Bivariate Data & Scatter Plots Learn to take bivariate data to create a scatter plot for the purpose of deriving meaning from the data.

43210 In addition to level 3.0 and beyond what was taught in class, the student may:  Make connection with other concepts in math.  Make connection with other content areas. The student will construct, interpret and identify patterns of associations for bivariate data displayed in two- way tables and scatterplots. - Write equation of line-of-best-fit. And use it to make predictions. - Calculate relative frequencies and describe their meaning. The student will construct scatterplots and two-way tables from bivariate data. - Draw line-of- best-fit for scatter plot. - Identify patterns of associations. - Able to generally describe relationship of bivariate data displayed in a two-way table. With help from the teacher, the student has partial success with level 2 and 3 elements. Even with help, students have no success with investigating patterns of association with bivariate data. Focus 7 - Learning Goal #2: The student will construct, interpret and identify patterns of associations for bivariate data displayed in two-way tables and scatterplots.

Scatter Plot What is a scatter plot? A scatter plot is a graph that shows the relationship between two sets of data. Each point on the graph is an ordered pair. (x, y) By how the points are grouped or not grouped, you can determine if the data is related. Types of correlation: POSITIVENEGATIVE NO CORRELATION

8 people were surveyed to find their shoe size and height. It’s hard to see a relationship between all of this data, so lets look at it as a scatter plot. Shoe size will be our “x” and height will be our “y.” This will make an ordered pair. Example 1:

Example 1 continued… Plot the data from the table onto the graph. What can you conclude from this data? According to our data, the height of a person is related to their shoe size. Generally, the larger the shoe size, the taller the person.

Activity: Ice Cream & Temperature An ice cream shop keeps track of how much ice cream they sell versus the temperature on that day. Here are their figures for the last 12 days: What can you conclude from this data? If we take this data and create a scatter plot, we will be able to draw a conclusion. Each student will plot this data on a scatter plot. Ice Cream Sales Vs. Temperature Temperature ˚CIce Cream Sales 14˚$215 16˚$325 12˚$185 15˚$332 19˚$406 22˚$522 19˚$412 25˚$613 23˚$544 18˚$421 23˚$445 17˚$408

Scatter Plot… What can you conclude from this data? It is now easy to see that warmer weather leads to more sales.