Tabulation 2
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This document provides an overview of a quantitative techniques course for a B.Com program. It discusses the objectives of learning about tabulation, including presenting data in textual and tabular formats and constructing frequency distributions. It also covers types of tables like general tables and summary tables, as well as simple and complex tables. An example is provided for constructing a blank table to show employee distribution by sex, grade, age group, and year for a nationalized bank. Finally, it concludes with some multiple choice questions about topics like bivariate frequency distributions and the components of a statistical table.
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tabulation 3
This document summarizes a session on tabulation of data from a quantitative techniques course. It defines tabulation as systematically organizing data in rows and columns in a table. The objectives of tabulation are to simplify complex data, highlight essential features, facilitate comparison and statistical analysis, and save space. Rules for effective tabulation include using an appropriate table size, arranging column and row headers systematically, clearly defining units of measurement, rounding figures, avoiding unnecessary details, making the table self-explanatory, and avoiding abbreviations. Multiple choice questions are provided to test understanding.
Tabulation theory
This document summarizes a session on tabulation of data from a quantitative techniques course. It defines tabulation as systematically organizing data in rows and columns in a table. The objectives of tabulation are to simplify complex data, highlight essential features, facilitate comparison and statistical analysis, and save space. Rules for effective tabulation include using an appropriate table size, arranging column and row headers systematically, clearly defining units of measurement, rounding figures, avoiding unnecessary details, making the table self-explanatory, and avoiding abbreviations. Multiple choice questions are provided to test understanding of topics like the objectives of tabulation and characteristics of open-ended classes.
frequency distribution table 1
This document discusses the preparation of a frequency distribution table from a discrete data series. It provides an example of survey data from 20 homes on the number of cars registered to each household. The data is organized into a frequency distribution table with columns for the number of cars, tally marks, and frequencies. The table shows that 0 cars were recorded 3 times, 1 car was recorded 4 times, 2 cars 6 times, and so on, with the total of all frequencies equaling the 20 total data points. The document also provides the meaning and steps for creating a frequency distribution table, including organizing the data values and tallying the frequency of each value.
Frequency Distribution Table 1
This document discusses a lesson on quantitative techniques for a B.Com program. It covers preparing a frequency distribution table from a discrete data series. An example is given of survey results from 20 homes on the number of cars registered to each household. The data is presented in a frequency distribution table with columns for the number of cars, tally marks, and frequencies. Key steps discussed are forming a three column table, placing values in the first column, tallying occurrences in the second column, and counting tallies to record frequencies in the third column. The document also includes several multiple choice questions to test understanding.
Textual and tabular format problems
This document discusses presenting data in textual and tabular formats. It includes two examples showing how to take information about coffee drinking habits and candidates for university exams and present them in tables. The learning objectives are to teach students how to present data in textual and tabular formats, including creating frequency distributions and bi-variate tables. Students will learn about classification rules, class intervals, and principles of tabulation.
Blank Table 1
This document discusses presenting data in textual and tabular formats. It provides two examples of presenting comparative data from two towns about coffee drinking habits in a table. It also gives an example of drafting a blank table to show the number of candidates by sex, faculty, class and year appearing for degree examinations at a university. The document concludes with multiple choice questions about statistical tables.
Frequency Distribution Table 3
This document discusses the preparation of frequency distribution tables for continuous data series. It provides examples and steps for creating a grouped frequency distribution table, including deciding the number of classes, determining the range and class interval, and obtaining the class limits and frequencies to summarize the distribution. An example is given using test marks from 60 students to demonstrate creating a table with 10 class intervals. The document also includes review questions to assess understanding of key concepts like discrete versus continuous frequency distributions, exclusive classification limits, and how the number of classes is determined.
frequency distribution table 3
This document discusses the preparation of frequency distribution tables for continuous data series. It provides examples and steps for creating a grouped frequency distribution table, including deciding the number of classes, determining the range and class interval, and obtaining the class limits and frequencies to summarize the distribution. An example is given using test marks from 60 students to demonstrate creating a table with 10 class intervals. The document also includes review questions to assess understanding of key concepts like discrete versus continuous frequency distributions, exclusive classification limits, and how the number of classes is determined.
