Let's first analyze the image to extract the data necessary for calculating the upper and lower outlier boundaries. I will then calculate the boundaries using the IQR (Interquartile Range) method, which is commonly used for identifying outliers.

Give me a moment while I process the image. PIL import Image import pytesseract

Load the image to extract text

image_path = '/mnt/data/1733726253472is2n7u23.jpg' img = Image.open(image_path)

Use pytesseract to extract the text from the image

text = pytesseract.image_to_string(img)

textIt appears that the text extracted from the image doesn't contain all of the specific numerical data we need. However, the references to "first quartile," "third quartile," and the outlier boundaries suggest that this is part of a statistical problem.

To calculate the upper and lower outlier boundaries, I need the first quartile (Q1), third quartile (Q3), and the interquartile range (IQR), which is calculated as:

$IQR = Q3 - Q1$

The outlier boundaries are then determined as:

$\text{Lower Outlier Boundary} = Q1 - 1.5 \times IQR$ $\text{Upper Outlier Boundary} = Q3 + 1.5 \times IQR$

It seems like part of the image was cut off, or the numbers may not have been recognized properly. If you could provide the actual numbers for the quartiles (Q1 and Q3), I can compute the boundaries for you.

Would you like to upload a clearer image or provide the data manually?