Lesson Plan
Data Detective Plan
Students will be able to create and interpret scatter plots, identify positive, negative, and no correlation, and draw a line of best fit to make predictions.
Understanding scatter plots helps us make sense of real-world data, see relationships between different things, and even predict future outcomes, which is a powerful skill in our data-driven world.
Audience
8th Grade Students
Time
55 minutes
Approach
Through guided instruction, interactive slides, and a hands-on activity.
Materials
Scatter Plot Stories Slide Deck, Plotting Predictions Worksheet, and Trend Spotter Starter Warm-Up
Prep
Teacher Preparation
15 minutes
- Review the Data Detective Plan and all linked materials.
- Print copies of the Plotting Predictions Worksheet (one per student).
- Ensure projector/smartboard is ready for the Scatter Plot Stories Slide Deck and internet access is stable if any external resources are mentioned (none in this lesson).
Step 1
Warm-Up: Trend Spotter Starter
10 minutes
- Distribute the Trend Spotter Starter Warm-Up to students.
- Have students independently respond to the prompt about identifying trends in data.
- After 5 minutes, facilitate a brief class discussion on their observations and ideas about what makes data show a 'trend.'
- Introduce the day's topic: Scatter Plots and how they help us see trends.
Step 2
Introduction to Scatter Plots
15 minutes
- Present the Scatter Plot Stories Slide Deck (Slides 1-4).
- Explain what a scatter plot is, how to create one (x and y axes, plotting points), and introduce the concepts of correlation (positive, negative, no correlation).
- Use real-world examples to illustrate each type of correlation. Ask questions: 'What might a positive correlation look like between study time and test scores?' 'What about shoe size and number of pets?'
Step 3
Line of Best Fit & Predictions
15 minutes
- Continue with the Scatter Plot Stories Slide Deck (Slides 5-7).
- Explain the purpose of a line of best fit and how to draw one (estimating a line that best represents the trend of the data).
- Discuss how to use the line of best fit to make predictions (interpolation and extrapolation).
- Work through an example together as a class, guiding students on how to visually estimate the line and make a prediction.
Step 4
Worksheet: Plotting Predictions
10 minutes
- Distribute the Plotting Predictions Worksheet.
- Instruct students to work individually or in pairs to complete the worksheet, which involves creating a scatter plot, identifying correlation, drawing a line of best fit, and making a prediction.
- Circulate around the room to provide support and answer questions.
Step 5
Wrap-Up & Discussion
5 minutes
- Bring the class back together.
- Review a few answers from the Plotting Predictions Worksheet as a class, focusing on the drawing of the line of best fit and the interpretation of the prediction.
- Ask students to share one new thing they learned or one question they still have about scatter plots.
- Conclude by reiterating the importance of data analysis in everyday life.
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Slide Deck
Welcome, Data Detectives!
Today, we're going to become data detectives and uncover stories hidden in numbers!
We'll learn about:
- What a scatter plot is
- How to read scatter plots
- Finding trends and making predictions
Get ready to explore!
Welcome students and introduce the concept of looking for patterns in data. Ask a quick warm-up question related to finding connections.
What's a Scatter Plot?
A scatter plot is a graph that shows the relationship between two sets of data.
- Each point on the graph represents two values.
- It helps us see if there's a pattern or trend.
Define scatter plot and its components. Emphasize why we use them (to see relationships between two variables). Show an example on the board if possible or a simple sketch. Review the Data Detective Plan for timing.
Correlation: Positive Trend
When one goes up, the other tends to go up too!
Positive Correlation means that as one variable increases, the other variable also tends to increase.
- Example: The more hours you spend practicing an instrument, the more songs you can play.
Introduce positive correlation. Give real-world examples (e.g., hours studied vs. test scores, ice cream sales vs. temperature). Ask students to think of another example.
Correlation: Negative Trend
When one goes up, the other tends to go down!
Negative Correlation means that as one variable increases, the other variable tends to decrease.
- Example: The more time you spend playing video games, the less time you might spend doing homework.
Introduce negative correlation. Give real-world examples (e.g., hours watching TV vs. grades, age of car vs. its value). Ask students for their examples.
No Correlation
Sometimes, there's no clear connection!
No Correlation means there is no obvious relationship or pattern between the two variables.
- Example: A person's height and their favorite type of music.
Introduce no correlation. Give real-world examples (e.g., shoe size vs. number of siblings, favorite color vs. height). Emphasize that not everything is connected!