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tabulation 3
This document summarizes a session on tabulation of data from a quantitative techniques course. It defines tabulation as systematically organizing data in rows and columns in a table. The objectives of tabulation are to simplify complex data, highlight essential features, facilitate comparison and statistical analysis, and save space. Rules for effective tabulation include using an appropriate table size, arranging column and row headers systematically, clearly defining units of measurement, rounding figures, avoiding unnecessary details, making the table self-explanatory, and avoiding abbreviations. Multiple choice questions are provided to test understanding.
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frequency distribution table 1
This document discusses the preparation of a frequency distribution table from a discrete data series. It provides an example of survey data from 20 homes on the number of cars registered to each household. The data is organized into a frequency distribution table with columns for the number of cars, tally marks, and frequencies. The table shows that 0 cars were recorded 3 times, 1 car was recorded 4 times, 2 cars 6 times, and so on, with the total of all frequencies equaling the 20 total data points. The document also provides the meaning and steps for creating a frequency distribution table, including organizing the data values and tallying the frequency of each value.
Frequency Distribution Table 1
This document discusses a lesson on quantitative techniques for a B.Com program. It covers preparing a frequency distribution table from a discrete data series. An example is given of survey results from 20 homes on the number of cars registered to each household. The data is presented in a frequency distribution table with columns for the number of cars, tally marks, and frequencies. Key steps discussed are forming a three column table, placing values in the first column, tallying occurrences in the second column, and counting tallies to record frequencies in the third column. The document also includes several multiple choice questions to test understanding.
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This document discusses presenting data in textual and tabular formats. It includes two examples showing how to take information about coffee drinking habits and candidates for university exams and present them in tables. The learning objectives are to teach students how to present data in textual and tabular formats, including creating frequency distributions and bi-variate tables. Students will learn about classification rules, class intervals, and principles of tabulation.
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This document discusses presenting data in textual and tabular formats. It provides two examples of presenting comparative data from two towns about coffee drinking habits in a table. It also gives an example of drafting a blank table to show the number of candidates by sex, faculty, class and year appearing for degree examinations at a university. The document concludes with multiple choice questions about statistical tables.
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This document discusses the preparation of frequency distribution tables for continuous data series. It provides examples and steps for creating a grouped frequency distribution table, including deciding the number of classes, determining the range and class interval, and obtaining the class limits and frequencies to summarize the distribution. An example is given using test marks from 60 students to demonstrate creating a table with 10 class intervals. The document also includes review questions to assess understanding of key concepts like discrete versus continuous frequency distributions, exclusive classification limits, and how the number of classes is determined.
frequency distribution table 3
This document discusses the preparation of frequency distribution tables for continuous data series. It provides examples and steps for creating a grouped frequency distribution table, including deciding the number of classes, determining the range and class interval, and obtaining the class limits and frequencies to summarize the distribution. An example is given using test marks from 60 students to demonstrate creating a table with 10 class intervals. The document also includes review questions to assess understanding of key concepts like discrete versus continuous frequency distributions, exclusive classification limits, and how the number of classes is determined.
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This document discusses data classification and presentation. It defines classification as arranging data into homogenous groups based on characteristics. The purpose of classification is to simplify, organize and make data more meaningful for analysis. It discusses various types of classification including geographical, chronological, qualitative and quantitative. Frequency and frequency distribution are also explained, including frequency tables, grouped frequency tables and cumulative frequency tables. Various terminology used in classification are defined such as class limits, class intervals, and class boundaries. The document emphasizes that classification is important to systematically organize raw data for drawing conclusions.
