Bivariate table 1
•
0 likes•16 views
This document discusses bi-variate frequency distribution tables. It begins with recapping univariate frequency distributions and introducing bi-variate distributions, which involve classifying data based on two variables simultaneously. The steps for creating a bi-variate frequency distribution table are described, including determining class intervals for each variable and placing them on the table axes to create cells for tallying observations. An example of population height and weight data classified into a bi-variate table is shown. Multiple choice questions reviewing key concepts of frequency distributions are also presented.
Report
Share
Report
Share
Recommended
Bi variate Table 2
This document discusses a quantitative techniques course covering bi-variate frequency distribution tables. It provides two examples of creating bi-variate tables using students' exam marks and husbands and wives ages. The first example uses data on 20 students' marks in two subjects to create a table grouping the marks into class intervals of 10. The second example uses ages of 22 husbands and wives, creating a table grouping both spouses' ages into class intervals of 5 years. The document ends with multiple choice questions to test understanding of frequency distributions, classifications and bi-variate tables.
Bi variate frequency distribution table 2
This document discusses a quantitative techniques course for a B.Com program. It covers bi-variate frequency distribution tables, including two practice problems. The first problem provides marks from 20 students in two subjects and requires students to create a bi-variate frequency distribution table with class intervals of 10. The second problem provides ages of 22 husbands and wives and requires a similar table to be made with class intervals of 5 years. The document concludes with multiple choice questions to test understanding of frequency distributions and classifications.
Frequency Distribution Table 5
This document discusses frequency distribution tables and includes three examples of creating frequency distribution tables from raw data. It summarizes the key steps as: 1) Preparation of Frequency Distribution Table - Continuous Series(Inclusive) Problems -03; 2) Three examples are provided of constructing frequency distribution tables from raw data by grouping the data into class intervals; 3) Multiple choice questions are then provided to test understanding of concepts related to frequency distribution tables like class intervals, class boundaries, and class limits.
frequency distribution table 5
This document discusses frequency distribution tables and includes three examples. It summarizes the key steps in creating frequency distribution tables: (1) grouping data into class intervals, (2) tallying the frequency of values within each interval, and (3) constructing a table with the class intervals, tallies, and frequencies. Three examples are provided that demonstrate creating frequency distribution tables using both inclusive and exclusive class intervals for sets of student test scores and worker hours. The document concludes with multiple choice questions to test understanding of class intervals, boundaries, and other concepts relating to frequency distribution tables.
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.
Classification Theory
This document provides an overview of quantitative techniques taught in a B.Com program. It discusses types of classification, including classification by time, space, and attributes. It also discusses types of frequency distributions, including individual, discrete, and continuous distributions. Specifically, it defines continuous distributions as those where variables can take any value between minimum and maximum, and defines key terms for continuous distributions like class limits, class intervals, class frequency, and cumulative frequency. The document aims to help students understand how to present and analyze data through classification and frequency distributions.
Tabulation and Classification
This document provides an overview of quantitative techniques taught in a B.Com program. It discusses types of classification, including classification by time, space, and attributes. It also discusses types of frequency distributions, including individual, discrete, and continuous distributions. Specifically, it defines continuous distributions as those where variables can take any value between minimum and maximum, and defines key terms for continuous distributions like class limits, class intervals, class frequency, and cumulative frequency. The document aims to help students understand how to present and analyze data through classification and frequency distributions.
Recommended
Bi variate Table 2
This document discusses a quantitative techniques course covering bi-variate frequency distribution tables. It provides two examples of creating bi-variate tables using students' exam marks and husbands and wives ages. The first example uses data on 20 students' marks in two subjects to create a table grouping the marks into class intervals of 10. The second example uses ages of 22 husbands and wives, creating a table grouping both spouses' ages into class intervals of 5 years. The document ends with multiple choice questions to test understanding of frequency distributions, classifications and bi-variate tables.
Bi variate frequency distribution table 2
This document discusses a quantitative techniques course for a B.Com program. It covers bi-variate frequency distribution tables, including two practice problems. The first problem provides marks from 20 students in two subjects and requires students to create a bi-variate frequency distribution table with class intervals of 10. The second problem provides ages of 22 husbands and wives and requires a similar table to be made with class intervals of 5 years. The document concludes with multiple choice questions to test understanding of frequency distributions and classifications.
