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To solve the problem, we need to analyze the table, which summarizes the monthly income intervals for 40 companies in Lima.

Here’s the breakdown of how we approach this:

### 1. Table Information
The table appears to include:
- $ x_i $ = midpoint of each income interval.
- $ f_i $ = frequency (number of companies in each interval).
- $ F_i $ = cumulative frequency.
- $ h_i $ = relative frequency.
- $ H_i $ = cumulative relative frequency.

We are asked for the **percentage of companies that had an income of at least $40,000**. In this case, “at least $40,000” means all income intervals where the income is **greater than or equal to $40,000**.

### 2. Step-by-Step Process:
- Identify the interval where $40,000 lies and those higher than this.
- Using the cumulative frequencies or relative frequencies, calculate the percentage of companies in these intervals.

In the table:
- The second row shows a midpoint $ x_i = 45 $, which covers incomes around $45,000, above the $40,000 threshold.
- The cumulative relative frequency $ H_2 $ for this interval is 0.95, meaning **95%** of companies have an income of $45,000 or less.
- Thus, the percentage of companies with income of **at least $40,000** is $ 1 - H_1 = 1 - 0.45 = 0.55 $, or **55%**.

### Final Answer:
The correct percentage is **55%**.

Would you like any further details on this solution or clarifications? Here are some follow-up questions to deepen understanding:

1. How is cumulative relative frequency $ H_i $ calculated from $ h_i $?
2. Why is the cumulative frequency important for understanding distributions?
3. How would the interpretation change if the income intervals were different?
4. What is the importance of midpoint $ x_i $ in summarizing data?
5. How can we use relative frequency to estimate the probability of an event?

**Tip:** Cumulative relative frequency can help you easily find the proportion of data points that lie below or above certain thresholds in a data set.

¿Qué porcentaje de empresas tuvieron ingresos de por lo menos 40,000 dólares?

This problem calculates the percentage of companies that had an income of at least $40,000 using cumulative relative frequency. By interpreting frequency distribution tables and applying simple percentage calculations, you can determine the proportion of companies meeting this income threshold.

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