PIL import Image

Open the image to inspect its contents

img_path = '/mnt/data/1732671777203p3j8dl4x.jpg' img = Image.open(img_path) img.show()It appears you've uploaded an image. I'll process it to extractesseract

Use pytesseract to extract text from the image

text = pytThe image contains a question about performing a goodness-of-fit test based on a candy distribution. Here are the key details extracted:

• The problem involves a reported color distribution for a candy, with the following color percentages:

  • Green: 17%
  • Orange: 19%
  • Yellow: 15%
  • Blue: 23%

• The observed frequencies (number of candies for each color) are given as:

  • Green: 18
  • Orange: 28
  • Yellow: 9
  • Blue: 17

The question is asking you to determine the null and alternative hypotheses and to compute the test statistic (χ²) for the goodness-of-fit test.

Null and Alternative Hypotheses:

• Null Hypothesis (H₀): The color distribution is the same as that reported.
• Alternative Hypothesis (H₁): The color distribution is different from that reported.

Next Steps:

1. Expected frequencies: The expected frequency for each color is calculated by multiplying the total number of candies by the reported percentage.
2. Chi-Square test statistic (χ²): We calculate the test statistic using the formula:

$χ² = \sum \frac{(O_i - E_i)^2}{E_i}$

Where:

• $O_i$ is the observed frequency.
• $E_i$ is the expected frequency.

Would you like me to help with calculating the expected frequencies, the test statistic, and determining the outcome of