Frequency Distribution Table 5
This document discusses frequency distribution tables and includes three examples of creating frequency distribution tables from raw data. It summarizes the key steps as: 1) Preparation of Frequency Distribution Table - Continuous Series(Inclusive) Problems -03; 2) Three examples are provided of constructing frequency distribution tables from raw data by grouping the data into class intervals; 3) Multiple choice questions are then provided to test understanding of concepts related to frequency distribution tables like class intervals, class boundaries, and class limits.
frequency distribution table 5
This document discusses frequency distribution tables and includes three examples. It summarizes the key steps in creating frequency distribution tables: (1) grouping data into class intervals, (2) tallying the frequency of values within each interval, and (3) constructing a table with the class intervals, tallies, and frequencies. Three examples are provided that demonstrate creating frequency distribution tables using both inclusive and exclusive class intervals for sets of student test scores and worker hours. The document concludes with multiple choice questions to test understanding of class intervals, boundaries, and other concepts relating to frequency distribution tables.
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.
Classification Theory
This document provides an overview of quantitative techniques taught in a B.Com program. It discusses types of classification, including classification by time, space, and attributes. It also discusses types of frequency distributions, including individual, discrete, and continuous distributions. Specifically, it defines continuous distributions as those where variables can take any value between minimum and maximum, and defines key terms for continuous distributions like class limits, class intervals, class frequency, and cumulative frequency. The document aims to help students understand how to present and analyze data through classification and frequency distributions.
Tabulation and Classification
This document provides an overview of quantitative techniques taught in a B.Com program. It discusses types of classification, including classification by time, space, and attributes. It also discusses types of frequency distributions, including individual, discrete, and continuous distributions. Specifically, it defines continuous distributions as those where variables can take any value between minimum and maximum, and defines key terms for continuous distributions like class limits, class intervals, class frequency, and cumulative frequency. The document aims to help students understand how to present and analyze data through classification and frequency distributions.
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.
Frequency Distribution Table 4
The document summarizes a lesson on creating frequency distribution tables from quantitative data. It includes two examples of constructing frequency tables from lists of marks and parts used in a mill. The class intervals are grouped and the frequency of data points within each interval is counted. Multiple choice questions at the end review key concepts like calculating the number of classes and identifying class intervals versus class limits.
frequency distribution table 4
The document summarizes a lesson on quantitative techniques that included:
1) Preparing frequency distribution tables with continuous series problems and examples using student marks and machine part replacements.
2) The class intervals, tallies, and frequencies were shown for the example problems.
3) Multiple choice questions were provided to test understanding of key concepts like calculating the number of classes and identifying class intervals versus limits.
Types of table, Preparation of Blank table
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 creating 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 drafting 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.
Tabulation 2
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.
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.
graphical representation 5
This document discusses cumulative frequency curves or ogives. It provides examples of how to construct more than ogive curves using data from frequency distributions. Specifically, it discusses how the more than cumulative frequency is plotted against the lower limit of each class to form the curve. Two example problems are worked through demonstrating how to draw the more than ogive curve from data on test marks and pensioner ages. Multiple choice questions are also provided to assess understanding of key concepts like the different types of ogive curves and how cumulative frequency polygons are used.
frequency distribution table 2
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.
Frequency Distribution Table 2
This document discusses preparing frequency distribution tables from discrete data series. It provides examples of creating frequency distribution tables from survey data on family sizes and word counts in a passage. The learning objectives are to present data in tables and calculate bi-variate distributions. Students will learn about classification, frequency distributions, class intervals, and sorting data into tables. Multiple choice questions review key concepts like discrete vs continuous distributions and the form of frequency data.
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.
Classification of Data
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.
Bowley skewness 1
This document discusses Bowley's coefficient of skewness, which is a measure of the skewness of a data distribution based on the positions of the quartiles. It provides examples of calculating Bowley's skewness for individual and discrete data series by finding the first quartile, third quartile, and median. The document also includes multiple choice questions to test understanding of measures of skewness, Karl Pearson's coefficient of skewness, and Bowley's coefficient of skewness.
