# Understanding the M&M's Data Table
Let's go through the information presented in your data table step-by-step.
## Section 1: Cup of M&M's Data Table
This section seems to want to gather data about different colors of M&M's. The table has columns for different colors and a total.
## Section 2: Predicted Number
This section could indicate that you'll be predicting the number of M&M's for each color.
## Section 3: Percent (%) or Description
This section likely will have percents or descriptions that can help in understanding the distribution of M&M's.
## Section 4: Bag of M&M's Data Table (Class)
This table seems to include the actual observations or data for a bag of M&M's for a class activity.
From this section, we can observe the following:
- Brown: 13
- Yellow: 14
- Red: 13
- Blue: 24
- Orange: 20
- Green: 16
- Total: 100
### Calculations Based on the Data
Given the total count of M&M's in a class bag is 100, we can infer the actual percentages of each color.
- Brown: [tex]\( \frac{13}{100} \times 100\% = 13\% \)[/tex]
- Yellow: [tex]\( \frac{14}{100} \times 100\% = 14\% \)[/tex]
- Red: [tex]\( \frac{13}{100} \times 100\% = 13\% \)[/tex]
- Blue: [tex]\( \frac{24}{100} \times 100\% = 24\% \)[/tex]
- Orange: [tex]\( \frac{20}{100} \times 100\% = 20\% \)[/tex]
- Green: [tex]\( \frac{16}{100} \times 100\% = 16\% \)[/tex]
These percentages can be used to understand how frequently each color appears in a given class bag.
## Section 5: Percent to (%) Deviation
This section is expected to provide insight into how far each color's actual count deviates from the predicted count.
### Example Calculation for Deviation
If you had a predicted percentage for each color, you would compare it with the actual percentage to compute the deviation.
For example:
- If the predicted Brown percentage was 10%, the deviation would be [tex]\( 13\% - 10\% = 3\% \)[/tex].
- If the predicted Yellow percentage was 15%, the deviation would be [tex]\( 14\% - 15\% = -1\% \)[/tex].
You would do similar calculations for other colors.
### Recap
The table is organized to:
1. Record individual predictions and actual counts.
2. Compute and understand percentages.
3. Compare actual results against predictions and calculate deviations.
Understanding these steps and interpreting the data correctly will help you derive meaningful insights from the study of M&M's colors distribution in a given dataset or set of predictions.
