Course Content
Science
The Class 7 Science curriculum offers a comprehensive exploration of fundamental scientific concepts, fostering a deeper understanding of the natural world. Covering a diverse array of topics, students delve into the intricacies of plant and animal nutrition, unraveling the mysteries of photosynthesis and digestion. From the transformation of fibers into fabric to the principles governing heat transfer, students embark on a journey through the realms of physics and biology. They uncover the properties of acids, bases, and salts, gaining insight into chemical reactions and their practical applications. Moreover, the course sheds light on environmental phenomena, elucidating the mechanisms behind weather patterns, winds, storms, and cyclones, while also delving into the significance of soil and water resources. Through hands-on exploration and theoretical learning, students develop a holistic perspective on scientific principles, equipping them with the knowledge and skills to navigate the complexities of the natural world.
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Nutrition in Plants
Nutrition in Animals
Heat
Acids, Bases and Salts
Physical and Chemical Changes
Respiration in Organisms
Transportation in Animals and Plants
Reproduction in Plants
Motion and Time
Electric Current and its Effects
Light
Forests: Our Lifeline
Wastewater Story
Water: A Precious Resource
Maths
abc
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Integers
Fractions and Decimals
Data Handling
Simple Equations
Lines and Angles
The Triangle and its Properties
Comparing Quantities
Rational Numbers
Algebraic Expressions
Exponents and Powers
Symmetry
Visualising Solid Shapes
SST
Class 7 Social Studies (SST) covers a broad spectrum of topics encompassing history, geography, and civics, aimed at providing students with a comprehensive understanding of their world and its historical, social, and environmental context. In history, students explore significant events and developments from medieval India, including the rise and fall of empires, cultural transformations, and the influence of various dynasties. Geography lessons focus on understanding the Earth's structure, various landforms, water bodies, and the impact of human activities on the environment, fostering awareness about sustainability and conservation. Civics introduces students to the functioning of government, the importance of democracy, and the roles and responsibilities of citizens, promoting an understanding of their place and duties within the society. This curriculum is designed to build critical thinking, awareness, and a sense of responsibility among students.
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Environment
Inside Our Earth
Our Changing Earth
Air
Water
Human – Environment Interactions: The Tropical and the Subtropical Region
Life in the desserts
INTRODUCTION: TRACING CHANGES THROUGH A THOUSAND YEARS
KINGS AND KINGDOMS
The Delhi Sultans
THE MUGHALS (16th TO 17th CENTURY)
TRIBES, NOMADS AND SETTLED COMMUNITIES
DEVOTIONAL PATHS TO THE DIVINE
THE MAKING OF REGIONAL CULTURES
EIGHTEENTH-CENTURY POLITICAL FORMATIONS
English
Class 7 English curriculum encompasses a diverse range of language skills and literary exploration. Students engage in reading comprehension activities, analyzing prose, poetry, and short stories to grasp main ideas, characters, and literary devices. Grammar and vocabulary exercises strengthen their understanding of language structure and usage. Writing skills are honed through the practice of various formats like essays, letters, and narratives, focusing on coherent organization and persuasive expression. Literary exploration introduces students to different genres and elements such as character development, plot, and figurative language. Speaking and listening activities improve verbal communication, while supplementary readings broaden literary exposure. Engaging in language games and interactive exercises further reinforces learning, fostering effective communication and critical thinking for academic and real-life contexts.
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Three Questions
A Gift of Chappals
The Rebel
The Squirrel
Gopal and the Hilsa-fish
The Shed
The Ashes That Made Trees Bloom
Chivvy
Quality
Trees
Expert Detectives
Mystery of the Talking Fan
The Invention of Vita-Wonk
Dad and the Cat and the Tree
A Homage to our Brave Soldiers
Meadow Surprises
A Bicycle in Good Repair
Garden Snake
The Story of Cricket
The Tiny Teacher
Bringing Up Kari
The Desert
Golu Grows a Nose
Chandni
The Bear Story
A tiger in the house
An alien hand
The Cop and the Anthem
I want something in a Cage
Class 7 Foundation
About Lesson

3.1 REPRESENTATIVE VALUES

In this section, we explore the concept of representative values in statistics, focusing on average, specifically the arithmetic mean.

Average Concept: The average, often referred to as the mean, is a value that represents the central tendency of a set of observations or data. It’s commonly used to understand typical values within a dataset. Consider these examples:

  1. Study Hours: If someone says “Isha spends on average about 5 hours daily for her studies,” it implies that while Isha may not study exactly 5 hours every day, 5 hours is a typical amount she dedicates.

  2. Temperature: Stating “The average temperature at this time of the year is about 40 degrees Celsius” indicates that although the temperature might vary daily, 40 degrees Celsius is a typical value during that season.

  3. Age: “The average age of pupils in my class is 12 years” suggests that while individual ages may vary, 12 years represents the typical age within the class.

