## Short Questions and Answers about *Data Representation *

This page contains short questions and answers about non numerical data representation methods such as charts and graphs which includes bar charts and its several types such as component bar chart, multiple bar chart, pie chart , scatter diagram, histogram, historigram etc

**Chart ** is a visual display of data in the form of lines, separated bars, subdivded bars, circles, or two dimensional geometrical (2D), three dimensional (3D) forms. Simple bar chart, multiple bar chart, component bar char and Pie chart are some important types.

**Graph **is a visual display of data in the form of continuous curves or discontinuous lines. Graph provide the facility of comparison. In simple graph it is possible to put down a large number of information. There are two major types of graphs (i) Graphs of time series (ii) Graphs of Frequency Distribution

**Ogive ** is a graphical representation of frequency distribution in which cumulative frequencies are plotted against upper or lower class boundaries taken along X-axis and plotted points are smoothly joined is called cumulative frequency curve or **Ogive**

**Box and whisker plot ** or simply **Box Plot **is a way of summarizing a set of data measured on an interval or ratio scale, often used in exploratory data analysis. It helps about the shape of the distribution, its central value, and variability. The Box produced consists of the most extreme values in the data set (maximum and minimum values), the lower and upper quartiles, and the median. A box plot is helpful for indicating whether a distribution is skewed and whether there are any unusual observations (outliers) in the data set.

Box and whisker plots are also very useful when large numbers of observations are involved and when two or more data sets are being compared.

A **Dot Plot ** is a way of summarizing data, often used in *exploratory data analysis * to illustrate the major features of the distribution of the data in a convenient form. For nominal or ordinal data, a **dot plot ** is similar to a **bar chart **, with the bars replaced by a series of dots. For continuous data, the **dot plot ** is similar to a **histogram **, with the rectangles replaced by dots.

A **dot plot ** also help to detect any unusual observations (outliers), or any gaps in the data set. The horizontal axis of a dot plot appropriate scale is used to represent the quantitative variable. The numerical value of each measurement in the data set is located on the horizontal scale represented by a dot. For repeated data values, the dots are placed above one another, forming a pile at that particular numerical location.

**Stem and leaf ** display is a graphical technique that offers a quick and novel way for simultaneously sorting and displaying data sets where each number in the data set is divided into two parts, a *Stem * and a *Leaf *. A stem is the leading digit(s) of each number and is used in sorting, while a leaf is the rest of the number or the trailing digit(s). A vertical line separates the leaf (or leaves) from the stem. It is technique that simultaneously ranks orders quantitative data and provides insight about the shape of the distribution.

A **scatter plot ** is a useful summary of a set of bivariate data (two variables), usually drawn before conducting a linear correlation coefficient or fitting a linear regression line. It gives a pictorial/ visual representation of the relationship between the two variables (such as positive correlation, negative correlation or no correlation), and aids the interpretation of the correlation coefficient or regression model.

**Principal of Least Squares ** says that the best-fitted line to a set of points is the one for which the sum of the squares of the vertical distances between the points and the line is minimum.

**Pie chart ** consists of a circle divided into sectors whose areas are proportional to the various parts into which the whole quantity is divided. It is an effective way of showing percentage parts when the whole quantity is taken as 100. It is also used when the basic categories are not quantifiable. For example as with expenditure, classified into food, clothing, fuel and light etc.

**Simple Bar Diagram ** is used when the data consist of a single component and do not involve much variation.

**Multiple Bar Diagram ** is used represent two or more related sets of data. It is a diagram which supplies more than one information at the same time.