computer simulations for informal inference Unit3 Data Collection Methods: Traditional and Modern Prepares students to learn about the various ways of collecting data, including Participatory Sensing, and the effect that data collection has on their interpretation of the patterns theydiscover Unit4 Predictions and Models Students learn to make and how to use mathematical and statistical models to predict future observations and how data scientists measure the success of these predictions...