The document discusses organizing and presenting data through descriptive statistics. It covers types of data, constructing frequency distribution tables, calculating relative frequencies and percentages, and using graphical methods like bar graphs, pie charts, histograms and polygons to summarize categorical and quantitative data. Examples are provided to demonstrate how to organize data into frequency distributions and calculate relative frequencies to graph the results.
Frequency Distribution (Class-interval- Tally).pptxAlwinCAsuncion
The document defines various measures of central tendency including mean, median, and mode for both ungrouped and grouped data. It also defines key terms related to frequency distributions such as lower class limit, upper class limit, class boundaries, class marks, class width, and cumulative frequency. An example is provided to illustrate the construction of a grouped frequency distribution table involving 7 classes with a class width of 7 using data on exam scores of 40 students.
This document discusses key concepts in utilizing assessment data through statistics. It defines statistics as dealing with quantitative data collection, presentation, analysis and interpretation. Descriptive statistics describe data without inferences, while inferential statistics allow predictions about a larger data set from a sample. Frequency distributions tabulate data into categories to make it more interpretable. They include class limits, size, boundaries, and marks. Steps for constructing distributions include determining the range, class size, limits, boundaries, tallying scores, and identifying other parts. An example constructs a distribution from exam scores using these steps.
Frequency_Distribution-1.ppt *Constructing Frequency Distribution Table)MayFelwa
The document discusses frequency distributions and how to construct them. It provides guidelines for constructing a frequency distribution, including deciding on the number of classes, finding the class width and limits, tallying data points into classes, and counting the tallies to determine frequencies. An example is shown of constructing a frequency distribution for a data set of 30 students' ages, with classes determined to have an interval size of 8 years based on 5 total classes.
Analysis and interpretation of Assessment.pptxAeonneFlux
The document provides information on statistics, frequency distributions, measures of central tendency (mean, median, mode), and how to calculate and interpret them. It defines statistics, descriptive and inferential statistics, and frequency distributions. It outlines the steps to construct a frequency distribution and calculate the mean, median, and mode for both ungrouped and grouped data. Examples are provided to demonstrate calculating each measure of central tendency.
This document discusses different methods for organizing data in research. It describes data organization as the process of structuring collected factual information in a way that is accepted by the scientific community. Proper data organization is important for research because it allows facts to be represented in context and helps researchers answer questions and hypotheses. The document then explains three common ways to organize data: frequency distribution tables, stem-and-leaf diagrams, and different types of charts including bar charts, pie charts, line charts, and histograms. Guidelines are provided for constructing each of these data organization methods.
Descriptive statistics can summarize and graphically present data. Tabular presentations display data in a grid, with tables showing frequencies of categories. Graphical presentations include bar graphs to show frequencies, pie charts to show proportions, and line graphs to show trends over time. Frequency distributions organize raw data into meaningful patterns for analysis by specifying class intervals and calculating frequencies and cumulative frequencies.
Mathematics 7 Frequency Distribution Table.pptxJeraldelEncepto
The document provides instructions for constructing a frequency distribution table using test score data from 60 students. It explains how to determine the number of class intervals, calculate the class width, tally the scores within each interval, and record the frequencies. The steps include finding the range of scores, dividing the range by the number of intervals, establishing the class limits, and populating the frequency table with tallies and counts.
The document discusses organizing and presenting data through descriptive statistics. It covers types of data, constructing frequency distribution tables, calculating relative frequencies and percentages, and using graphical methods like bar graphs, pie charts, histograms and polygons to summarize categorical and quantitative data. Examples are provided to demonstrate how to organize data into frequency distributions and calculate relative frequencies to graph the results.
Frequency Distribution (Class-interval- Tally).pptxAlwinCAsuncion
The document defines various measures of central tendency including mean, median, and mode for both ungrouped and grouped data. It also defines key terms related to frequency distributions such as lower class limit, upper class limit, class boundaries, class marks, class width, and cumulative frequency. An example is provided to illustrate the construction of a grouped frequency distribution table involving 7 classes with a class width of 7 using data on exam scores of 40 students.
This document discusses key concepts in utilizing assessment data through statistics. It defines statistics as dealing with quantitative data collection, presentation, analysis and interpretation. Descriptive statistics describe data without inferences, while inferential statistics allow predictions about a larger data set from a sample. Frequency distributions tabulate data into categories to make it more interpretable. They include class limits, size, boundaries, and marks. Steps for constructing distributions include determining the range, class size, limits, boundaries, tallying scores, and identifying other parts. An example constructs a distribution from exam scores using these steps.
