To solve this, we need to extract data from the cumulative frequency graph on the right side of the image and use it to fill out the frequency table.

Step 1: Fill in the frequency table

The cumulative frequency graph gives us the cumulative count of people at various height intervals, so we can calculate the frequency for each interval by subtracting the cumulative frequency at the beginning of the interval from the cumulative frequency at the end.

• 100 < h ≤ 120: The cumulative frequency at 120 cm is about 10.
• 120 < h ≤ 140: Cumulative frequency at 140 cm is about 25. Subtract the cumulative frequency at 120 cm (which is 10): $25 - 10 = 15$.
• 140 < h ≤ 160: Cumulative frequency at 160 cm is about 60. Subtract the cumulative frequency at 140 cm (which is 25): $60 - 25 = 35$.
• 160 < h ≤ 180: Cumulative frequency at 180 cm is about 90. Subtract the cumulative frequency at 160 cm (which is 60): $90 - 60 = 30$.
• 180 < h ≤ 200: The cumulative frequency at 200 cm is 100. Subtract the cumulative frequency at 180 cm (which is 90): $100 - 90 = 10$.

So, the frequency table is:

Step 2: Estimate the number of people shorter than 150 cm

From the graph, we estimate that around 45 people are below 150 cm.

Step 3: Estimate the number of people taller than 170 cm

From the graph, around 25 people are taller than 170 cm (since the cumulative frequency at 170 cm is around 75, and the total is 100).

Step 4: Estimate the median height

The median height corresponds to the value where the cumulative frequency is 50 (half of 100). From the graph, this occurs at approximately 155 cm.

Do you need any further details or have any questions? Here are some follow-up questions:

1. What is the purpose of a cumulative frequency graph?
2. How do we determine median height from a cumulative frequency graph?
3. How would the graph look if the distribution was skewed?
4. Can cumulative frequency decrease at any point in the graph?
5. Why is cumulative frequency important in statistics?

Tip: The cumulative frequency graph is very useful for estimating percentiles and median values efficiently.