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.
Crafting Effective Tables of Specifications (TOS).pptx
Crafting Effective Tables of Specifications for Course Assessment
The document discusses how to create tables of specifications (TOS) to plan assessments. A TOS is a two-way chart that maps learning objectives, content areas, cognitive levels, and the number of assessment items. It ensures assessments are well-balanced, aligned with course objectives, and avoid biases. The document provides a step-by-step process to create a TOS, including identifying objectives, categorizing cognitive levels, defining content, creating the table, distributing percentages, justifying distributions, and writing sample questions. An effective TOS leads to valid, fair assessments that better support student learning.
Mean, median & mode 2
This document discusses measures of central tendency and dispersion such as mean, median, mode, range, standard deviation, and quartile deviation. It provides examples of calculating the mean, median, and mode for continuous data series. One example calculates the mean as 36.31, median as 34.5, and mode using the formula Z = 3Me - 2X as 30.88. The document also includes multiple choice questions related to relationships between averages and identifying averages based on values given. It recommends statistics textbooks for additional reference on topics discussed.
KPC skewness 1
This document discusses Karl Pearson's Coefficient of Skewness, a method for measuring the skewness of a data distribution. It provides examples of calculating the coefficient under individual and discrete series. For an individual series with data points ranging from 35 to 75 and a mean of 55, the coefficient is calculated to be 0.77, indicating positive skewness. For a discrete series with wage data, the coefficient is calculated to be -0.26, indicating negative skewness. The document also includes multiple choice questions to test understanding of skewness and the relationships between the mean, median and mode of a distribution.
mean median mode 3
This document outlines a course on quantitative techniques for a B.Com program. It discusses key concepts students will learn, including different measures of central tendency (mean, median, mode) and dispersion. It covers the merits and demerits of each measure of central tendency. Example problems are provided to demonstrate calculating and comparing means, medians, and modes. Multiple choice questions at the end test understanding of these concepts.
Mean, median & mode 1
This document discusses a quantitative techniques course for a B.Com program. It covers measures of central tendency and dispersion, including the mean, median, mode, and standard deviation. The learning objectives are to understand these concepts and apply them to sample data. The session discusses calculating the mean, median, and mode for individual and discrete data series. It provides an example of calculating these values for a set of wage and employee data. Multiple choice questions review key aspects of the measures discussed.
Range, Q.D and Co-efficient 2
This document outlines the key topics and objectives of a Quantitative Techniques course for a B.Com program. The learning objectives are to understand measures of central tendency and dispersion such as mean, median, mode, range, mean deviation, standard deviation, and quartile deviation. Example problems are provided to calculate range, quartile deviation, and the coefficient of quartile deviation from wage distribution data. Multiple choice questions are also included as a review of the concepts taught.
More Related Content
Similar to Bivariate table 1
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.
Frequency Distribution Table 4
The document summarizes a lesson on creating frequency distribution tables from quantitative data. It includes two examples of constructing frequency tables from lists of marks and parts used in a mill. The class intervals are grouped and the frequency of data points within each interval is counted. Multiple choice questions at the end review key concepts like calculating the number of classes and identifying class intervals versus class limits.
frequency distribution table 4
The document summarizes a lesson on quantitative techniques that included:
1) Preparing frequency distribution tables with continuous series problems and examples using student marks and machine part replacements.
2) The class intervals, tallies, and frequencies were shown for the example problems.
3) Multiple choice questions were provided to test understanding of key concepts like calculating the number of classes and identifying class intervals versus limits.
Types of table, Preparation of Blank table
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 creating 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 drafting 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.
Tabulation 2
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.
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.
graphical representation 5
This document discusses cumulative frequency curves or ogives. It provides examples of how to construct more than ogive curves using data from frequency distributions. Specifically, it discusses how the more than cumulative frequency is plotted against the lower limit of each class to form the curve. Two example problems are worked through demonstrating how to draw the more than ogive curve from data on test marks and pensioner ages. Multiple choice questions are also provided to assess understanding of key concepts like the different types of ogive curves and how cumulative frequency polygons are used.
frequency distribution table 2
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.
