📚 Topic Summary
A line of best fit is a straight line drawn on a scatter plot that represents the general trend of the data. Extrapolation is when we use this line to predict values beyond the range of the original data. In simpler terms, we're using the pattern we see to guess what might happen next, even if we haven't directly observed it. Think of it like predicting how tall a plant will grow next week based on its growth in the past weeks!
When using a line of best fit for extrapolation, it's important to remember that our predictions become less reliable the further we extrapolate. The trend might not continue indefinitely! It's more of an educated guess than a guaranteed outcome.
🧮 Part A: Vocabulary
Match the terms with their definitions:
| Term |
Definition |
| 1. Line of Best Fit |
A. Predicting values beyond the known data range. |
| 2. Scatter Plot |
B. A graph showing the relationship between two sets of data. |
| 3. Extrapolation |
C. A line that best represents the trend in a scatter plot. |
| 4. Data Point |
D. The point where the line of best fit crosses the y-axis. |
| 5. Y-Intercept |
E. A single value in a dataset. |
(Match the following: 1-C, 2-B, 3-A, 4-E, 5-D)
📝 Part B: Fill in the Blanks
Complete the following paragraph using the words: data, line, extrapolation, trend, predict.
When analyzing a scatter plot, we draw a ______ of best fit to represent the overall ______. We can then use this ______ to ______ future values, a process called ______. Remember to always consider the reliability of your predictions!
(Answer: line, trend, line, predict, extrapolation)
🤔 Part C: Critical Thinking
Imagine you're using a line of best fit to predict the sales of ice cream based on temperature. What are some factors, besides temperature, that could affect ice cream sales and make your extrapolation less accurate?
