Data classification and tabulation-1.pdf
- 1. DATA CLASSIFICATION AND TABULATION Dr. S. Malini Associate Professor Department of Economics Ethiraj College for Women
- 2. • Arranging data into homogenous groups or classes according to some common characteristics present in the data • Process of sorting and categorizing data into various types, forms or any other distinct class CLASSIFICATION Quantitative Weight , Scores, Per Capita Income Qualitative Gender , Intelligence Geographical Regions, States, Cities, Countries Chronological Years , Days, Months BASES OF CLASSIFICATION
- 3. • Simplification and Briefness: Classification presents data in a brief manner. Hence, it becomes fairly easy to analyze the data. • Utility: As classification highlights the similarity in the data, it brings out its utility. • Distinctiveness: With the help of grouping data into different classes, classification also brings out the distinctiveness in data. • Comparability: it facilitates comparison of data. • Scientific Arrangement: Classification arranges data on scientific lines. Thus it also increases the reliability of data. • Attractive and Effective: Lastly, through the process of classification, data becomes effective and attractive. USES OF CLASSIFICATION
- 4. Systematic & logical presentation of numeric data in rows and columns It facilitates comparison by bringing related information close to each other and helps in further statistical analysis and interpretation. TABULATION Simplify data Essential features of data Facilitate comparison and further analysis Highlight the features of Data Draw Inferences Objectives of tabulation
- 5. PARTS OF A TABLE Table Number easy reference and identification a table should be numbered. written in the centre at the top of the table. Sometimes it is written just before the title of the table. Title clearly worded, brief and unambiguous title describing the nature of data contained in the table. placed centrally on the top of a table, just below the table number (or just after table number in the same line). Captions brief and self-explanatory vertical columns. It may involve headings and sub-headings as well. The units of data contained should also be given for each column Stubs brief and self-explanatory headings of horizontal rows. Also a variable with a large number of classes is usually represented in rows. Body numerical information or frequency of observations in the different cells. This arrangement of data is according to the description of captions and stubs. Footnotes foot of the table for explanation of any fact or information included in the table which needs some explanation. meant for explaining or providing further details about the data, that have not been covered in title, captions and stubs. Sources of Data source of information from which data are taken. include the name of the author, volume,
- 6. RELATED CONCEPTS TO TABULATION Frequency Distribution – the principle of classifying data into groups Class interval -the numerical width of any class in a particular distribution difference between the upper-class limit and the lower-class limit Illustration – Age of 10 Persons 8, 19, 58, 35, 45, 12, 6, 13, 18, 47 Class limits- Lower and upper-class limits Lower class limit - the smallest possible data value assigned to the class Upper-class limit – the largest possible data value assigned to the class Class midpoint - the value halfway between the lower and upper limit of the class Age 0-20 20-40 40-60 Frequency 6 1 3
- 7. Cumulative Frequency The running total of frequencies. It is the sum of all the previous frequencies up to the current point Tally Bar Representation of the data in the form of vertical lines CI f C.f 5 2 2 8 6 8 10 8 16 12 10 26 Marks Tally bar Frequency 10 |||| 4 20 || 2 30 | 1
- 8. Diagrammatic data presentation allows us to understand the data more easily. Types of Diagrams Bar Charts – It commonly used to compare several categories of data. Each rectangular bar has a length and height proportional to the values it represents. One axis of the bar chart presents the categories being compared. The other axis shows a measured value Pie Charts- displays data and statistics in an easy-to-understand ‘pie-slice’ format and illustrates numerical proportion. It is a circle representing all the data given. The 360 degrees about the centre of the circle is divided up according to the proportions of the different quantities shown DIAGRAMMATIC REPRESENTATION 0 1 2 3 4 5 6 Category 1 Category 2 Category 3 Category 4 Bar Chart Series 1 Series 2 Series 3 58% 23% 10% 9% PIE CHART 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
- 9. Line Chart –It graphically displays data that changes continuously over time. It used to show trends, for comparison, Make predictions Histograms - Compares the distribution or frequency of different values or ranges of values. Class intervals are usually of equal width Frequency Polygon- Histogram is another way of representing a frequency distribution on a graph. You draw a frequency polygon by joining the midpoints of the upper widths of the adjacent rectangles of the histogram with straight lines. Stem and Leaf diagrams -numerical representation of the data where the most significant digit is highlighted. Cumulative Frequency Curve – 0 gives are of two types – ‘less than 0 give’ and ‘more than 0 give’. Graphs - Use of graphs in interpreting data, trends and forecasting, easier to understand 0 2 4 6 Line Chart Series 1 Series 2 Series 3
- 10. MERITS AND DEMERITS OF DIAGRAMMATIC REPRESENTATION Merits Easy to Understand Simplified Presentation Quick to grasp Reveals hidden facts Easy to compare Universally accepted Demerits Limited information Restricts further data analysis Portrays limited characteristics Fail to present a meaningful look in certain situations Possibility of misuse Careful usage
- 11. THANK YOU