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To represent the distributions in each exercise, I'll suggest appropriate graphs for both sets of data.

### Ex 1: Number of Students by Faculty in a University
Since this data is categorical, a **bar graph** would be suitable to visually represent the number of students in each faculty. Here’s how it would look:

- **X-axis**: Faculty categories (Natural Sciences, Physics, Economics, Mathematics).
- **Y-axis**: Number of students.
- Each bar height represents the number of students per faculty.

### Ex 2: Level of Education Attained by Employees
This data also involves categorical values, making a **bar graph** appropriate here as well. Another option could be a **pie chart**, as it would visually indicate the proportion of employees in each education level. Here’s the setup for each:

1. **Bar Graph**:
   - **X-axis**: Level of Education (Tertiary, Upper Secondary, Lower Secondary, Primary).
   - **Y-axis**: Number of employees.
   - Each bar height represents the number of employees per education level.

2. **Pie Chart** (alternative):
   - Each slice represents a level of education.
   - The size of each slice corresponds to the number of employees in that category.

Would you like a detailed guide on creating these graphs or help with any specific calculations?

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#### Related Questions:
1. What is the best method to create bar graphs in software like Excel or Google Sheets?
2. How would we interpret these graphs to draw meaningful insights about student distribution across faculties?
3. What percentage of students in Ex 1 belong to each faculty?
4. How would we determine which faculty or education level has the highest representation?
5. Can we use any statistical measures to analyze these distributions further?

#### Tip:
For data that represents parts of a whole, consider a pie chart to easily visualize proportions.

Draw a graph to represent the distribution of students by faculty in a university and the level of education attained by a group of 100 employees.

Learn how to create graphical representations for data distributions. This example shows student distribution across university faculties and education levels of employees, using bar graphs and pie charts for effective data visualization. Suitable for middle school students studying basic statistics.

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