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The document describes how to calculate the median of a data set grouped into classes. The median is the middle value of the data set when sorted in numerical order. To find the median: 1) Calculate the cumulative frequency and identify the median class with a cumulative frequency greater than or equal to half the total frequency 2) Calculate the lower limit (LL) of the median using the median class boundaries and half the total frequency 3) Determine the class interval (i) and cumulative frequency (<cf>) below the median class to calculate the median

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Median of grouped data

This document provides steps for calculating the median of grouped data:
1. Create a frequency distribution table with class intervals, frequencies, and cumulative frequencies.
2. Find the median class by calculating N/2, where N is the total number of data points.
3. The median is calculated using the formula: x = L + (n2 - F2)/f2 * i, where L is the lower limit of the median class, n2 is the median class, F2 is the cumulative frequency before the median class, f2 is the frequency of the median class, and i is the class interval.

Statistics & probability lesson 8&9

This document discusses measures of central tendency, variation, and dispersion in statistical data. It explains that measures of central tendency alone are not enough to understand differences between data sets. Measures of variation such as range, variance, and standard deviation provide additional important information. The document uses an example of returns on stocks to illustrate this point, defining key terms like rate of return. It states that the variation or dispersion in historical returns can help predict future performance beyond just average returns.

..............Pascua_Renlie Jane_01.pptx

This document contains data and analysis on the level of aspiration and readiness of senior high school students in pursuing tertiary education. It includes distribution tables and charts showing respondents by gender, academic strand, age, and family income. Measures of central tendency and variation are calculated on the data sets, including range, midrange, mean, median, mode, variance and standard deviation. Results are summarized on the levels of aspiration and readiness based on the analysis.

Mean of grouped data

This document provides steps for calculating the mean of grouped data:
1. Make a frequency distribution table with class intervals, frequencies, and midpoints.
2. Multiply the midpoint and frequency for each class to calculate the fx value.
3. Use the formula x=fx/n, where f is the frequency, x is the midpoint, and n is the total frequency, to calculate the mean.
For example, given data grouped into classes with frequencies totaling 30, the mean was calculated to be 73.97.

Mean for Grouped Data

This document discusses measures of central tendency, specifically how to calculate the mean of grouped data. It provides the formula for calculating the mean of grouped data and walks through an example of finding the mean test scores of students. The document demonstrates how to find the midpoint of each score group, multiply by the frequency, sum the results, and divide by the total frequency to determine the mean.

STATISTICS

This document discusses various statistical concepts including:
1. Collection, organization, and presentation of data through methods like observation, interviews, questionnaires, etc. and organizing data through tables, histograms, and frequency polygons.
2. Measures of central tendency including mode, median, and mean. Mode is the most frequent value, median is the middle value, and mean is the average. These can be calculated for grouped or ungrouped data.
3. Quartiles and percentiles which divide a distribution into four equal parts, with the lower quartile being the 25th percentile, median the 50th, and upper quartile the 75th. Quartiles for grouped data use the lower boundary and frequency of the relevant class

Group 3 measures of central tendency and variation - (mean, median, mode, ra...

This document discusses various measures of central tendency and variation. It defines central tendency as indicating where the center of a distribution tends to be, and mentions that measures of central tendency answer whether scores are generally high or low. It then discusses specific measures of central tendency - the mean, median, and mode - and how to calculate each one for both ungrouped and grouped data. It also discusses other measures of variation like range and standard deviation, and how to compute standard deviation for ungrouped and grouped data.

Frequency Distribution (Class-interval- Tally).pptx

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.

Median of grouped data

This document provides steps for calculating the median of grouped data:
1. Create a frequency distribution table with class intervals, frequencies, and cumulative frequencies.
2. Find the median class by calculating N/2, where N is the total number of data points.
3. The median is calculated using the formula: x = L + (n2 - F2)/f2 * i, where L is the lower limit of the median class, n2 is the median class, F2 is the cumulative frequency before the median class, f2 is the frequency of the median class, and i is the class interval.