Frequency Distribution Table 2
This document discusses preparing frequency distribution tables from discrete data series. It provides examples of creating frequency distribution tables from survey data on family sizes and word counts in a passage. The learning objectives are to present data in tables and calculate bi-variate distributions. Students will learn about classification, frequency distributions, class intervals, and sorting data into tables. Multiple choice questions review key concepts like discrete vs continuous distributions and the form of frequency data.
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.
Classification of Data
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.
Bowley skewness 1
This document discusses Bowley's coefficient of skewness, which is a measure of the skewness of a data distribution based on the positions of the quartiles. It provides examples of calculating Bowley's skewness for individual and discrete data series by finding the first quartile, third quartile, and median. The document also includes multiple choice questions to test understanding of measures of skewness, Karl Pearson's coefficient of skewness, and Bowley's coefficient of skewness.
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.
Crafting Effective Tables of Specifications (TOS).pptx
Crafting Effective Tables of Specifications for Course Assessment
The document discusses how to create tables of specifications (TOS) to plan assessments. A TOS is a two-way chart that maps learning objectives, content areas, cognitive levels, and the number of assessment items. It ensures assessments are well-balanced, aligned with course objectives, and avoid biases. The document provides a step-by-step process to create a TOS, including identifying objectives, categorizing cognitive levels, defining content, creating the table, distributing percentages, justifying distributions, and writing sample questions. An effective TOS leads to valid, fair assessments that better support student learning.
Similar to Bivariate table 1 (17)
Crafting Effective Tables of Specifications (TOS).pptx
Crafting Effective Tables of Specifications (TOS).pptx
More from AkkiMaruthi2
Mean, median & mode 2
This document discusses measures of central tendency and dispersion such as mean, median, mode, range, standard deviation, and quartile deviation. It provides examples of calculating the mean, median, and mode for continuous data series. One example calculates the mean as 36.31, median as 34.5, and mode using the formula Z = 3Me - 2X as 30.88. The document also includes multiple choice questions related to relationships between averages and identifying averages based on values given. It recommends statistics textbooks for additional reference on topics discussed.
KPC skewness 1
This document discusses Karl Pearson's Coefficient of Skewness, a method for measuring the skewness of a data distribution. It provides examples of calculating the coefficient under individual and discrete series. For an individual series with data points ranging from 35 to 75 and a mean of 55, the coefficient is calculated to be 0.77, indicating positive skewness. For a discrete series with wage data, the coefficient is calculated to be -0.26, indicating negative skewness. The document also includes multiple choice questions to test understanding of skewness and the relationships between the mean, median and mode of a distribution.
mean median mode 3
This document outlines a course on quantitative techniques for a B.Com program. It discusses key concepts students will learn, including different measures of central tendency (mean, median, mode) and dispersion. It covers the merits and demerits of each measure of central tendency. Example problems are provided to demonstrate calculating and comparing means, medians, and modes. Multiple choice questions at the end test understanding of these concepts.
Mean, median & mode 1
This document discusses a quantitative techniques course for a B.Com program. It covers measures of central tendency and dispersion, including the mean, median, mode, and standard deviation. The learning objectives are to understand these concepts and apply them to sample data. The session discusses calculating the mean, median, and mode for individual and discrete data series. It provides an example of calculating these values for a set of wage and employee data. Multiple choice questions review key aspects of the measures discussed.
Range, Q.D and Co-efficient 2
This document outlines the key topics and objectives of a Quantitative Techniques course for a B.Com program. The learning objectives are to understand measures of central tendency and dispersion such as mean, median, mode, range, mean deviation, standard deviation, and quartile deviation. Example problems are provided to calculate range, quartile deviation, and the coefficient of quartile deviation from wage distribution data. Multiple choice questions are also included as a review of the concepts taught.
graphical representation 1
This document discusses graphical representation of quantitative data. It explains that graphs are better suited than diagrams for statistical analysis as they allow interpolation, extrapolation and locating values like the median and quartiles. Diagrams are only for comparison. The document then contrasts key differences between diagrams and graphs. Finally, it provides general rules for creating graphs and examples of questions to test comprehension.
