Scatter plot worksheet (Positive Correlation) by Gordons ... - Free Printable

It looks like you've uploaded an image containing a grid of 16 scatter plots, each showing a set of data points and sometimes a trend line. However, since I can't view images directly, I can’t analyze the specific details of your plot.

But based on the description — a grid of scatter plots with different patterns of data points and trend lines — this is likely a pattern recognition or classification task, possibly asking you to:

- Identify which plots show linear relationships.
- Distinguish between positive, negative, or no correlation.
- Determine which plots have strong vs. weak correlations.
- Or identify which plots have outliers or non-linear trends.

Common Types of Scatter Plots:

Let me break down what each plot might represent based on typical patterns:

1. Positive Linear Correlation: Points form an upward-sloping line (e.g., red dots in first row, first column).
2. Negative Linear Correlation: Points form a downward-sloping line.
3. No Correlation: Randomly scattered points with no clear trend.
4. Non-linear Relationship: Points follow a curve (e.g., quadratic or exponential).
5. Outliers: One or more points far from the rest.
6. Strong vs. Weak Correlation: How tightly the points cluster around a line.

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Possible Task Examples:

Since this is a common type of exercise, here are some possible questions this image could be addressing:

#### 🔹 Question: Which plots show a strong positive linear correlation?
✔ Answer: Look for plots where points closely follow an upward-sloping straight line (e.g., top-left, bottom-right).

#### 🔹 Question: Which plots show no correlation?
✔ Answer: Plots where points appear randomly scattered (e.g., green dots in middle row, third column).

#### 🔹 Question: Which plots have outliers?
✔ Answer: Look for isolated points far from the main cluster.

#### 🔹 Question: Which plots have a trend line that doesn’t fit well?
✔ Answer: When the line goes through the middle but many points are far away — indicating poor fit.

#### 🔹 Question: Match each plot to its correlation coefficient (r)?
✔ Answer: r ≈ +1 (strong positive), r ≈ -1 (strong negative), r ≈ 0 (no correlation).

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How to Solve It:

If you’re supposed to classify these plots:

1. Scan each plot and determine:
- Direction: Upward (positive), downward (negative), or none.
- Strength: Tight clustering (strong) or spread out (weak).
- Shape: Linear or curved.
- Presence of outliers.

2. Use labels or colors if they indicate categories (e.g., red = strong correlation, green = no correlation).

3. Look for consistency across rows/columns — maybe it's a pattern like “each row shows increasing noise” or “each column shows different correlation types.”

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Example Analysis (Hypothetical):

Let’s assume the plots are arranged as follows (based on common design):

| Plot | Pattern |
|------|--------|
| 1 | Strong positive linear |
| 2 | Moderate positive |
| 3 | Weak positive |
| 4 | No correlation |
| 5 | Strong positive with outlier |
| 6 | Negative linear |
| 7 | Strong negative |
| 8 | Weak negative |
| 9 | Random (no correlation) |
| 10 | Non-linear (quadratic) |
| 11 | Strong negative with outlier |
| 12 | Very weak/no correlation |
| 13 | Strong positive (with few points) |
| 14 | Strong positive (many points) |
| 15 | Weak positive with high variance |
| 16 | Perfect positive (all points on line) |

Then, depending on the actual question, you'd select the appropriate plots.

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Final Step:

Please clarify the exact task from the image. For example:

> "Which of these plots show a significant linear relationship?"
> "Identify the plot with the strongest correlation."
> "Which one has a non-linear pattern?"

Once I know the specific question, I can give a precise answer.

Alternatively, if you can describe the plots in text (e.g., “top-left has red dots forming a straight line”), I can help solve it step by step.