Objectives of Data Tabulation Session 01 To carry

Objectives of Data Tabulation Session 01 To carry out investigations To do comparisons To locate omissions and errors in the data To use space economically To study the trends To simplify data To use it as future references

Importance of Tabulation Under tabulation, data is divided into various parts and Session 01 for each part there are totals and sub totals. Therefore, relationship between different parts can be easily known. Since data are arranged in a table with a title and a number so these can be easily identified and used for the required purpose Tabulation makes the data brief. Therefore, it can be easily presented in the form of graphs. Tabulation presents the numerical figures in an attractive form.

Importance of Tabulation Session 01 Tabulation makes complex data simple and as a result of this, it becomes easy to understand the data. This form of the presentation of data is helpful in finding mistakes. Tabulation is useful in condensing the collected data.

Importance of Tabulation makes it easy to analyze the Session 01 data from tables. Tabulation is a very cheap mode to present the data. It saves time as well as space. Tabulation is a device to summaries the large scattered data. So, the maximum information may be collected from these tables.

Rules of Tabulation Session 01 There are no hard and fast rules for the tabulation of data but for constructing good table, following general rules should be observed while tabulating statistical data. The table should suit the size of the paper and, therefore, the width of the column should be decided before hand. Number of columns and rows should neither be too large nor too small. As far as possible figures should be approximated before tabulation. This would reduce unnecessary details.

Rules of Tabulation Items should be arranged either in alphabetical, Session 01 chronological or geographical order or according to size. The sub-total and total of the items of the table must be written. Percentages are given in the tables if necessary. Ditto marks should not be used in a table because sometimes it create confusion. Table should be simple and attractive.

Rules of Tabulation A table should be logical, well-balanced in length Session 01 and breadth and the comparable columns should be placed side by side. Light/heavy/thick or double rulings may be used to distinguish sub columns, main columns and totals. For large data more than one table may be used.

Parts of an Ideal Table Session 01 Table number: A number must be allotted to the table for identification, particularly when there are many tables in a study. Title: The title should explain what is contained in the table. It should be clear, brief and set in bold type on top of the table. It should also indicate the time and place to which the data refer.

Parts of an Ideal Table Date: Session 01 The date of preparation of the table should be given. Stubs or Row designations: Each row of the table should be given a brief heading. Such designations of rows are called “stubs”, or, “stub items” and the entire column is called “stub column”. Column headings or Captions: Column designation is given on top of each column to explain to what the figures in the column refer. It should be clear and precise. This is called a “caption”, or, “heading”. columns should be numbered if there are four, or, more columns.

Parts of an Ideal Table Session 01 Body of the table: The data should be arranged in such a way that any figure can be located easily. Various types of numerical variables should be arranged in an ascending order, i. e. , from left to right in rows and from top to bottom in columns. Column and row totals should be given. Unit of measurement: If the unit of measurement is uniform throughout the table, it is stated at the top right-hand corner of the table along with the title. If different rows and columns contain figures in different units, the units may be stated along with “stubs”, or, “captions”. Very large figures may be rounded up but the method of rounding should be explained.

Parts of an Ideal Table Session 01 Source: At the bottom of the table a note should be added indicating the primary and secondary sources from which data have been collected. Footnotes and references: If any item has not been explained properly, a separate explanatory note should be added at the bottom of the table.

Limitation of Tabulation Tables contain only numerical data. They do not Session 01 contain details. qualitative expression is not possible through tables. Tables can be used by experts only to draw conclusions. Common men do not understand them properly.

Methods of Tabulation Session 02 Simple tabulation is when the data are tabulated to one characteristic. For example, the survey that determined the frequency or number of employees of a firm owning different brands of mobile phones like Blackberry, Nokia, Iphone, etc.

Methods of Tabulation Session 02 Double tabulation is when two characteristics of data are tabulated. For example, frequency or number of male and female employees in the firm owning different brand of mobile phones like Blackberry, Nokia, Iphone, etc.

Methods of Tabulation Session 02 Complex tabulation of data that includes more than two characteristics. For example, frequency or number of male, female and the total employees owning different brand of mobile phones like Blackberry, Nokia, Iphone, etc. Crosstabulations, is also a sub-type of complex tabulation that includes cross-classifying factors to build a contingency table of counts or frequencies at each combination of factor levels. A contingency table is a display format used to analyze and record the possible relationship between two or more categorical variables

Frequency Tables Session 03 Simple frequency tables Grouped frequency tables Cumulative frequency tables

Simple Frequency Tables If the value of a variable, e. g. , height, weight, etc. Session 03 (continuous), number of students in a class, readings of a taxi-meter (discrete) etc. , occurs twice or more in a given series of observations, then the number of occurrence of the value is termed as the “frequency” of that value.

Simple Frequency Tables Session 03 Marks of 100 students of a class in economics

Simple Frequency Tables Session 03 Simple frequency table for marks

Session 04 Grouped Frequency Tables The tabulation of raw data by dividing the whole range of observations into a number of classes and indicating the corresponding class-frequencies against the class-intervals, is called “grouped frequency distribution”. Thus the steps in preparing the grouped frequency distribution are: 1. Determining the class intervals. 2. Recording the data using tally marks. 3. Finding frequency of each class by counting the tally arks.

