Presentation of Data Test - 4

These three can be prepared when data is given in the form of class intervals and corresponding frequencies.

An arithmetic line graph is also called time series graph. In this graph time (hour, day/date, week, month, year, etc.) is plotted along x-axis and the value of the variable (time series data) along y-axis.

An area chart or area graph  displays graphically quantitative data. It is based on the line chart . The area between axis and line are commonly emphasized with colors, textures and hatchings. Commonly one compares with an area chart two or more quantities.

Legend is a picture or symbol or colour given to each graph to differentiate the bars with each other.

For "less than" ogive the cumulative frequencies are plotted against the respective upper limits of the class intervals

Mean and mode can not be calculated by using graphical method.  Only median can be ascertained by constructing ogives.

By using cumulative frequencies,  we can prepare less than type and more than type ogive.

The frequency curve is obtained by drawing a smooth freehand curve passing through the points of the frequency polygon as closely as possible. It may not necessarily pass through all the points of the frequency polygon but it passes through them as closely as possible.

Component bar diagrams are suitable for data having different components.  Similarly, Circles also can be used to present component data by sub dividing the circle and preparing pie chart.

The legend displays the series in a chart with a predefined symbol and the name of the series.

Cumulative percentage is another way of expressing frequency distribution. It calculates the percentage of the cumulative frequency within each interval, much as relative frequency distribution calculates the percentage of frequency.

The main advantage of cumulative percentage over cumulative frequency as a measure of frequency distribution is that it provides an easier way to compare different sets of data.

Cumulative frequency and cumulative percentage graphs are exactly the same, with the exception of the vertical axis scale. In fact, it is possible to have the two vertical axes, (one for cumulative frequency and another for cumulative percentage), on the same graph.

Cumulative percentage is calculated by dividing the cumulative frequency by the total number of observations (n), then multiplying it by 100 (the last value will always be equal to 100%

The frequency curve is obtained by drawing a smooth freehand curve passing through the points of the frequency polygon as closely as possible. It may not necessarily pass through all the points of the frequency polygon but it passes through them as closely as possible.

Ogive is also called cumulative frequency curve. As there are two types of cumulative frequencies, for example "less than" type and "more than" type, accordingly there are two ogives for any grouped frequency distribution data.

A pie diagram is also a component diagram, but unlike a bar diagram, here it is a circle whose area is proportionally divided among the components.  it represents. It is also called a pie chart. The circle is divided into as many parts as there are components by drawing straight lines from the centre to the circumference

An arithmetic line graph is also called time series graph. In this graph time (hour, day/date, week, month, year, etc.) is plotted along x-axis and the value of the variable (time series data) along y-axis. A line graph by joining these plotted points, thus, obtained is called arithmetic line graph (time series graph). It helps in understanding the trend, periodicity, etc. in a long term time series data.

An arithmetic line graph is also called time series graph. In this graph time (hour, day/date, week, month, year, etc.) is plotted along x-axis and the value of the variable (time series data) along y-axis. A line graph by joining these plotted points, thus, obtained is called arithmetic line graph (time series graph). It helps in understanding the trend, periodicity, etc. in a long term time series data.

For example,  if the data is about marks of students in a 100 marks paper,  and data is presented in the form of marks 0-10, 10-20, 20-30 etc.  The range of the data will be 100-0=100. Number of class intervals are 10. Therefore,  width of the class intervals will be 100/10=10.

A frequency polygon is a plane bounded by straight lines, usually four or more lines. Frequency polygon is an alternative to histogram and is also derived from histogram itself. A frequency polygon can be fitted to a histogram for studying the shape of the curve. The simplest method of drawing a frequency polygon is to join the midpoints of the topside of the consecutive rectangles of the histogram.

A frequency distribution is defined as an orderly arrangement of data classified according to the magnitude of the observations.

 In a tabular presentation, data are presented in rows (read horizontally) and columns (read vertically). The most simple way of  conceptualising a table is to present the data in rows and columns alongwith some  explanatory notes. Tabulation can be done using one-way, two-way or three-way  classification depending upon the number of characteristics involved

Histograms, Frequency Polygons and Ogive can be prepared only if class intervals are given.  These can not be prepared from discrete data.

In a tabular presentation, data are presented in rows (read horizontally) and columns (read vertically).

A component part chart can be presented by circle through pie graph by converting the frequencies into angles and it also can be presented in the form of component bar graph by converting frequencies into percentage.

It shows different components in a single bar.

An arithmetic line graph is also called time series graph. In this graph time (hour, day/date, week, month, year, etc.) is plotted along x-axis and the value of the variable (time series data) along y-axis. A line graph by joining these plotted points, thus, obtained is called arithmetic line graph (time series graph). It helps in understanding the trend, periodicity, etc. in a long term time series data.