Statistics & probability lesson 8&9

This document discusses measures of central tendency, variation, and dispersion in statistical data. It explains that measures of central tendency alone are not enough to understand differences between data sets. Measures of variation such as range, variance, and standard deviation provide additional important information. The document uses an example of returns on stocks to illustrate this point, defining key terms like rate of return. It states that the variation or dispersion in historical returns can help predict future performance beyond just average returns.

..............Pascua_Renlie Jane_01.pptx

This document contains data and analysis on the level of aspiration and readiness of senior high school students in pursuing tertiary education. It includes distribution tables and charts showing respondents by gender, academic strand, age, and family income. Measures of central tendency and variation are calculated on the data sets, including range, midrange, mean, median, mode, variance and standard deviation. Results are summarized on the levels of aspiration and readiness based on the analysis.

Mean of grouped data

This document provides steps for calculating the mean of grouped data:
1. Make a frequency distribution table with class intervals, frequencies, and midpoints.
2. Multiply the midpoint and frequency for each class to calculate the fx value.
3. Use the formula x=fx/n, where f is the frequency, x is the midpoint, and n is the total frequency, to calculate the mean.
For example, given data grouped into classes with frequencies totaling 30, the mean was calculated to be 73.97.

Mean for Grouped Data

This document discusses measures of central tendency, specifically how to calculate the mean of grouped data. It provides the formula for calculating the mean of grouped data and walks through an example of finding the mean test scores of students. The document demonstrates how to find the midpoint of each score group, multiply by the frequency, sum the results, and divide by the total frequency to determine the mean.

STATISTICS

This document discusses various statistical concepts including:
1. Collection, organization, and presentation of data through methods like observation, interviews, questionnaires, etc. and organizing data through tables, histograms, and frequency polygons.
2. Measures of central tendency including mode, median, and mean. Mode is the most frequent value, median is the middle value, and mean is the average. These can be calculated for grouped or ungrouped data.
3. Quartiles and percentiles which divide a distribution into four equal parts, with the lower quartile being the 25th percentile, median the 50th, and upper quartile the 75th. Quartiles for grouped data use the lower boundary and frequency of the relevant class

Group 3 measures of central tendency and variation - (mean, median, mode, ra...

This document discusses various measures of central tendency and variation. It defines central tendency as indicating where the center of a distribution tends to be, and mentions that measures of central tendency answer whether scores are generally high or low. It then discusses specific measures of central tendency - the mean, median, and mode - and how to calculate each one for both ungrouped and grouped data. It also discusses other measures of variation like range and standard deviation, and how to compute standard deviation for ungrouped and grouped data.

Frequency Distribution (Class-interval- Tally).pptx

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.

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1. The administrative/top-down model where curriculum is developed by administrators and experts from goals and objectives.
2. The grass roots/bottom-up model where teachers and schools lead curriculum development from their experiences.
3. The Tyler model from the 1940s which is a scientific approach with four steps: determining objectives, identifying learning experiences, organizing experiences, and evaluating objectives.
4. The Taba model advocates teacher involvement and an inductive approach starting with specifics and building to a general design.
5. The Oliva model is a deductive model offering a process for complete curriculum development focusing on curricular and instructional components.

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The document discusses various physical disabilities and orthopedic impairments including:
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- Orthopedic impairments relating to bones, joints or muscles that affect educational performance, with causes including genetic abnormalities or disorders like cerebral palsy.
- Specific conditions mentioned include attention deficit hyperactive disorder, deaf-blindness, deafness, hearing impairment, traumatic brain injury, and visual impairment.

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This document discusses calculating the mean, or average, of grouped and ungrouped data sets. It defines the mean as a measure of central tendency and shows how to compute the mean for grouped data by multiplying the frequency by the midpoint, summing these products, and dividing by the total number of data points. An example is provided to demonstrate calculating the mean of 60 students' assessment scores grouped into intervals. The document also states how to compute the mean of ungrouped data and thanks the reader for listening.

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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.

Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) Curriculum

(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
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𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
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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.

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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

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Parental authority refers to the natural right and duty of parents over their unemancipated children under Philippine law. The father and mother jointly exercise parental authority and are responsible for the child's well-being. In cases of disagreement, the father's decision prevails unless a court orders otherwise. Parental authority is suspended if a parent commits a crime involving civil interdiction, and can be terminated if the parent subjects the child to abuse or allows sexual abuse. Grandparents, siblings, and institutions like orphanages can also exercise substitute parental authority in the absence of parents. The document outlines the rights and responsibilities of those exercising parental authority over a child's person and property.