Frequency_Distribution-1.ppt *Constructing Frequency Distribution Table)MayFelwa
The document discusses frequency distributions and how to construct them. It provides guidelines for constructing a frequency distribution, including deciding on the number of classes, finding the class width and limits, tallying data points into classes, and counting the tallies to determine frequencies. An example is shown of constructing a frequency distribution for a data set of 30 students' ages, with classes determined to have an interval size of 8 years based on 5 total classes.
Analysis and interpretation of Assessment.pptxAeonneFlux
The document provides information on statistics, frequency distributions, measures of central tendency (mean, median, mode), and how to calculate and interpret them. It defines statistics, descriptive and inferential statistics, and frequency distributions. It outlines the steps to construct a frequency distribution and calculate the mean, median, and mode for both ungrouped and grouped data. Examples are provided to demonstrate calculating each measure of central tendency.
This document discusses different methods for organizing data in research. It describes data organization as the process of structuring collected factual information in a way that is accepted by the scientific community. Proper data organization is important for research because it allows facts to be represented in context and helps researchers answer questions and hypotheses. The document then explains three common ways to organize data: frequency distribution tables, stem-and-leaf diagrams, and different types of charts including bar charts, pie charts, line charts, and histograms. Guidelines are provided for constructing each of these data organization methods.
Descriptive statistics can summarize and graphically present data. Tabular presentations display data in a grid, with tables showing frequencies of categories. Graphical presentations include bar graphs to show frequencies, pie charts to show proportions, and line graphs to show trends over time. Frequency distributions organize raw data into meaningful patterns for analysis by specifying class intervals and calculating frequencies and cumulative frequencies.
Mathematics 7 Frequency Distribution Table.pptxJeraldelEncepto
The document provides instructions for constructing a frequency distribution table using test score data from 60 students. It explains how to determine the number of class intervals, calculate the class width, tally the scores within each interval, and record the frequencies. The steps include finding the range of scores, dividing the range by the number of intervals, establishing the class limits, and populating the frequency table with tallies and counts.
This document discusses frequency distributions and methods for graphically presenting frequency distribution data. It defines a frequency distribution as a tabulation or grouping of data into categories showing the number of observations in each group. The document outlines the parts of a frequency table as class limits, class size, class boundaries, and class marks. It then provides steps for constructing a frequency distribution table from a set of data. Finally, it discusses histograms and frequency polygons as methods for graphically presenting frequency distribution data, and provides examples of how to construct these graphs in Excel.
This document provides information on presenting data through textual, tabular, and graphical methods. It discusses preparing stem-and-leaf plots and frequency distribution tables to organize and summarize data. Frequency distribution tables include elements like class intervals, frequencies, relative frequencies, and cumulative frequencies. The document also introduces contingency tables for enumerating data by cell across rows and columns. The overall purpose is to teach students the various ways of organizing and presenting numerical data through different visual and textual methods.
This document discusses frequency distributions and how to construct them from raw data. It provides examples of creating stem-and-leaf displays, frequency tables, relative frequency tables, and cumulative frequency tables from various data sets. Key concepts covered include class width, class boundaries, tallying data, and calculating relative frequencies and percentages. Overall, the document serves as a tutorial on how to organize and summarize data using various types of frequency distributions.
- A frequency distribution organizes data into classes and displays the frequency of observations in each class.
- Grouped data uses classes with cut-offs to group interval or ratio level data, while ungrouped data lists each observation individually for smaller data sets.
- To make a frequency distribution, the data's range is found and classes are determined. Each observation is tallied and frequencies per class are calculated. This displays the distribution of the data.
The document discusses statistical concepts used in analyzing assessment data. It defines statistics as the science of collecting, organizing, summarizing, and interpreting data. Descriptive statistics are used to describe data through measures of central tendency like the mean, median, and mode, while inferential statistics make predictions about a larger data set based on a sample. The document outlines steps for constructing frequency distributions and calculating the mean, including determining class limits and sizes. Graphs like histograms and frequency polygons can be used to visually represent grouped assessment data.
The document defines basic statistics and discusses frequency distribution and types of frequency distributions. It provides steps to construct discrete and continuous frequency distributions, including determining class limits and boundaries. Examples are given to demonstrate creating frequency tables from raw data for discrete and continuous variables. Key concepts discussed include tally marks, frequencies, class intervals, midpoints, and cumulative frequencies.
Chapter 2: Frequency Distribution and GraphsMong Mara
This document discusses different types of graphs and charts that can be used to represent frequency distributions of data, including histograms, frequency polygons, ogives, bar charts, pie charts, and stem-and-leaf plots. It provides examples of how to construct each graph or chart using sample data sets and discusses key aspects of each type such as class intervals, relative frequencies, and ordering of data. Guidelines are given for determining the optimal number of classes and class widths for grouped data. Exercises at the end provide practice applying these techniques to additional data sets.