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This document discusses classification, which is the process of arranging primary data into groups according to common characteristics. It defines classification and lists its objectives as facilitating comparison, striking homogeneity, and enabling further statistical analysis. The document describes types of classification like chronological, geographical, qualitative, and quantitative. It provides rules for classification, such as classes being exhaustive, mutually exclusive, and of equal magnitude. The document presents an example and MCQs to test understanding of classification concepts.
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This document discusses preparing frequency distribution tables from discrete data series. It provides examples of making tally marks and frequency counts from data on number of children per family and word counts in a passage. As we have discussed and learned today, preparing frequency distribution tables involves organizing discrete data into class intervals and counting the frequency of observations within each interval. This allows discrete data to be organized and summarized in a tabular format.
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The document discusses different methods of graphically representing frequency distributions: histograms, frequency polygons, and frequency curves. It provides examples of how to construct each type of graph using sample data on times taken to travel to school, net worth over years, and ages of pensioners. Students will learn how to analyze and interpret these graphs as well as how to present data using histograms, frequency polygons, frequency curves, and pie charts. The document concludes with sample multiple choice questions to test comprehension.
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This document discusses quantitative techniques as part of a B.Com program. It covers measures of central tendency and dispersion, including the mean, median, mode, range, mean deviation, and standard deviation. The learning objectives are to understand different measures of central tendency and dispersion. The learning outcomes are to differentiate, determine, and identify relationships between averages, and apply measures of dispersion to data by comparing standard deviation to mean deviation. The document also provides examples and practice questions on these topics.
Missing frequency 1
This document discusses a quantitative techniques course for a B.Com program. It covers measures of central tendency like mean, median, and mode. The learning objectives are to understand different measures of central tendency and dispersion. The learning outcomes are to differentiate, determine, and identify relationships between averages, and apply measures of dispersion to sample data. The session covers problems calculating missing frequencies and variables in the mean under discrete series. It provides two examples of finding missing values when the mean is given. The document concludes with multiple choice questions reviewing the material.
diagrams theory
This document discusses the presentation of quantitative data through diagrams. It begins by stating the learning objectives, which are for students to learn how to present data graphically using various charts and diagrams and calculate cumulative frequency. It then discusses different types of diagrams used for data presentation, including bar diagrams, pie charts, and two-dimensional diagrams. The key advantages of diagrams over tables are that they can more quickly and easily convey complex ideas in numbers and trends may be more noticeable. Guidelines for effective diagrams include giving them a clear title, using an appropriate size and scale, including a legend if multiple variables are shown, and selecting the correct type of diagram for the data. Common one-dimensional and two-dimensional diagram types are also listed.
KPC skewness 2
This document discusses measures of skewness, including Bowley's coefficient of skewness. It provides examples of calculating Bowley's coefficient using quartiles to determine if a distribution is skewed or symmetrical. The document also includes review questions related to skewness, Bowley's coefficient formula, and examples of its calculation using quartile data from continuous distributions.
Diagrams part 2
This document discusses one dimensional bar diagrams, including simple and subdivided bar diagrams. It provides examples of how to construct simple and component bar diagrams to present statistical data comparing production costs between companies and expenditures across categories for two schools. Multiple choice questions are also included at the end to test understanding of diagrammatic data presentation.
Mean Deviation and Co- efficient
This document discusses quantitative techniques for a B.Com program. It covers measures of central tendency and dispersion such as mean, median, mode, range, mean deviation, standard deviation, and quartile deviation. The learning objectives are to understand these concepts and apply them to sample data. An example is provided to calculate the mean deviation and coefficient of mean deviation from the mean, median, and mode for household income data. Multiple choice questions review key concepts like the definition of mean deviation and properties of variance. References for further reading on statistics are also included.
graphical representation 6
This document discusses quantitative techniques and constructing graphs from data. It covers constructing less than and more than ogive curves, which are cumulative frequency curves. An ogive curve shows the cumulative frequency distribution and can be used to find the median. Two problems are presented on drawing less than and more than ogive curves from data on weights of items and ages of pensioners. Multiple choice questions are also provided to test understanding of ogives and cumulative frequency polygons.
