IM Alg1.1.3 Lesson: A Gallery of Data

The dot plots represent the distribution of the amount of tips, in dollars, left at 2 different restaurants on the same night.
[size=150]What do you notice? What do you wonder?[br][br][img]data:image/png;base64,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[/img][/size]
Your teacher will assign your group a statistical question.
Write the question in the space below.
As a group, create a dot plot, histogram, and box plot to display the distribution of the data.
Create a dot plot.
Create a histogram
Create a box plot
As a group, write 3 comments that interpret the data.[br]
As you visit each display, write a sentence or two summarizing the information in the display.
Choose one of the more interesting questions you or a classmate asked and collect data from a larger group, such as more students from the school. Create a data display and compare results from the data collected in class.
Close

Information: IM Alg1.1.3 Lesson: A Gallery of Data