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How to Graph an Ogive

Ogive Graph Definition:
A graph of frequency distribution which summarize the percentage of data either lower level or higher level related to the given data.When the data are plotted in the graph an S-shaped curve similar to a part of the parabola is formed which shows increasing numbers or percentage that eventually reaches 100%.The general Histogram and Ogive graph varies in shapes and depending on the frequency. For given cumulative frequency Ogive graph increases from 0% to 100%.

Cumulative Frequency:
A frequency distribution indicates the number of individual events occurred. A cumulative frequency indicates the successive addition of a number of events occurred  in the given categories, which adds up to the value of 100.

Types of Ogive: 
There are two types of Ogive graph lower than Ogive and Greater than Ogive.
  1. Lower than Ogive: The cumulative frequency are arranged in ascending order and plotted against upper class level.
  2. Greater than Ogive: The cumulative frequency are arranged in descending order and plotted against lower class level.

How to Make Ogive Graph:

To make an Ogive graph we need to work out with cumulative frequency, each frequency is added with next frequency. The following steps are taken to draw an Ogive graph.

              Step 1: Frequencies are added to get cumulative frequencies.
              Step 2: Write down only the class interval with an upper limit of each class and cumulative relative frequency in another                                 tabular column.
              Step 3: Plot the order pair on a graph in ordered pair with respect upper limit of each class and cumulative frequencies.

Example Problems:

   1. Consider the following distribution and plot the Ogive graph             
          Class                  1-10        11-20       21-30       31-40      41-50       51-60   
 Frequency   18  14  13  10  8  6

Solution: Use the above table to draw Ogive graph

Step 1: Frequencies are added to get cumulative frequencies.

       Class            Frequency         Cumulative Frequency      
 1-3  2.5  2.5
 3-5  7.5  10
 5-7  10  20
 7-9  12.5  32.5
 9-11  25  57.5
 11-13  22.5  80
 13-15  7.5  87.5

Step 2: 

         Class               Cumulative Frequency       
 3  2.5
 5  10
 7  20
 9  32.5
 11  57.5
 13  80
 15  87.5