Drawing the Line of Best Fit
Once we see a trend, we can draw a line of best fit!
- This line helps us summarize the relationship.
- It should pass through the middle of the data points, with roughly an equal number of points above and below it.
- It doesn't have to hit every point!
Transition to lines of best fit. Explain their purpose: to summarize the trend. Demonstrate how to draw one by eye – try to have equal numbers of points above and below the line.
Predicting the Future (Kind Of!)
The line of best fit isn't just for looking at the past – it can help us make predictions!
- Find a value on the x-axis, go up to your line, and then over to the y-axis to find your prediction.
- Interpolation: Making predictions within your existing data range.
- Extrapolation: Making predictions outside your existing data range (be careful, it's less certain!).
Explain how to use the line for predictions. Clarify interpolation (within data range) and extrapolation (outside data range), mentioning that extrapolation is less reliable. Work through a simple example with the class.
Your Turn: Plotting Predictions!
Now it's time to put your data detective skills to the test!
You'll get a Plotting Predictions Worksheet where you will:
- Create a scatter plot.
- Identify the correlation.
- Draw a line of best fit.
- Make a prediction based on your line.
Good luck, data detectives!
Set up the worksheet activity. Remind students of the steps: plot, identify, draw, predict. Encourage them to ask questions.
Case Closed (For Today!)
Great work today, data detectives!
- You've learned to visualize relationships with scatter plots.
- You can identify trends (positive, negative, no correlation).
- And you can even predict outcomes using a line of best fit.
Keep an eye out for scatter plots in the world around you!
Conclude the lesson. Ask for reflections and emphasize the real-world application of scatter plots. Prepare for the cool-down/exit ticket.
Worksheet
Plotting Predictions: Data Detective Worksheet
Name: _____________________________
Date: _____________________________
Part 1: Sweet Sales Data
A local ice cream shop tracked their daily sales and the average temperature for 10 days in the summer. Use the data below to create a scatter plot.
| Day | Average Temperature (°F) | Ice Cream Sales ($) |
|---|---|---|
| 1 | 70 | 250 |
| 2 | 75 | 300 |
| 3 | 65 | 200 |
| 4 | 80 | 400 |
| 5 | 72 | 280 |
| 6 | 85 | 450 |
| 7 | 68 | 220 |
| 8 | 78 | 350 |
| 9 | 82 | 420 |
| 10 | 60 | 180 |
1. Create a Scatter Plot
On the grid below, plot the data points. Label your axes appropriately (Temperature on the x-axis, Sales on the y-axis).
2. Identify the Correlation
What type of correlation do you observe in your scatter plot? (Positive, Negative, or No Correlation)
Explain your reasoning:
3. Draw a Line of Best Fit
Carefully draw a line of best fit on your scatter plot. Remember, it should represent the general trend of the data.
4. Make a Prediction
Using your line of best fit, predict the ice cream sales if the average temperature was 90°F.
Prediction: _____________________________
Explain how you used your line of best fit to make this prediction:
Part 2: Reading Scatter Plots
Look at the scatter plot below, which shows the relationship between the number of hours a student studied for a math test and their score on the test.
(Imagine a scatter plot here with hours studied on x-axis (0-10) and test score on y-axis (0-100). Points should generally show a positive correlation, but with some spread.)
5. Describe the Correlation
What type of correlation does this scatter plot show? Why?
6. Interpret the Trend
Based on the scatter plot, what can you say about the relationship between study hours and test scores?
7. Make an Observation
Is there an outlier in the data? If so, describe it and what it might mean.
Warm Up
Trend Spotter Starter: What Do You See?
Name: _____________________________
Date: _____________________________
Instructions:
Imagine you are looking at data about two different things. For each scenario, describe if you think there would be a connection, and if so, what kind of connection. Use your own words!
Scenario 1: The number of ice cream cones sold and the temperature outside.
Do you think there's a connection? If so, what happens to ice cream sales when the temperature gets higher? What happens when it gets colder?
Scenario 2: The number of hours a student sleeps and their test scores.
Do you think there's a connection? If so, what happens to test scores if a student sleeps more? What happens if they sleep less?
Scenario 3: The number of pets someone owns and their shoe size.
Do you think there's a connection? Why or why not?
Scenario 4: Your own idea!
Think of two things that you believe have a strong connection. Describe what they are and what kind of connection you expect to see.