A graph of a cumulative frequency distribution is called :
Ogive
When we work with data, especially in statistics, visualizing the distribution of data points helps us understand patterns and trends. Different types of frequency distributions call for different types of graphs. The question asks about a specific graph used for cumulative frequency distribution.
Before discussing the graph, let's briefly understand what a cumulative frequency distribution is. A cumulative frequency distribution shows the total frequency of all values less than or equal to the upper boundary of each class interval. It essentially adds up the frequencies as you move through the class intervals.
The graph specifically designed to represent a cumulative frequency distribution is called an Ogive (pronounced oh-jive). There are typically two types of Ogives:
The Ogive is particularly useful for determining percentiles, quartiles, and the median of a dataset directly from the graph.
The question asks for the graph of a cumulative frequency distribution. As explained above, the Ogive is the standard graphical representation used for both 'less than' and 'more than' cumulative frequency distributions. Therefore, the graph of a cumulative frequency distribution is called an Ogive.
Let's look at why the other options are not the correct graph for a cumulative frequency distribution:
| Graph Type | What it Represents | Used For |
|---|---|---|
| Histogram | Frequency distribution | Grouped continuous data |
| Frequency Polygon | Frequency distribution | Grouped data (midpoints) |
| Frequency Curve | Smooth frequency distribution | Smoothed grouped data |
| Ogive (Cumulative Frequency Curve) | Cumulative frequency distribution | Cumulative frequencies (less than or more than) |
| Bar Graph | Frequencies or values for categories | Categorical or discrete data |
| Pie Diagram | Proportions of a whole | Parts of a total |
Understanding Ogives is important for quickly estimating certain statistical measures:
The intersection point of a <less than> Ogive and a <more than> Ogive for the same dataset gives the median on the x-axis.
Consider the following statements:
Statement 1: Range is not a good measure of dispersion.
Statement 2: Range is highly affected by the existence of extreme values.
Which one of the following is correct in respect of the above statements?
Data can be represented in which of the following forms?
1. Textual form
2. Tabula form
3. Graphical form
Select the correct answer using the code given below.The formula to determine the number of classes given by Sturge’s Rule is which one of the following ?
1) K = 1+ 3.322 (log N)
2) K= (log N) 1.322
3)K = $\frac{1+3.322} {(log N)} $
4) K = $\frac{3.322}{(log N) + 1} $
Where :
K = Number of classes
N = Total number of observations
$\log N$ = Logarithm of the total number of observations
For showing the growth of population for the last 8 years, the best diagram is