The image you uploaded contains two main parts. I'll address each:

1. Table Data: The table presents two columns:

   • $x_i$ (Time in minutes): 5, 6, 7, 8, and 9.
   • $f(x_i)$ (Frequencies): 0, 4, 2, 2, and $x$.

   The problem seems to indicate that there was an error in recording two of the entries. It specifically mentions that the value for $f(5)$ should have been 3, not 0, and for $f(9)$, it should have been 3, not $x$.

2. Multiple-Choice Question: The question asks what will happen to the sum of the squared differences (variance or dispersion) after correcting these recording errors. The answer options are:

   • Increase
   • Decrease
   • No change
   • Impossible to determine

Answer to the multiple-choice question:

The sum of squared differences is sensitive to changes in the data. Correcting the errors (increasing $f(5)$ from 0 to 3 and reducing $f(9)$ from $x$ to 3) will change the squared differences from the mean. Without doing detailed calculations, we can expect that the squared differences will increase, because the previously low values (like 0) are corrected to be higher, which generally increases the overall variance.

Thus, the correct answer is likely: "Increase" (יגדל).

Would you like me to calculate the exact impact of these changes, or explain the concept of squared differences further?

Here are 5 related questions you can consider:

1. How is the sum of squared differences (variance) calculated from a set of data?
2. What impact do corrections to data have on the mean and variance?
3. What methods are used to identify errors in recorded data?
4. How can frequency tables be used to compute descriptive statistics like the mean and variance?
5. What are some common types of errors that occur in statistical data recording?

Tip: When correcting errors in data, it's important to reassess both the mean and the variance, as both can change with updated values.