KPC skewness 2
This document discusses Karl Pearson's Coefficient of Skewness. It provides the formula for Karl Pearson's Coefficient of Skewness as SK= Mean - Mode/ S.D. An example calculation is shown to demonstrate computing the coefficient from sample data. Multiple choice questions are also provided to test understanding. The learning objectives are to understand measures of skewness including Karl Pearson's Coefficient of Skewness and how to apply it to sample data to analyze the normalcy and skewness of distributions.
graphical representation 4
This document discusses constructing cumulative frequency (ogive) curves from data. It begins by recapping how to create histograms, frequency polygons, and pie charts. Then it provides learning objectives and outcomes around analyzing and presenting data graphically using these visualizations. The main content explains how to calculate less than and more than cumulative frequencies and draw the corresponding ogive curves. It gives examples of drawing less than ogive curves for two data sets listing number of workers by daily wage and number of pensioners by age group. Finally, it presents multiple choice questions to test understanding of ogive curves.
graphical representation 2
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.
Measures of Dispersion
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.
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.
Diagrams part 3
This document discusses quantitative techniques for a B.Com program. It covers one dimensional bar diagrams, including percentage and multiple bar diagrams. It provides examples of problems involving percentage and multiple bar diagrams with solutions. It also includes learning objectives and outcomes about presenting and interpreting data graphically using various charts and diagrams. There are example problems and solutions for constructing percentage and multiple bar diagrams from given data. The document concludes with multiple choice questions and answers about different types of bar diagrams.
graphical representation 3
This document discusses quantitative techniques for constructing graphs such as histograms, frequency polygons, and frequency curves from data. It provides examples of problems involving drawing these different types of graphs based on data about student heights, company net worth, and pensioner ages. The document also includes multiple choice questions about histograms, frequency polygons, pie charts, and other graphical representations of data.
Diagrams part 4
This document discusses different types of two-dimensional bar diagrams that can be used to represent data graphically, including squares, pie diagrams, and rectangle bar diagrams. It provides examples of how to construct these diagrams from sample data about sales over time and expenditures by schools. Students learn how to analyze and interpret these diagrams within their given contexts. The document also includes multiple choice questions to test comprehension.
More from AkkiMaruthi2 (18)
Recently uploaded
Walmart Business+ and Spark Good for Nonprofits.pdf
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
Chapter 4 - Islamic Financial Institutions in Malaysia.pptx
Chapter 4 - Islamic Financial Institutions in Malaysia.pptxMohd Adib Abd Muin, Senior Lecturer at Universiti Utara Malaysia
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
The Diamonds of 2023-2024 in the IGRA collection
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...Nguyen Thanh Tu Collection
https://app.box.com/s/tacvl9ekroe9hqupdnjruiypvm9rdaneHow to Fix the Import Error in the Odoo 17
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
How to deliver Powerpoint Presentations.pptx
"How to make and deliver dynamic presentations by making it more interactive to captivate your audience attention"
Main Java[All of the Base Concepts}.docx
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Chapter wise All Notes of First year Basic Civil Engineering.pptx
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...Nguyen Thanh Tu Collection
https://app.box.com/s/y977uz6bpd3af4qsebv7r9b7s21935vdPollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...National Information Standards Organization (NISO)
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Aberdeen
BÀI TẬP DẠY THÊM TIẾNG ANH LỚP 7 CẢ NĂM FRIENDS PLUS SÁCH CHÂN TRỜI SÁNG TẠO ...
BÀI TẬP DẠY THÊM TIẾNG ANH LỚP 7 CẢ NĂM FRIENDS PLUS SÁCH CHÂN TRỜI SÁNG TẠO ...Nguyen Thanh Tu Collection
https://app.box.com/s/qhtvq32h4ybf9t49ku85x0n3xl4jhr15Wound healing PPT
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
clinical examination of hip joint (1).pdf
described clinical examination all orthopeadic conditions .
Recently uploaded (20)
Walmart Business+ and Spark Good for Nonprofits.pdf
Walmart Business+ and Spark Good for Nonprofits.pdf
Chapter 4 - Islamic Financial Institutions in Malaysia.pptx
Chapter 4 - Islamic Financial Institutions in Malaysia.pptx
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
BÀI TẬP BỔ TRỢ TIẾNG ANH LỚP 9 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2024-2025 - ...