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Tabulation 2
- 1. PROGRAMME B.COM SUBJECT QUANTITATIVE TECHNIQUE – I SEMESTER III UNIVERSITY VIJAYANAGAR SRI KRISHNADEVARAYA UNIVERSITY, BALLARI SESSION 16
- 2. RECAP • Tabulation of Data, Meaning, Objectives & Rules for Tabulation
- 3. LEARNING OBJECTIVES • The aim of the chapter is to make students to present data in textual and Tabular format including the technique of creating frequency distribution and working out bi-variate distribution table
- 4. LEARNING OUTCOMES • After the Chapter, The Students Shall be able to Describe and Understand the Rules & Types of Classification, Frequency Distribution, Class Interval & its Types, Basic Principles Tabulation and The Sorting of Data.
- 5. SESSION - 16 • Types of Tables, Preparation of Blank Table and Problems - 01
- 6. Types of Tables • Statistical tables can be classified under two general categories, namely, general tables and summary tables. General tables contain a collection of detailed information including all that is relevant to the subject or theme. Summary tables are designed to serve some specific purposes. They are smaller in size than general tables, emphasize on some aspect of data and are generally incorporated within the text.
- 7. CONTD • The statistical tables may further be classified into two broad classes namely simple tables and complex tables. A simple table summarizes information on a single characteristic and is also called a univariate table. A complex table summarizes the complicated information and presents them into two or more interrelated categories.
- 8. Preparation of Blank Table FORMAT OF TABLE TITLE HEAD NOTE Footnote Table Number Source STUB HEADING CAPTION COLUMN HEADING / COLUMN HEADING SUB ENTRIES BODY
- 9. Example 01 • Draft a blank table to show the distribution of employees in a in a nationalized bank according to Sex ; Male and Female Grade ; Below Rs. 1000, Rs.1000-1500, Periods ; 2011 and 2012 Age Group ; Below 25, 25-40,
- 10. CONTD Distribution Of Employees Of A Nationalized Bank (Age, Sex, Salary, and For Two years) YEA R AGE GRO-- UPS GRADE SALARIES TOTAL BELOW RS 1000 RS 1000- 1500 2011 Below 25 25-40 MALE FEMALE TOTAL MALE FEMALE TOTAL MALE FEMALE TOTAL TOTAL 2012 Below 25 25-40 TOTAL
- 11. SUMMARY As we already discussed and learnt today on Classifications and Tabulation as below • Types of Tables, Preparation of Blank Table and Problems 01
- 12. MCQs 1 . A frequency distribution formed considering two variables at a time is called: (a) Univariate frequency distribution (b) Bivariate frequency distribution (c) Trivariate frequency distribution (d) Bimodal distribution 2 . The arrangement of data in rows and columns is called: (a) Classification (b) Tabulation (c) Frequency distribution (d) Cumulative frequency distribution
- 13. MCQs 3 . When the qualitative or quantitative raw data are classified according to one characteristic, the tabulation of different groups is called: (a) Dichotomy (b) Manifold-division (c) Bivariate (d) One-way 4 . A statistical table consists of at least: (a) Two parts (b) Three parts (c) Four parts (d) Five parts
- 14. MCQs 5 . In a statistical table, prefatory note is shown: (a) Below the body (b) Box head ` (c) Foot note (d) Below the title
- 15. CONTD ANSWERS 1. B 2. B 3. D 4. C 5. D
- 16. REFERENCES • S.P. Gupta, Sultan Chand and Sons Publications, 2017 • S. C. Gupta, Himalaya Publishing House, Fundamentals of Statistics, 2018 • R.S.N Pillai and Bagavathi, S.Chand publications, 2010
- 17. THANK YOU