It appears you've uploaded two files. Let me take a look at the images to assist you with the math content in them. I will begin analyzing them. PIL import Image

Load the images to analyze

image_path_1 = '/mnt/data/1733548810088xpovm1q0.jpg' image_path_2 = '/mnt/data/17335488100887jthk1np.jpg'

Open the images to inspect their content

image_1 = Image.open(image_path_1) image_2 = Image.open(image_path_2)

Display both images for analysis

image_1.show() image_2.show()The images you uploaded are now displayed. I will analyze their content to help you with any mathematical questions or problems they contain. Let me extract the relevant information. pytesseract

Use OCR (Optical Character Recognition) to extract text from the images

text_1 = pytesseract.image_to_string(image_1) text_2 = pytesseract.image_to_string(image_2)

text_1, text_2From the images you uploaded, here's what I extracted:

Image 1:

It contains a table showing the yearly tuition data from 2011 to 2018:

• 2011: $26,674
• 2012: $27,670
• 2013: $28,124
• 2014: $28,088
• 2015: $30,210
• 2016: $32,543
• 2017: $33,685
• 2018: $35,479

Image 2:

It outlines the steps to find a linear equation using the data (in the form $y = mx + b$):

1. Use of Linear Regression (via a calculator or software):
   • Step 6 explains how to find the linear equation using linear regression. It mentions the coefficient of determination (r) and the line of best fit.
   • This process involves using a calculator's LinReg function, storing the regression equation, and then calculating the values of $a$ (slope) and $b$ (y-intercept).

Next Steps:

• If you'd like, I can help you find the linear regression equation based on the tuition data from Image 1.
• Would you like to proceed with that, or do you have any specific questions regarding the process or the data?

Let me know how you'd like to proceed!