PIL import Image import pytesseract

Load the image

image_path = '/mnt/data/1737595883278651f4owe.jpg' image = Image.open(image_path)

Use OCR to extract text from the image

extracted_text = pytesseract.image_to_string(image) extracted_textThe extracted data from the image is:
42, 52, 50, 53, 28, 28, 42, 52, 50, 30, 53, 42, 45

I will now calculate the sample mean and sample standard deviation for this dataset. numpy as np

Data extracted from the image

data = [42, 52, 50, 53, 28, 28, 42, 52, 50, 30, 53, 42, 45]

Calculate sample mean and sample standard deviation

sample_mean = np.mean(data) sample_std_dev = np.std(data, ddof=1) # ddof=1 for sample standard deviation

sample_mean, sample_std_devThe calculations are as follows:

• Sample Mean: $43.62$ (rounded to 2 decimal places)
• Sample Standard Deviation: $9.49$ (rounded to 2 decimal places)

Let me know if you want step-by-step details of these calculations or further analysis.

Here are some related questions for practice or exploration:

1. How would you calculate the variance for this dataset?
2. What is the median value of the data points?
3. How would adding an outlier (e.g., 100) affect the mean and standard deviation?
4. Can you determine if this data is normally distributed?
5. How do population standard deviation and sample standard deviation differ?

Tip: Remember, the sample standard deviation uses $n-1$ in the denominator to account for bias when estimating a population parameter.