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2. The grass roots/bottom-up model where teachers and schools lead curriculum development from their experiences.
3. The Tyler model from the 1940s which is a scientific approach with four steps: determining objectives, identifying learning experiences, organizing experiences, and evaluating objectives.
4. The Taba model advocates teacher involvement and an inductive approach starting with specifics and building to a general design.
5. The Oliva model is a deductive model offering a process for complete curriculum development focusing on curricular and instructional components.

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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.

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(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.

ZK on Polkadot zero knowledge proofs - sub0.pptx

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Your Skill Boost Masterclass: Strategies for Effective Upskilling

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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.

writing about opinions about Australia the movie

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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

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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.

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- 1. Median (Measure Of Central Tendency) Reporter: Czarina D. Altea
- 2. Where : LL = lower limit of assumed median determine by the expression N/2 n = total number of observations/frequency i = class interval <cf = less than cumulative frequency fm = frequency of median class /alteaczarina Formula: Median
- 3. Class Frequency (f) 66-68 1 69-71 3 72-74 4 75-77 8 78-80 11 81-83 9 84-86 5 87-89 5 90-92 1 93-95 2 n= 49 /alteaczarina Median of Group Data Cumulative frequency (cf)
- 4. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 75-77 8 78-80 11 81-83 9 84-86 5 87-89 5 90-92 1 93-95 2 n=49 /alteaczarina Median of Group Data
- 5. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75-77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data
- 6. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75-77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data Median class: The class with the cumulative frequency greater than or equal to one-half of the total frequency n 2
- 7. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75-77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data n 2
- 8. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75-77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data Median class = 78-80 n/2 = 49/2 = 24.5
- 9. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75- 77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data Median class = 78-80 n/2 = 24.5 LL = 77 + 78 / 2 = 155/2 = 77.5 LL =78 - 0.5 = 77.5 or
- 10. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75- 77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data Median class = 78-80 n/2 = 24.5 LL = 77.5 i = 68-66=2+1= 3
- 11. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75-77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data Median class = 78-80 n/2 = 24.5 LL = 77.5 i = 3 <cf = ? fm
- 12. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75-77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data fm cf <cf
- 13. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75-77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data Median class = 78-80 n/2 = 24.5 LL = 77.5 i = 3 <cf = 16 fm =11
- 14. Median of Group Data Median class = 78-80 n/2 = 24.5 LL = 77.5 i = 3 <cf = 16 fm =11 /alteaczarina
- 15. Median of Group Data /alteaczarina
- 16. Median of Group Data /alteaczarina
- 17. Median of Group Data /alteaczarina
- 18. Class Frequency (f) Cumulative frequency(cf) 66-68 1 1 69-71 3 4 72-74 4 8 75-77 8 16 78-80 11 27 81-83 9 36 84-86 5 41 87-89 5 46 90-92 1 47 93-95 2 49 n=49 /alteaczarina Median of Group Data Median class = 78-80 n/2 = 24.5 LL = 77.5 i = 3 <cf = 16 fm =11 Median = 79.82
- 20. Class Frequency (f) cf 12-18 5 5 19-25 6 11 26-32 5 16 33-39 8 24 40-46 5 29 47-53 1 30 n= 30 /alteaczarina Median of Group Data Median class = 26-32 n/2 = 15 LL = 25.5 i = 7 <cf = 11 fm = 5 Median =
- 21. = 25.5 + 7 Median class = 26-32 n/2 = 15 LL = 25.5 i = 7 <cf = 11 fm = 5
- 22. Class Frequency (f) cf 19-21 13 22-24 12 25-27 15 28-30 7 31-33 3 N = /alteaczarina Median of Group Data Median class = n/2 = LL = i = <cf = fm = Median =
- 23. Class Frequency (f) cf 73-75 2 76-78 6 79-81 12 82-84 16 85-87 18 88-90 39 91-93 31 94-96 21 97-99 5 n= /alteaczarina Median of Group Data Median class = n/2 = LL = i = <cf = fm = Median =