Unit 1, Section 2: Visualizing Data
Instructional Days: 14
Data collection methods affect what we can know about the real world. Visual representations help tell stories with data. Distributions of numerical and categorical variables help describe variability in the data. Technology and computers allow us to visualize complex relationships in data.
Students will view the video called The Value of Data Visualization to help them understand the importance of graphical representations of data. Discussion questions will allow students to begin to think about how they would want to see a data set visualized. The video can be found at: https://www.youtube.com/watch?v=xekEXM0Vonc
S-ID 1: Represent data with plots on the real number line (dotplots, histograms, bar plots, and boxplots).
S-ID 3: Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).
S-ID 6: Represent data on two quantitative variables on a scatterplot and describe how the variables are related.
Create visualizations with data. Learn the difference between plots used for categorical and numerical variables. Interpret and understand graphs of distributions for numerical and categorical variables.
Applied Computational Thinking Using RStudio:
• Learn to download, load, upload, and work with data using RStudio syntax and structure.
• Create appropriate graphical displays of data.
• Differentiate between observations and variables.
• Learn to use objects, functions, and assignments.
Students will continue to understand that data on its own is just collected; but once interpreted, it can lead to discoveries or understandings.
Students will use complex sentences to construct summary statements about their understanding of data, how it is collected, how it is used and how to work with it.
Students will engage in partner and whole group discussions and presentations to express their understanding of data science concepts.
Students will use complex sentences to write informative short reports that use data science concepts and skills.
Data File or Data Collection Method
Students’ Food Habits Campaign Data
CDC Data File
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