All questions of Data representation for Grade 9 Exam

10+(6�4)=34 is the last class upper limit

Correct Answer is A

A frequency polygon is made by joining the mid points of each bar of a histogram along with 2 imaginary class intervals. Hence, for any point on a frequency polygon the y co-ordinate is the frequency and x co - ordinate is the Class Mark of the interval. In this case, the class mark of the interval 20-30 is 25 . Therefore the correct option is 'c'. If this helps you please upvote and follow

Histogram

A histogram is a graphical representation of a frequency distribution in the form of rectangles. It is a type of bar graph, with the class intervals as the bases and the heights proportional to the corresponding frequencies. The histogram is used to represent numerical data in a more visual and effective way.

Steps to create a histogram:

1. Gather data and decide on the intervals: The data is first collected and then grouped into intervals or classes. The intervals should be mutually exclusive and exhaustive.

2. Draw the X and Y-axis: The X-axis represents the intervals or classes, and the Y-axis represents the frequency of the data.

3. Draw the rectangles: The height of each rectangle is proportional to the frequency of the data in the corresponding interval. The width of the rectangle represents the range of the interval.

4. Label the graph: The graph should be labeled with a title, the X and Y-axis, and the interval boundaries.

Advantages of Histogram:

1. Easy to understand: Histograms are easy to understand and interpret. It provides a clear picture of the data distribution.

2. Effective for large data sets: Histograms are effective for large data sets. It can provide a quick overview of the data distribution.

3. Helps in identifying outliers: Histograms can help in identifying outliers and anomalies in the data.

4. Helps in decision making: Histograms can help in decision making by providing a visual representation of the data.

Conclusion:

Histograms are an effective way to represent data in a graphical form. It is used to understand the distribution of data and to identify patterns and anomalies. It is widely used in various fields such as statistics, finance, and science.