This document discusses various methods for presenting data, including tabular form, arrays, simple tables, frequency distributions, and stem-and-leaf displays. It provides examples and tasks to practice each method. Specifically, it discusses how to construct frequency distributions and stem-and-leaf displays, including how to determine class limits, boundaries, widths, and marks. The goal is to organize and present data in a meaningful way that allows for easy interpretation and analysis.
This document provides an overview of quantitative data summarization techniques including frequency distributions, relative frequency distributions, and cumulative frequency distributions. It discusses organizing raw data into a data array and determining the number of classes, class intervals, and boundaries for constructing frequency distribution tables. Examples are provided to illustrate how to calculate frequencies, relative frequencies, and cumulative frequencies to summarize sets of quantitative data. The document also contains an exercise for students to collect sibling data and practice summarizing it using these techniques.
fraction pieces reporting in mathematicsBabyAnnMotar
This document discusses organizing data in frequency tables and types of statistical graphs. It defines frequency and frequency distribution tables, and lists the steps to construct a frequency distribution table using an example. These steps include choosing the number of classes, finding the range and class width, determining the lower and upper limits of each class, tallying the frequencies, and completing the table. The document also briefly describes how pie charts, fraction strips, and fraction towers can help students learn fractions in a hands-on way.
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.
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.
The document discusses frequency distribution tables, including how to construct them from raw data by grouping data into classes of equal intervals and determining the frequency of observations within each class. Key aspects covered include determining class limits, boundaries, frequencies, widths, and cumulative frequencies. Examples are provided to demonstrate how to build a frequency distribution table and corresponding graphical representations like histograms, frequency polygons, and ogives from sets of data.
This document defines and provides examples of frequency distributions and measures of central tendency. It discusses array, frequency distribution, class intervals, class boundaries, class marks, relative frequency distributions, and cumulative frequency distributions. It also covers calculating the mean, median, and mode of both ungrouped and grouped data. Formulas are provided for determining the mean, median, and mode of grouped data using class marks, frequencies, and boundaries.
The document contains an agenda for a math class which includes collecting projects, returning exams, and discussing remaining schedule and topics. It also lists exam dates. There are sections on introducing statistics, describing how to organize and display data through frequency tables, histograms, and polygons. Examples are provided to demonstrate calculating the mean, median, and mode of sample data sets to characterize the data.
Statistics is the study of data collection, organization, analysis, interpretation, and presentation. It involves planning data collection through surveys and experiments. The mean, median, and mode are common measures used to describe central tendencies in data. For grouped data, the mean can be calculated using direct, assumed mean, or step deviation methods assuming class frequencies are centered at class marks. Formulas are used to find the mode and median, which can also be found graphically using ogives to plot cumulative frequencies against class limits.
This lecture covers techniques for organizing and presenting data graphically, including:
- Constructing frequency distributions and histograms to organize numerical data into class intervals.
- Creating bar charts and pie charts to present categorical data by comparing frequencies or percentages.
- Examples are provided for constructing frequency distributions, histograms, bar charts, and pie charts using sample temperature and candy data sets.
- Techniques like cumulative frequency tables and ogives (cumulative percentage polygons) are also introduced.
The document discusses frequency distributions and their components. A frequency distribution arranges data into categories and shows the number of observations in each category. Key parts include:
- Class limits, which define the groupings by lower and upper limits.
- Class size, which is the width of each interval. It is calculated as the range divided by the number of classes.
- Class boundaries and marks, which separate and indicate the midpoints of categories.
The document provides steps for constructing a frequency distribution, including computing the range, determining class size, setting limits, tallying scores, and counting frequencies. An example uses exam scores to demonstrate these steps.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
More Related Content
Similar to G7- ORGANIZATION OF FREQUENCY TABLE.pptx
This document discusses frequency distributions and methods for graphically presenting frequency distribution data. It defines a frequency distribution as a tabulation or grouping of data into categories showing the number of observations in each group. The document outlines the parts of a frequency table as class limits, class size, class boundaries, and class marks. It then provides steps for constructing a frequency distribution table from a set of data. Finally, it discusses histograms and frequency polygons as methods for graphically presenting frequency distribution data, and provides examples of how to construct these graphs in Excel.