Ogive Graph

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From Encyclopedia

Graphs Graphs

A graph is a pictorial representation of the relationship between two quantities. A graph can be anything from a simple bar graph that displays the measurements of various objects to a more complicated graph of functions in two or three dimensions. The former shows the relationship between the kind of object and its quantity; the latter shows the relationship between input and output. Graphing is a way to make information easier for a viewer to absorb. The simplest graphs show the number of many objects. For example, a bar graph might name the months of the year along a horizontal axis and show numbers (for the number of days in each month) along a vertical axis. Then a rectangle (or bar) is drawn above each month. The height of the bar might indicate the number of days in that month on which it rained, or on which a person exercised, or on which the temperature rose above 90 degrees. See the generic example of a bar graph below (top right). Another simple kind of graph is a circle graph or pie graph, which shows fractions or percentages. In this kind of graph, a circle is divided into pieshaped sectors. Each sector is given a label and indicates the fraction of the total area that goes with that label. See the generic example of a pie graph below (top middle). A pie chart might be used to display the percentages of a budget that are allotted to various expenditures. If the sector labeled "medical bills" takes up two-tenths of the area of the circle, that means that two-tenths, or 20 percent, of the budget is devoted to medical expenses. Usually the percentages are written on the sectors along with their labels to make the graph easier to read. In both bar graphs and pie graphs, the reader can immediately pick out the largest and smallest categories without having to search through a chart or list, making it easy to compare the relative sizes of many objects simultaneously. Often the two quantities being graphed can both be represented numerically. For example, student scores on examinations are often plotted on a graph, especially if there are many students taking the exam. In such a graph, the numbers on the horizontal axis represent the possible scores on the exam, and the numbers on the vertical axis represent numbers of students who earned that score. The information could be plotted as a simple bar graph. If only the top point of each bar is plotted and a curve is drawn to connect these points, the result is a line graph. See the generic example of a line graph on the pevious page (top left). Although the points on the line between the plotted points do not correspond to any pieces of information, a smooth line can be easier to understand than a large collection of bars or dots. Graphs become slightly more complicated when one (or both) of the quantities in the graph can have continuous values rather than a discrete set. A common example of this is a quantity that changes over time. For example, a scientist might be observing the rate of growth of bacteria. The rates could be plotted so that the horizontal axis displays units of time and the vertical axis displays numbers (how many bacteria exist). Then, for instance, the point (3,1000) would mean that at "time 3" (which could mean three o'clock, or three seconds after starting, or various other times, depending on the units being used and the starting point of the experiment) there were one thousand bacteria in the sample. The rise and fall of the graph show the increases and decreases in the number of bacteria. In this case, even though only a finite set of points represent actual data, the remaining points do have a natural interpretation. For instance, suppose that in addition to the point (3,1000), the graph also contains the point (4,1500) and that both of these points correspond to actual measurements. If the scientist joins all of the points on the graph by a line, then the point (3.5,1200) might lie on the graph, or perhaps the point (3.5,1350). There are many different lines that can be drawn through a collection of points. Looking at the overall shape of the data points helps the scientist decide which line is the most reasonable fit. In the previous example, the scientist could estimate that at time 3.5, there were 1200 (or 1350) bacteria in the sample. Thus graphing can be helpful in making estimates and predictions. Sometimes the purpose for drawing a graph may not be to view the data already known but to construct a mathematical model that will allow one to analyze data and make predictions. One of the simplest models that can be constructed from a set of data is called a best-fit line. Such a line is useful in situations in which the data are roughly linear—that is, they are increasing or decreasing at a roughly constant rate but do not fall precisely on a line. (See graph on the previous page, bottom right.) A best-fit line can be a very useful tool for analyzing data because lines have very simple formulas describing their behavior. If, for instance, one has collected data up to time 5 and wishes to predict what the value will be at time 15, the value 15 can be inserted into the formula for the line to derive an estimation. One can also determine how good an estimate is likely to be by computing the correlation factor for the data. The correlation factor is a quantity that measures how close the set of data is to being linear; that is, how good a "fit" the best-fit line actually is. One of the most common uses of graphs is to display the information encoded in a function. A function, informally speaking, is an operation or rule that can be applied to numbers. Functions are usually graphed in the cartesian plane (that is, the x,y -plane) with the horizontal or x -axis representing the input variable and the vertical or y -axis representing the output variable. The graph of a function differs from the other types of graphs described so far in that all the points on the graph represent actual information. A concrete relationship, usually given by a mathematical formula, connects the two objects being analyzed. For example, the "squaring" function takes numbers and squares them. Thus an input of the number 1 corresponds to an output of 1; an input of 2 corresponds to an output of 4; an input of −7 corresponds to an output of 49; and so on. Therefore, the graph of this function contains the points (1, 1), (2, 4), (−7, 49), and infinitely many others. Does the point (10, 78) lie on this graph? To determine the answer, examine which characteristics all the points on the graph have in common. Any point on the graph of a function represents an input-output pair, with the x -coordinate representing input and the y -coordinate representing output. With the squaring function, each output value is the square of the corresponding input value, so on the graph of the squaring function, each y -coordinate must be the square of the corresponding x -coordinate. Because 78 is not the square of 10, the point (10, 78) does not lie on the graph of the squaring function. It is traditional to name graphs with an equation rather than with words. The equation of any graph, regardless of whether it is the graph of a function, is meant to be a perfect description of the graph—it should tell the viewer the relationship between the x - and y -coordinates of the numbers being graphed. For example, the equation of the graph of the squaring function is y = x ² because the y -coordinate of any point on the graph is the square of the x -coordinate. The line that passes through the point (0, 3) and slants upwards with slope 4 (that is, at a rate of four units up for every one unit to the right) has equation y = 4x + 3. This indicates that for every point on the graph, the y -coordinate is 3 more than 4 times the x -coordinate. An equation of a graph has many uses: it is not only a description of the graph but also a mechanism for finding points on the graph and a test for determining whether a given point lies on the graph. For example, to find out whether the point (278, 3254) lies on the line y = 4x + 3, simply insert (278, 3254), resulting in the inequality 3254 ≠ 4(278) + 3. Because t

From Yahoo Answers

Question:I know that Its a graph for Cumulative Frequency, but My teacher and I were discussing ogive's and he told me that he had never seen one used outside of a text book. He told me that if I can find a use for an Ogive in some type of media or any context in which an ogive would be useful!!! PLEASE HELP!!!!

Answers:It could be used as a sales graph but honestly they aren't overly used.

Question:I know that Its a graph for Cumulative Frequency, but My teacher and I were discussing ogive's and he told me that he had never seen one used outside of a text book. He told me that if I can find a use for an Ogive in some type of media or any context in which an ogive would be useful he would give me extra credit!!! PLEASE HELP!!!!

Answers:rib in Gothic vault: a diagonal rib in a Gothic vault - pointed arch: an arch that rises to a sharp point - cumulative frequency graph: a graph or curve that represents the cumulative frequencies of a set of values

Question:An ogive is a graph that represents cumulative frequencies or cumulative relative frequencies. The points labeled on the horizontal axis are the a.Upper class limits b.Midpoints c.Lower class limits d.Frequencies

Answers:in most cases the label on the horizontal axis of a histogram is the mid point of the class. this is not always true however.


Answers:< ogive is the graph/curve of the less than cumulative frequency distribution which shows the number of observations LESS THAN the upper class boundary/class limit. > ogive, on the other hand, is the graph/curve of the greater than cumulative frequency distribution which shows the number of observations GREATER THAN the lower class boundary/class limit.

From Youtube

Excel Statistics 22: Histogram & Ogive Charts & % Cumulative Frequency :See how to create a Percent Cumulative Frequency Distribution with Formulas, a Histogram and an Ogive Chart. See how to add a new data series to a chart and how to have two different Charts Types in one chart.Chapter 02 Busn 210 Business and Economic Statistics and Excel Class This is a beginning to end video series for the Business & Economics Statistics/Excel class, Busn 210 at Highline Community College taught by Michael Gel ExcelIsFun Girvin

Math Graphing - Introduction to Graphs :This lesson introduces students to basic graphs by showing students how to read simple data. Students are also taught how to read bar graphs and interpret the data as well.