Grouped Frequency Tables Important Terms Session 04 Class-limits: The maximum and minimum values of a class-interval are called upper class limit and lower class-limit respectively Class-mark, or, Mid-value: The class-mark, or, mid-value of the class-interval lies exactly at the middle of the class-interval

Grouped Frequency Tables Session 04 Class boundaries: Class boundaries are the true- limits of a class interval. It is associated with grouped frequency distribution, where there is a gap between the upper class-limit and the lower class-limit of the next class. This can be determined by using the formula: where d = common difference between the upper class-limit of a class-interval and the lower class limit of the next higher class interval

Grouped Frequency Tables Width or Length (or size) of a Class-interval: Session 04 Width of a class-interval = Upper class boundary − Lower class-boundary Relative frequency:

Grouped Frequency Tables Session 04 Percentage frequency: Frequency density:

Grouped Frequency Tables Types of Grouped tables Exclusive type Session 04 Upper limit excluded X f 10 – 15 XX 15 – 20 XX 20 – 25 XX 25 – 30 XX

Grouped Frequency Tables Exclusive type Session 04 Lower limit excluded X f Above 10 but no more than 15 XX Above 15 but no more than 20 XX Above 20 but no more than 25 XX Above 25 but no more than 35 XX

Grouped Frequency Tables Exclusive types Session 04 Upper limit excluded X f 30 - XX 40 - XX 50 - XX 60 -70 XX

Grouped Frequency Tables Session 04 Inclusive type X f 30 – 39 XX 40 – 49 XX 50 – 59 XX 60 – 69 XX

Grouped Frequency Tables Session 04 Open – End Type X f 0 – 10 XX 10 – 20 XX 20 – 30 XX 30 – over XX X f Below 30 XX 30 – 40 XX 40 – 50 XX 50 and over XX

Grouped Frequency Tables Session 04 Unequal class intervals X f 10 – 30 XX 30 – 35 XX 35 – 40 XX 40 – 60 XX 60 – 70 XX 70 – 100 XX

Multivariate Frequency Tables Session 05 The multivariate frequency table is a statistic method to organize and simplify a large set of data of two or more variables in a single table. Example:

Multivariate Frequency Tables Session 05 Example: Multivariate frequency table

Multivariate Frequency Tables Session 05 Example: Marginal frequency tables for X and Y

Multivariate Frequency Tables Session 05 Example: Conditional Distribution X when Y Lies Between 300 and 400

Session 06 Cumulative Frequency Tables The cumulative frequency table of a set of data is a table which indicates the sum of the frequencies of the data up to a required level. It can be used to determine the number of items that have values below a particular level. Example: Construct the cumulative frequency distribution (both “less than” and “more than” types) from the following data:

Cumulative Frequency Tables Session 06 Example: Cumulative frequency table

Session 07 & 8 Cross Tabulation Cross-tabs or cross tabulation is a quantitative research method appropriate for analyzing the relationship between two or more variables. Data about variables is recorded in a table or matrix. A sample is used to gather information about the variable. Cross Tabulation gives you the ability to compare two questions to each other and evaluate relationships between the responses of those questions. You can review the frequency and assess the statistical significance in that relationship. Cross tabulation is particularly useful when you want to assess whethere is a relationship between how your entire respondent base, or a specific subset of respondents,

Cross Tabulation Session 07 & 8 General Hints When Constructing Tables 1. Make sure that all the categories of the variables presented in the tables have been specified and that they are mutually exclusive (i. e. no overlaps and no gaps) and exhaustive. 2. When making cross-tabulations, check that the column and row counts correspond to the frequency counts for each variable. 3. Check that the grand total in the table corresponds to the number of subjects in the sample. If not, an explanation is required. This could be presented as a footnote. (Missing data, for example. ) 4. Think of a clear title for each table. Also be sure that the headings of rows and columns leave no room for misinterpretation. 5. Number your tables and keep them together with the objectives to which they are related. This will assist in organizing your report and ensure that work is not duplicated.

Session 07 & 8 Cross Tabulation - Descriptive Cross Tabulation Example 1: A study was carried out on the degree of job satisfaction among doctors and nurses in rural and urban areas. To describe the sample a crosstabulation was constructed which included the sex and the residence (rural or urban) of the doctors and nurses interviewed. This was useful because in the analysis the opinions of male and female staff had to be compared separately for rural and urban areas. Type of health worker by residence

Cross Tabulation - Descriptive Cross Tabulation Session 07 & 8 Residence and sex of doctors and nurses

Session 07 & 8 Cross Tabulation - Descriptive Cross Tabulation Example 2: We want to know the ages at which teenage pregnancies occur and whether they are more frequent among schoolgirls than among girls who are not attending school. In order to answer these questions we may construct the following cross-tabulation. Number of teenage pregnancies at different ages among girls attending school and not attending school (Province X, 2000 - 2010)

Session 07 & 8 Cross Tabulation - Descriptive Cross Tabulation Example 3: A study was done to examine the factors contributing to the high proportion of stillbirths in a hospital. The following cross-tabulation describes how many of the fresh and macerated (wasted) stillbirths weighed less than 2500 grams and how many weighed 2500 grams or more. Weight of foetus by condition at birth

Session 07 & 8 Cross Tabulation - Descriptive Cross Tabulation Example 4: In a cross-sectional survey on malnutrition, for example, relationships could be tested between the duration of breastfeeding and the mothers’ age, or the mothers’ working status (answering previously formulated research questions, but sometimes new questions that crop up during analysis of the material). Note that in such tables it is allowed to calculate your percentages both horizontally and vertically as all variables have a similar chance of appearing in the survey. However, we will usually put the variable that is assumed to influence the other one in rows, while the ‘dependent’ variable will be put in columns

Cross Tabulation - Descriptive Cross Tabulation Session 07 & 8 Duration of breastfeeding by mothers’ age Working status of mothers in relation to duration of breastfeeding

Cross Tabulation - Analytic crosstabulations Session 07 & 8 Example 5: One of the possible contributing factors to malnutrition of under 5’s is knowledge of the mothers of appropriate weaning foods. The crosssectional comparative study on malnutrition based on the survey gave the following results Mothers’ level of knowledge and nutritional status of their children