This document provides information on presenting data through textual, tabular, and graphical methods. It discusses preparing stem-and-leaf plots and frequency distribution tables to organize and summarize data. Frequency distribution tables include elements like class intervals, frequencies, relative frequencies, and cumulative frequencies. The document also introduces contingency tables for enumerating data by cell across rows and columns. The overall purpose is to teach students the various ways of organizing and presenting numerical data through different visual and textual methods.
This document discusses frequency distributions and how to construct them from raw data. It provides examples of creating stem-and-leaf displays, frequency tables, relative frequency tables, and cumulative frequency tables from various data sets. Key concepts covered include class width, class boundaries, tallying data, and calculating relative frequencies and percentages. Overall, the document serves as a tutorial on how to organize and summarize data using various types of frequency distributions.
- A frequency distribution organizes data into classes and displays the frequency of observations in each class.
- Grouped data uses classes with cut-offs to group interval or ratio level data, while ungrouped data lists each observation individually for smaller data sets.
- To make a frequency distribution, the data's range is found and classes are determined. Each observation is tallied and frequencies per class are calculated. This displays the distribution of the data.
The document discusses statistical concepts used in analyzing assessment data. It defines statistics as the science of collecting, organizing, summarizing, and interpreting data. Descriptive statistics are used to describe data through measures of central tendency like the mean, median, and mode, while inferential statistics make predictions about a larger data set based on a sample. The document outlines steps for constructing frequency distributions and calculating the mean, including determining class limits and sizes. Graphs like histograms and frequency polygons can be used to visually represent grouped assessment data.
The document defines basic statistics and discusses frequency distribution and types of frequency distributions. It provides steps to construct discrete and continuous frequency distributions, including determining class limits and boundaries. Examples are given to demonstrate creating frequency tables from raw data for discrete and continuous variables. Key concepts discussed include tally marks, frequencies, class intervals, midpoints, and cumulative frequencies.
Chapter 2: Frequency Distribution and GraphsMong Mara
This document discusses different types of graphs and charts that can be used to represent frequency distributions of data, including histograms, frequency polygons, ogives, bar charts, pie charts, and stem-and-leaf plots. It provides examples of how to construct each graph or chart using sample data sets and discusses key aspects of each type such as class intervals, relative frequencies, and ordering of data. Guidelines are given for determining the optimal number of classes and class widths for grouped data. Exercises at the end provide practice applying these techniques to additional data sets.
This document discusses various methods for presenting data, including tabular form, arrays, simple tables, frequency distributions, and stem-and-leaf displays. It provides examples and tasks to practice each method. Specifically, it discusses how to construct frequency distributions and stem-and-leaf displays, including how to determine class limits, boundaries, widths, and marks. The goal is to organize and present data in a meaningful way that allows for easy interpretation and analysis.
This document provides an overview of quantitative data summarization techniques including frequency distributions, relative frequency distributions, and cumulative frequency distributions. It discusses organizing raw data into a data array and determining the number of classes, class intervals, and boundaries for constructing frequency distribution tables. Examples are provided to illustrate how to calculate frequencies, relative frequencies, and cumulative frequencies to summarize sets of quantitative data. The document also contains an exercise for students to collect sibling data and practice summarizing it using these techniques.
fraction pieces reporting in mathematicsBabyAnnMotar
This document discusses organizing data in frequency tables and types of statistical graphs. It defines frequency and frequency distribution tables, and lists the steps to construct a frequency distribution table using an example. These steps include choosing the number of classes, finding the range and class width, determining the lower and upper limits of each class, tallying the frequencies, and completing the table. The document also briefly describes how pie charts, fraction strips, and fraction towers can help students learn fractions in a hands-on way.
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.
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.
The document discusses frequency distribution tables, including how to construct them from raw data by grouping data into classes of equal intervals and determining the frequency of observations within each class. Key aspects covered include determining class limits, boundaries, frequencies, widths, and cumulative frequencies. Examples are provided to demonstrate how to build a frequency distribution table and corresponding graphical representations like histograms, frequency polygons, and ogives from sets of data.
This document defines and provides examples of frequency distributions and measures of central tendency. It discusses array, frequency distribution, class intervals, class boundaries, class marks, relative frequency distributions, and cumulative frequency distributions. It also covers calculating the mean, median, and mode of both ungrouped and grouped data. Formulas are provided for determining the mean, median, and mode of grouped data using class marks, frequencies, and boundaries.
The document contains an agenda for a math class which includes collecting projects, returning exams, and discussing remaining schedule and topics. It also lists exam dates. There are sections on introducing statistics, describing how to organize and display data through frequency tables, histograms, and polygons. Examples are provided to demonstrate calculating the mean, median, and mode of sample data sets to characterize the data.
