5.MATH.9.A

Represent categorical data with bar graphs or frequency tables and numerical data, including data sets of measurements in fractions or decimals, with dot plots or stem-and-leaf plots.

Grade 5 · Texas Essential Knowledge and Skills (TEKS) · TEKS 2012

Standard Unwrapping

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Vocabulary
categorical databar graphsfrequency tablesnumerical datadata setsmeasurementsfractionsdecimalsdot plotsstem-and-leaf plots
Skills
  • represent (categorical data with bar graphs) #dok2
  • represent (categorical data with frequency tables) #dok2
  • represent (numerical data as dot plots) #dok2
  • represent (numerical data as stem-and-leaf plots) #dok2
  • organize (data by type for appropriate representation) #dok2
Learning Targets
  • I can identify the difference between categorical data and numerical data. #dok1
  • I can describe the similarities and differences between bar graphs, frequency tables, dot plots, and stem-and-leaf plots. #dok1
  • I can construct a bar graph to represent categorical data. #dok2
  • I can organize categorical data into a frequency table. #dok2
  • I can represent a data set of numerical measurements as a dot plot. #dok2
  • I can represent a data set of numerical measurements as a stem-and-leaf plot. #dok2
  • I can choose an appropriate representation for a given data set. #dok2
  • I can justify why a particular representation is appropriate for the data set. #dok3
Big Ideas
  • Different types of data (categorical and numerical) require different visual and organizational representations for effective interpretation.
  • Bar graphs, frequency tables, dot plots, and stem-and-leaf plots are tools that help us analyze, communicate, and understand data.
Essential Questions
  • How do we decide which type of graph or table to use for different types of data?
  • How do bar graphs and frequency tables help us understand categorical data?
  • What information can dot plots and stem-and-leaf plots reveal about numerical data?
  • Why is it important to organize and represent data accurately?
  • In what real-world situations might we need to use these types of data representations?