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# Scatter Plots

## Identify positive, negative, and no correlation relations

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Practice Scatter Plots
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Scatter Plots
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## Time of Day and Number of Calories Consumed with Scatter Plots

### Topic

Analyzing the time of day and calories with scatter plots

### Vocabulary

• Correlation
• Scatter Plot
• Positive Correlation
• Negative Correlation
• No Correlation
• Mean
• Median
• Mode
• Variance
• Standard Deviation

### Student Exploration

#### We know that there is a correlation between fast food and the number of calories we eat, but is there correlation between the time of day and the number of calories we eat? How can you use scatter plots to investigate this?

Do you love escaping to the kitchen late at night for a midnight snack? Have you ever wanted breakfast for dinner? Have you ever wondered if your eating habits change over of the course of a day?

One way you could investigate this is in a scatter plot! In order to do so record the food you eat over the course of several days. Be sure to record the time of day and the number of calories in each meal. You can use this website to determine the number of calories in each meal.

Then create a scatter plot graph for the time of day vs. the number calories that you eat.

Food Image 1.

Food Image 2.

Food Image 3.

### Extension Investigation

Is there a correlation between the time of day and the number of calories that you eat? How can you use scatter plots to investigate this?

In this activity you will use scatter plots as a tool to explore whether there is a correlation between the time of day and the number of calories you eat. Here’s how to do it!

1. For five days record all of the food that you eat, how much, the time of day that you eat, and the number of calories (if available on the packaging). Record your data in a table like that below.
Example of table for recording data.
Food Quantity (how much) Time of Day Calories
2. After recording your food data, convert the time into military time (so that you will be able to graph your data more easily). Military time is on a 24-hour clock where the hours before noon rum as usual and after 12 noon the time continues, oppose to returning to 1pm. For example, 1pm in military time is 13:00 (as it is an hour after noon) and 5:15pm in military time is 17:15 (as it is five hours and 15 minutes past noon). For further instruction and examples of how to change the time, check out the following link.
3. Next find the calories for all the food that you ate over the 5-day period. For all the foods that you do not know the caloric information about use the website below to determine the number of calories.
4. Then put all of the time and caloric information into one table for the 5 days, like the example below. At this point you need to add up all the calories that you ate in a single meal, so that at the time of the meal you record the total number of calories you consumed at that meal.
Example of table for time of day vs. number of calories.
Time of Day (in military time) Number of Calories
5. Create a scatter plot graph for the time of day vs. number of calories.
6. After you graph this data, examine it! What type of correlation is there between the time of day and the number of calories that you eat? Does it have a positive, negative or no correlation? If there is a positive or negative correlation – is it strong or weak? How does your scatter plot show this? Explain.
7. What conclusions can you draw from your scatter plot graph and the correlation between the time of day and number of calories you consume? Explain.
8. Scan and upload your graph to the CK-12’s website to share with other students! You can use educreations.com to record your discussion of your scatter plot and then upload it to the CK-12’s website!

1. Calculate the mean, median, and mode for your data.
2. Then calculate the variance for your data. Again, the variance is a measure of the dispersion and its value is lower for tightly grouped data than for widely spread data. What does the variance say about your data? Explain.
3. Then calculate the standard deviation for your data. Again, the standard deviation measures how closely the data clusters around the mean. What does the variance say about your data? Explain.
4. What is the linear regression equation for your data? What is the slope? What is the y\begin{align*}y-\end{align*}intercept? What is the correlation coefficient? What is the coefficient of determination?

### Connections to other CK-12 Subject Areas

• Measures of Central Tendency and Dispersion
• Mean
• Median
• Mode
• Variance of Data Set
• Standard Deviation of a Data Set

Sites for images: