{"id":1155,"date":"2015-11-12T18:35:31","date_gmt":"2015-11-12T18:35:31","guid":{"rendered":"https:\/\/courses.candelalearning.com\/collegealgebra1xmaster\/?post_type=chapter&p=1155"},"modified":"2015-11-12T18:35:31","modified_gmt":"2015-11-12T18:35:31","slug":"draw-and-interpret-scatter-plots","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/odessa-collegealgebra\/chapter\/draw-and-interpret-scatter-plots\/","title":{"raw":"Draw and interpret scatter plots","rendered":"Draw and interpret scatter plots"},"content":{"raw":"
A scatter plot<\/strong> is a graph of plotted points that may show a relationship between two sets of data. If the relationship is from a linear model<\/strong>, or a model that is nearly linear, the professor can draw conclusions using his knowledge of linear functions. Below is\u00a0a sample scatter plot.\n\n[caption id=\"\" align=\"aligncenter\" width=\"487\"]\"ScatterFigure 1.<\/b> A scatter plot of age and final exam score variables[\/caption]\n

Notice this scatter plot does not<\/em> indicate a linear relationship<\/strong>. The points do not appear to follow a trend. In other words, there does not appear to be a relationship between the age of the student and the score on the final exam.<\/p>\n\n

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Example 1: Using a Scatter Plot to Investigate Cricket Chirps<\/h3>\n

The table below\u00a0shows the number of cricket chirps in 15 seconds, for several different air temperatures, in degrees Fahrenheit.[footnote]Selected data from http:\/\/classic.globe.gov\/fsl\/scientistsblog\/2007\/10\/<\/a>. Retrieved Aug 3, 2010[\/footnote] Plot this data, and determine whether the data appears to be linearly related.<\/p>\n\n<\/colgroup>
Chirps<\/strong><\/td>\n44<\/td>\n35<\/td>\n20.4<\/td>\n33<\/td>\n31<\/td>\n35<\/td>\n18.5<\/td>\n37<\/td>\n26<\/td>\n<\/tr>
Temperature<\/strong><\/td>\n80.5<\/td>\n70.5<\/td>\n57<\/td>\n66<\/td>\n68<\/td>\n72<\/td>\n52<\/td>\n73.5<\/td>\n53<\/td>\n<\/tr><\/tbody><\/table><\/div>\n
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Solution<\/h3>\nPlotting this data\u00a0suggests that there may be a trend. We can see from the trend in the data that the number of chirps increases as the temperature increases. The trend appears to be roughly linear, though certainly not perfectly so.\n<\/span>\n\n[caption id=\"\" align=\"aligncenter\" width=\"487\"]\"ScatterFigure 2<\/b>[\/caption]\n\n<\/div>\n<\/div>\n<\/div>\n<\/section>
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A scatter plot<\/strong> is a graph of plotted points that may show a relationship between two sets of data. If the relationship is from a linear model<\/strong>, or a model that is nearly linear, the professor can draw conclusions using his knowledge of linear functions. Below is\u00a0a sample scatter plot.<\/p>\n
\"Scatter<\/p>\n

Figure 1.<\/b> A scatter plot of age and final exam score variables<\/p>\n<\/div>\n

Notice this scatter plot does not<\/em> indicate a linear relationship<\/strong>. The points do not appear to follow a trend. In other words, there does not appear to be a relationship between the age of the student and the score on the final exam.<\/p>\n

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Example 1: Using a Scatter Plot to Investigate Cricket Chirps<\/h3>\n

The table below\u00a0shows the number of cricket chirps in 15 seconds, for several different air temperatures, in degrees Fahrenheit.[1]<\/sup><\/a> Plot this data, and determine whether the data appears to be linearly related.<\/p>\n\n\n\n\n\n\n\n\n\n\n\n<\/colgroup>\n\n\n\n
Chirps<\/strong><\/td>\n44<\/td>\n35<\/td>\n20.4<\/td>\n33<\/td>\n31<\/td>\n35<\/td>\n18.5<\/td>\n37<\/td>\n26<\/td>\n<\/tr>\n
Temperature<\/strong><\/td>\n80.5<\/td>\n70.5<\/td>\n57<\/td>\n66<\/td>\n68<\/td>\n72<\/td>\n52<\/td>\n73.5<\/td>\n53<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
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Solution<\/h3>\n

Plotting this data\u00a0suggests that there may be a trend. We can see from the trend in the data that the number of chirps increases as the temperature increases. The trend appears to be roughly linear, though certainly not perfectly so.
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\"Scatter<\/p>\n

Figure 2<\/b><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/section>\n

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