14 of 1514 of 15 Items%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0A%0D%0AQuestion%0D%0ABeth has been recording her son's weight each year for the past 10 years, as shown in the table below:%0D%0A%0D%0A%0D%0A%0D%0AUsing this table, draw a scatter plot on the graphing calculator DESMOS to determine if the statements below are true or false.%0D%0A%0D%0A(3 points)%0D%0ATrue%09False%0D%0AThe data suggests a linear association between the recorded age and weight.%09%0D%0ATrue – The data suggests a linear association between the recorded age and weight.%0D%0AFalse – The data suggests a linear association between the recorded age and weight.%0D%0AThe data can be represented with a line of best fit y=5x+15%0D%0A%0D%0A=%0D%0A5%0D%0A%0D%0A+%0D%0A15%0D%0ATrue – The data can be represented with a line of best fit y is equal to 5 x plus 15%0D%0AFalse – The data can be represented with a line of best fit y is equal to 5 x plus 15%0D%0AThere is no correlation between the recorded age and weight.%09%0D%0ATrue – There is no correlation between the recorded age and weight.%0D%0AFalse – There is no correlation between the recorded age and weight.
To determine if the statements are true or false, we need to create a scatter plot using the given data. The data table shows Beth's son's weight recorded each year for the past 10 years. Unfortunately, the data you posted is not visible or formatted correctly. Please provide the actual data, ensuring that it is clear and properly organized.
Once you have the correct data, you can use an online graphing tool like DESMOS to create a scatter plot. Here's how:
1. Open DESMOS (https://www.desmos.com/).
2. On the main page, you will see a blank graphing space.
3. Enter the age values on the x-axis and the corresponding weight values on the y-axis.
4. Click on the settings icon (a wrench icon) on the top right corner of the graphing space.
5. In the settings menu, make sure the "Tables" option is selected on the left side.
6. The "Table" tab will show up. Enter the age values in the x-column and the weight values in the y-column.
7. Once you have entered all the data, click outside the settings menu to close it.
8. You should now see the scatter plot based on the data you entered.
Now, we can analyze the scatter plot to determine the validity of the statements:
Statement 1: "The data suggests a linear association between the recorded age and weight."
Look at the scatter plot and see if the points generally form a straight line. If they appear to follow a linear pattern, the statement is true. If the points are scattered randomly without presenting a clear linear relationship, then the statement is false.
Statement 2: "The data can be represented with a line of best fit y=5x+15"
If the scatter plot appears to roughly follow a straight line, you can try adding a line of best fit to the plot. Set the line of best fit to the equation y=5x+15. If the line fits the data reasonably well, then this statement is true. If the line does not align with the majority of the data points, then this statement is false.
Statement 3: "There is no correlation between the recorded age and weight."
Examine the scatter plot and observe if there is a clear trend or pattern. If the points are scattered randomly without any apparent direction, then this statement is true. If there is a noticeable trend or relationship (even if it's not linear), then this statement is false.
By interpreting the scatter plot based on the actual data, you can determine whether each statement is true or false.