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+1. What is the name of the international standard for floating-point representation?
+2. How many bits are the floating point numbers defined by that standard allowed to be?
+3. Does your computer support all those formats?  Can you think of an easy way to check with only one line of Python?
+4. Why doesn't this code give the same answers to the two multiplications?  
+
+```
+import pandas as pd
+import numpy as np
+
+# Generate two random 64-bit integers
+num1 = np.random.randint(0, 2**63 - 1)
+num2 = np.random.randint(0, 2**63 - 1)
+
+# Multiply them together using the normal Python multiplication operator
+print(f"num1 * num2 = {num1 * num2}")
+
+# Create a Pandas DataFrame with the generated numbers
+data = {'Number1': [num1], 'Number2': [num2]}
+df = pd.DataFrame(data)
+
+# Multiply the numbers together using the Pandas multiplication operator
+df['Product'] = df['Number1'] * df['Number2']
+
+print(df)
+```
+
+5. You can use `sys.getsizeof` to see how large a Python object is.  Does the size of a Python floating-point number change as it gets larger?  Why or why not?
+6. We already know that the precision of floating-point numbers decreases as their magnitude increases.  Using Pandas, create a dataframe representing a large amount of US Dollars.  What is the smallest number of dollars where adding one cent begins to yield wrong results?
+7. Name three practical differences between Python strings and bytes.  Using `sys.getsizeof`, see how the sizes may be different.  Do emoji change this answer?
+8. Given this sample CSV file (tomato_sales.csv):
+```
+Store,Region,Tomato_Sales
+Store1,East,300
+Store2,West,450
+Store3,North,500
+Store4,South,350
+Store5,East,400
+```
+
+and this Python file to do a simple accounting function:
+
+```python
+def read_tomato_sales(file_name):
+    data = pd.read_csv(file_name)
+    total_sales = data["Tomato_Sales"].sum()  # This will raise an error
+    print(f"Total tomato sales: {total_sales}")
+
+read_tomato_sales("tomato_sales_error.csv")
+```
+
+describe a hypothetical situation where modifying the CSV file to create a type confusion error could cause nuclear war due to AIs taking over the food supply chain.
+
+9. Prevent that nuclear war by modifying `read_tomato_sales` to perform better data validation.
+
+10. Given today's conversation about character encodings, describe why you would want to use bytes instead of strings when processing data containing multiple human languages at the same time.  Write a small Python function to demonstrate this.