TYPES OF GRAPH & FLOW CHART

Prelude
PART (A) TYPES OF GRAPHS
Line graphs
Pie charts
Bar graph
Scatter plot
Stem and plot
Histogram
Frequency polygon
Frequency curve
Cumulative frequency or ogives
PART (B) FLOW CHART
PART (C) LOG AND SEMILOG GRAPH

1. TYPES OF GRAPH AND FLOW CHART By M. Waleed Ahsan Khan Tareen 13-arid-1100 DVM 8 th evening

2. Contents Prelude PART (A) TYPES OF GRAPHS PART (B) FLOW CHART PART ( C) LOG AND SEMI LOG GRAPH 2

3. Statistics Numbers that is concerned with collection, organization, measurement, and analysis of the numerical data . The graphical demonstration of statistical data in a chart is normally specified as statistical graph chart. 3

4. WHY GRAPHS ? To reveal a trend or comparison of a data Easily understood 4

5. (A)Types T here are different kinds of graphical charts based on statistics as follows: Line graphs Pie charts Bar graph Scatter plot Stem and plot Histogram Frequency polygon Frequency curve Cumulative frequency or ogives   5

6. Line Graph   A line joining several points, or a line that shows the relationship between the points   xy plane  independent variable and a dependent variable 6

7. Example 7

8. Pie Charts A pie chart can be taken as a circular graph which is divided into different disjoint pieces , each displaying the size of some related information. Represents a whole and each part represents a percentage of the whole 8

9. Advantages  Good visual treat Percentage value-instantly known 9

10. Preferred use(Limitation) C ategorical data - one understand what percentage each of these category constitute 10

11. Example 11

12. Final Product 12

13. Bar Graph Bar graph is drawn on an x-y graph and it has labelled horizontal or vertical bars that show different values The size, length and color of the bars represent different values. 13

14. Preferred use(Limitation) Non continuous data C omparing or contrasting the size of the different categories of the data provided. 14

15. E xample 15

16. Scatter plot A scatter plot or scatter graph is a type of graph which is drawn in Cartesian coordinate to visually represent the values for two variables for a set of data. It is a graphical representation that shows how one variable is affected by the other . Data is presented-collection of points-value of a variable positioned  horizontal or x-axis (Explanatory variable ) Value of the other variable positioned on the vertical or y-axis (response variable) 16

17. Example Note that these data are not random 17

18. Stem and Leaf Plot Stem and leaf plot also called as  stem plot  are connected with quantitative data such that it helps in Displaying shapes of the distributions, Organize numbers and Set it as comprehensible as possible . 18

19. Stem and leaf Descriptive technique-emphases on the data provided It concludes more about the shape of a set of data Provides better view about each of the data. The data is arranged by “place value”. In Stem plots each data is taken  divide  Two separate parts  a  stem  and a  leaf . A stem is usually the first digit of the number in the data  a vertical column a leaf is the last digit of the number in the data  the row to the right side of the corresponding stem 19

20. Example 20

21. 21

22. Histogram Histogram is the most accurate graph that represents a frequency distribution. In the histogram the scores are spread uniformly over the entire class interval. The class intervals are plotted on the x-axis and the frequencies on the y-axis. Each interval is represented by a separate rectangle.  The area of each rectangle is proportional to the number of measures within the class- interval. The entire histogram is proportional to the statistical data set. 22

23. Example 23

24. Frequency Polygon The frequency polygon has most of the properties of a histogram, with an extra feature. Here the mid point of each class of the x-axis is marked. Then the midpoints and the frequencies are taken as the plotting point. These points are connected using line segments. We also complete the graph, that is, it's closed by joining to the x-axis. Frequency polygon gives a less accurate representation of the distribution, than a histogram, as it represents the frequency of each class by a single point not by the whole class interval. 24

25. Example 25

26. Final Product 26

27. F requency C urve The frequency polygon consists of sharp turns, and ups and downs which are not in conformity with actual conditions. To remove these sharp features of a polygon, it becomes necessary to smooth it. No definite rule for smoothing the polygon can be laid down. It should be understood very clearly that the curve does not, in any way, sharply deviate from the polygon. In order to draw a satisfactory frequency curve, first of all, we need to draw a frequency histogram  the frequency polygon and ultimately the frequency curve. 27

28. Example 28

29. Cumulative Frequency (OGIVE) Cumulative frequency is a graph plotting cumulative frequencies on the y-axis and class scores on the x-axis. The difference between frequency curve and an ogive is that in the later we plot the cumulative frequency on the y-axis rather than plotting the individual frequencies. Advantage : it enables median, quartiles, etc to be studied from the graph. 29

30. Example 30

31. Example 31

32. 32

33. (B) Flow chart A diagram of the sequence of movements or actions of people or things involved in a complex system or activity. 33

34. Purpose The purpose of a flow chart is to provide people with a common language or reference point when dealing with a project or process . Flowcharts use simple geometric symbols and arrows to define relationships.  34

35. Example 35

36. (C) Graphs on Logarithmic and Semi-Logarithmic Axes In a  semilogarithmic graph , one axis has a logarithmic scale and the other axis has a linear scale. In  log-log graphs,  both axes have a logarithmic scale. The idea here is we use semilog or log-log graph axes so we can more easily see details for small values of  y  as well as large values of  y . 36

37. Semi-Logarithmic Graphs In the following set of axes, the vertical scale is  logarithmic  (equal scale between powers of 10) and the horizontal scale is  linear  (even spaces between numbers). There are no negative numbers on the  y -axis, since we can only find the logarithm of positive numbers. 37

38. Example 38

39. Example 39

40. Example 40

41. Example 41

42.  linear  T-P  axes Plot shows reasonable detail for values of  x  greater than  1, but doesn't tell us much for smaller values of  x  or  y . The points are too close to the  x -axis for us to see what is going on 42

43. Semi-logarithmic axes 43

44. Log-log Graphs Log-log graphs use a logarithmic scale for both vertical and horizontal axes. 44

45. Example 45