Answer:
I can surely direct you on the most proficient method to develop a crate and-stubble plot for the given information. In any case, I can't outwardly draw it here. How about we go through the means:
1. **Order the Data:** Orchestrate the information in climbing request.
\[ 56, 57, 58, 58, 59, 60, 61, 61, 62, 63, 64, 65, 66, 66, 67, 68, 70, 70 \]
2. **Find Quartiles:**
- **Q1 (First Quartile):** The middle of the lower half of the information. For this situation, it's the normal of the 25% and half qualities.
- **Q2 (Second Quartile):** The middle of the whole dataset, which is the normal of the half and half qualities.
- **Q3 (Third Quartile):** The middle of the upper portion of the information, which is the normal of the 75% and 100 percent values.
3. **Calculate Interquartile Reach (IQR):**
\[ IQR = Q3 - Q1 \]
4. **Identify Outliers:**
- Anomalies are commonly esteems that fall beneath \(Q1 - 1.5 \times IQR\) or above \(Q3 + 1.5 \times IQR\).
5. **Construct the Crate and-Hair Plot:**
- Define a number boundary.
- Place a crate from \(Q1\) to \(Q3\).
- Define a boundary (stubble) from the crate to the littlest and biggest qualities inside \(1.5 \times IQR\) of \(Q1\) and \(Q3\) individually.
- Address anomalies if any.
You can utilize this data to physically draw the plot or utilize a device like a diagramming number cruncher or factual programming to produce the crate and-bristle plot.