Attached is the study guide for the unit on bivariate data analysis covering both numerical and categorical data.
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On Thursday, we looked at the associations that we can make by looking at bivariate categorical data. This was done in advance of us looking at our own data.
Today, we looked at categorical data and discussed contingency tables. In future lessons, we'll see how spreadsheets can help us automate the data analysis process.
Returning from break, we picked up where we left off and looked at scatterplots that formed from real data--not exact models.
We looked at exact linear models and linear models that were not exact and discussed the differences in their appearance and other characteristics.
In this lesson, we considered the line of best fit as the line that was closest to the most number of points on a scatterplot.
We rounded out the week by creating rudimentary lines of best fit. Our definition of lines of best fit entails the line that is closest to the most number of points.
Today, students looked at bivariate data and began graphing points on a coordinate plane. We looked at the patterns and 'story' that the data told us. We considered both linear and non linear relationships.
In this lesson, we read stories and graphed them on a coordinate plane. After we completed this lesson, students got experience creating their own graphing story complete with a video and a graph in Desmos
On Monday we looked more closely at linear functions and graphing. Much of this was review and set up for graphing stories that were NOT straight lines--either story functions or scatterplots.
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