Statistics is the study of data collection, organization, analysis, interpretation, and presentation. It involves planning data collection through surveys and experiments. The mean, median, and mode are common measures used to describe central tendencies in data. For grouped data, the mean can be calculated using direct, assumed mean, or step deviation methods assuming class frequencies are centered at class marks. Formulas are used to find the mode and median, which can also be found graphically using ogives to plot cumulative frequencies against class limits.
This lecture covers techniques for organizing and presenting data graphically, including:
- Constructing frequency distributions and histograms to organize numerical data into class intervals.
- Creating bar charts and pie charts to present categorical data by comparing frequencies or percentages.
- Examples are provided for constructing frequency distributions, histograms, bar charts, and pie charts using sample temperature and candy data sets.
- Techniques like cumulative frequency tables and ogives (cumulative percentage polygons) are also introduced.
The document discusses frequency distributions and their components. A frequency distribution arranges data into categories and shows the number of observations in each category. Key parts include:
- Class limits, which define the groupings by lower and upper limits.
- Class size, which is the width of each interval. It is calculated as the range divided by the number of classes.
- Class boundaries and marks, which separate and indicate the midpoints of categories.
The document provides steps for constructing a frequency distribution, including computing the range, determining class size, setting limits, tallying scores, and counting frequencies. An example uses exam scores to demonstrate these steps.
Similar to G7- ORGANIZATION OF FREQUENCY TABLE.pptx (20)
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
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
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"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!"
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
5. a. Define frequency distribution table;
b. Organize the data collected using
frequency distribution table;
c.Construct a frequency distribution
table given a set of data.
9. Ungrouped data is data given as
individual data points.
Grouped data are framed by
amassing singular perceptions of a
variable into gatherings.
Data as Ungrouped or Grouped.
10. Sample Raw Data
GREEN RED RED VIOLET
PINK YELLOW PINK GREEN
BLUE BLACK PINK RED
VIOLET GREEN BLUE BLUE
GREEN PINK BLUE PINK
BLACK BLUE RED PINK
GREEN GREEN BLUE YELLOW
BLACK YELLOW
15. SOCIAL
MEDIA APPS
TALLY FREQUENCY
FACEBOOK IIII -II 7
INSTAGRAM IIII 5
PINTEREST I 1
SNAPCHAT IIII 4
TIKTOK IIII- IIII 9
TUMBLER II 2
TWITTER II 2
QUESTIONS:
a. How many students
participated in the survey?
b. What is the difference
between FB and TIKTOK
users?
c. Which is not commonly
used?
d. How many uses TIKTOK?
e. Which social media apps
is mostly used?
19. Step 1: Solve for RANGE
Subtract the lowest value from the highest
value.
Range = highest value – lowest value
20. Step 2: Set the desired number of classes
Decide on the number of class interval
desired. (usually 5 - 15).
Step 3: Solve for the class width or class size
i
Divide the range by the desired number of
class interval to determine the size of the class
interval.
21. Step 4: Make the first class interval.
Include the smallest value of the data. (Ex.
25-28)
Step 5. Identify the class limits (apparent limits)
Class limit is the highest and lowest values
describing a class. (Example: The class intervals
are 19 – 23, 24 – 28, 29 – 33...
22. Step 6. Determine the frequency of each class
interval by counting the mark tally
Class Interval Class
Boundaries
Tally Frequency Class
Mark
45-48
41-44
37-40
33-36
29-32
25-28
23. Step 6. Determine the frequency of each class
interval by counting the mark tally
24. Step 7. Distribute data in classes.
The column for tally is optional.
Class Interval Class
Boundaries
Tally Frequency Class
Mark
45-48 III 3
41-44 IIII-II 7
37-40 IIII-IIII 10
33-36 IIII-I 6
29-32 IIII-III 8
25-28 IIII-I 6
25. To find CLASS BOUNDARY, add 0.5 to the
upper class limit and subtract 0.5 to the
lower class limit.
The CLASS MARK is the midpoint of the
class. It can be found by getting the average
of the class limits.
For example, the class mark for 45-48
can be solved by
45+48
2
=
93
2
= 46.5
26.
27. On a ½ sheet of paper,
illustrate and solve the
following problems
accurately. Label your
28. Supposed these are the raw scores of 30 students
in a 20-item quiz and you are about to organize
and construct a frequency distribution table.
(desired number of classes = 5)
5 13 11 9 15
20 16 12 11 8
4 9 13 7 15
19 9 6 8 13
11 12 11 7 9
12 15 17 11 6
30. Supposed these are the 1ST Quarter
Mathematics Grades of 30 students in
XXX National High School. Organize
and construct a frequency
distribution table.