Chapter wise All Notes of First year Basic Civil Engineering.pptx
Chapter wise All Notes of First year Basic Civil Engineering.pptx
Film vocab for eal 3 students: Australia the movie
Film vocab for eal 3 students: Australia the movie
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
BÀI TẬP DẠY THÊM TIẾNG ANH LỚP 7 CẢ NĂM FRIENDS PLUS SÁCH CHÂN TRỜI SÁNG TẠO ...
BÀI TẬP DẠY THÊM TIẾNG ANH LỚP 7 CẢ NĂM FRIENDS PLUS SÁCH CHÂN TRỜI SÁNG TẠO ...
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
NEWSPAPERS - QUESTION 1 - REVISION POWERPOINT.pptx
Bivariate table 1
- 1. PROGRAMME B.COM SUBJECT QUANTITATIVE TECHNIQUE – I SEMESTER III UNIVERSITY VIJAYANAGAR SRI KRISHNADEVARAYA UNIVERSITY, BALLARI SESSION 13
- 2. RECAP • Preparation of Frequency Distribution Table - Continuous Series(Inclusive) Problems -03
- 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 - 13 • Bi-Variate Frequency Distribution Table Meaning & Problems-------- 01
- 6. Bi-Variate Frequency Distribution Table Meaning; • Frequency distributions involving one variable are called univariate frequency distribution. In many situations it may be necessary to study two variables simultaneously. • For example, we want to study the age of wives and husbands, height and weight of students. • The data classified on the basis of two variables is called a Bi-Variate Frequency Distribution Table.
- 7. CONTD • STEPS OF BI-VARIATE FREQUENCY DISTRIBUTION Determine the suitable class interval of each variable Write one of class interval vertically on the left hand side of the table and other at the top horizontally A tally mark has to be put in the cell where the variables intersect in both class intervals Repeat the procedure till to exhaust all the variables or observations Total the tally marks of the column and keep at the bottom. Similarly, rows tally marks total it and keep at the right side of the table
- 8. EXAMPLE 1 • The given below data related to the height and weight of 20 persons. You are required to form a Bi-variate frequency table with class intervals 62-64, 64-66 for height and 115-125, 125-135 for weight Weight 169 134 135 136 147 124 117 127 143 129 Height 69 64 64 65 68 63 64 70 71 62 Weight 162 140 122 133 140 133 120 148 128 151 Height 69 67 64 68 67 68 65 67 66 66
- 9. CONTD BI-VARIATE FREQUENCY DISTRIBUTION WEIGHT HEIGHT 62-64 64-66 66-68 68-70 70-72 TOTAL 115-125 I III -- -- -- 4 125-135 I I I II I 6 135-145 -- II II -- I 5 145-155 -- -- II I -- 3 155-165 -- -- -- I -- 1 165-175 -- -- -- I -- 1 TOTAL 2 6 5 5 2 20
- 10. SUMMARY As we already discussed and learnt today on Classifications and Tabulation as below • Bi-Variate Frequency Distribution Table Meaning & Problems-------- 01
- 11. MCQs 1 . The class marks are given below: 10,12,14,16,18. The first class of the distribution is: (a) 9----12 (b) 10.5----12.5 (c) 9----11 (d) 10----12 2 . If the midpoints are 10, 15, 20, 25 and 30. The last class boundary of the distribution is: (a) 25----30 (b) 27.5----32.5 (c) 20----35 (d) 30----35
- 12. MCQs 3 . The number of classes depends upon: (a) Class marks (b) Frequency (c) Class interval (d) Class boundary 4 . The class interval is the difference between: (a) Two extreme values (b) Two successive frequencies (c) Two successive upper limits (d) Two largest values
- 13. MCQs 5 . When the classes are 40----44, 45----49, 50----54, ... the class interval is: (a) 4 (b) 6 (c) 100 (d) 5
- 14. CONTD ANSWERS 1. C 2. B 3. C 4. C 5. D
- 15. 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
- 16. THANK YOU