To calculate the mean and median of the data set provided in the image, I will first extract the numbers, organize them, and perform the calculations.

Extracted Data:

• Column 1: 253, 245, 175, 162, 210, 201, 236, 189, 246, 216, 213
• Column 2: 131, 213, 170, 188, 255, 267, 163, 241, 263, 269, 179
• Column 3: 304, 315, 323, 317, 290, 231, 262, 253, 245, 215, 225

Combined Data Set:

$253, 245, 175, 162, 210, 201, 236, 189, 246, 216, 213, 131, 213, 170, 188, 255, 267, 163, 241, 263, 269, 179, 304, 315, 323, 317, 290, 231, 262, 253, 245, 215, 225$

I will now calculate the mean and median. numpy as np

Data extracted from the image

data = [ 253, 245, 175, 162, 210, 201, 236, 189, 246, 216, 213, 131, 213, 170, 188, 255, 267, 163, 241, 263, 269, 179, 304, 315, 323, 317, 290, 231, 262, 253, 245, 215, 225 ]

Calculating the mean and median

mean_value = np.mean(data) median_value = np.median(data)

mean_value, median_value### Results:

• Mean: 232.27 (approx.)
• Median: 236.0

Would you like a step-by-step explanation of how these were calculated?

Here are some related questions for further exploration:

1. How does the mean compare to the median in terms of distribution?
2. What is the range of this data set?
3. Can we calculate the standard deviation to analyze the data's spread?
4. How would outliers (if present) affect the mean and median?
5. What would the mode of the data set be?

Tip: The median is often a better measure than the mean in datasets with outliers or skewed distributions!