Arithmetic Mean: The arithmetic mean is the most common representative value used to find the average in a dataset. It’s calculated by adding up all the observations and dividing by the number of observations.

Examples:

  1. Study Hours: If Ashish studies for 4 hours, 5 hours, and 3 hours respectively on three consecutive days, his average study time is calculated by adding up the hours and dividing by the number of days.

  2. Runs Scored: For a batsman who scored 36, 35, 50, 46, 60, 55 runs in six innings, the mean runs scored per inning is found by adding all runs and dividing by the number of innings.

Understanding Mean:

  • Mean lies between the highest and lowest values of the data.
  • It’s not necessarily equal to any individual observation in the dataset.
  • For any two numbers, the mean lies between them.

Range: The difference between the highest and lowest observations in a dataset gives the range. It provides an understanding of the spread of the data.

Example: For the ages of 10 teachers (32, 41, 28, 54, 35, 26, 23, 33, 38, 40), the range is calculated as the difference between the highest and lowest ages.

3.2 ARITHMETIC MEAN

This section delves into the arithmetic mean, a fundamental measure of central tendency in statistics.

Definition and Concept: The arithmetic mean, often simply called the mean, is a representative value that reflects the average of a set of observations. It’s calculated by summing up all the observations and dividing by the total number of observations.

Example: Consider two vessels containing 20 liters and 60 liters of milk, respectively. To find the average amount of milk in each vessel if shared equally, we calculate the mean by dividing the total quantity of milk by the number of vessels.

Examples of Mean Calculation:

  1. Study Hours: If Ashish studies for 4 hours, 5 hours, and 3 hours respectively on three consecutive days, his average study time is found by dividing the total study hours by the number of days.

  2. Runs Scored: For a batsman scoring 36, 35, 50, 46, 60, and 55 runs in six innings, the mean runs scored per inning is calculated by adding all runs and dividing by the number of innings.

Understanding Mean:

  • The mean represents the central tendency of the data.
  • It’s not necessarily equal to any individual observation but falls between the highest and lowest values.
  • For any two numbers, the mean lies between them.

Range: The difference between the highest and lowest observations in a dataset provides the range, indicating the spread of the data.

Example: For the ages of 10 teachers (32, 41, 28, 54, 35, 26, 23, 33, 38, 40), the range is determined by subtracting the lowest age from the highest age.

3.3 MODE

This section introduces the concept of mode as another measure of central tendency, particularly useful when analyzing data with frequent repetitions of specific values.

Definition and Concept: The mode of a dataset refers to the observation that occurs most frequently. Unlike the mean, which represents the average, or the median, which represents the middle value, the mode highlights the most common value(s) in the dataset.

Example: Consider a set of numbers: 1, 1, 2, 4, 3, 2, 1, 2, 2, 4. Here, the mode is 2, as it occurs more frequently than any other value.

Mode of Large Data: In datasets with a large number of observations, manually identifying the mode can be cumbersome. Therefore, tabulating the data and counting the frequency of each observation simplifies the process.

Example: For margins of victory in football matches, organizing the data in a table and tallying the frequencies helps in determining the mode efficiently.

Understanding Mode:

  • The mode highlights the most common observation(s) in the dataset.
  • It is particularly useful when analyzing categorical data or data with discrete values.
  • Unlike the mean or median, the mode may not always be unique; a dataset can have multiple modes if multiple values occur with the same highest frequency.

3.4 MEDIAN

This section introduces the concept of the median as another measure of central tendency, particularly useful when analyzing data with extreme values or outliers.

Definition and Concept: The median of a dataset is the middle value when the data is arranged in ascending or descending order. Unlike the mean, which can be influenced by extreme values, the median provides a robust measure of central tendency that is less affected by outliers.

Example: Consider a set of numbers: 24, 36, 46, 17, 18, 25, 35. When arranged in ascending order, the median is 25, as it lies in the middle of the dataset.

Finding the Median: To find the median:

  1. Arrange the data in ascending or descending order.
  2. If the number of observations is odd, the median is the middle value.
  3. If the number of observations is even, the median is the average of the two middle values.

Understanding Median:

  • The median is robust to outliers and extreme values, making it suitable for datasets with skewed distributions.
  • It provides a clearer representation of central tendency when the dataset contains extreme values.
  • Unlike the mean, the median does not require every value to be considered, making it computationally simpler for large datasets.

3.5 USE OF BAR GRAPHS WITH A DIFFERENT PURPOSE

In this section, the focus shifts to utilizing bar graphs as a visual representation of data for analytical purposes beyond simple visualization.

Choosing a Scale:

  • A key aspect of creating effective bar graphs is choosing an appropriate scale that accurately represents the data while maintaining clarity and readability.
  • The scale determines the relationship between the length of the bars and the values they represent.
  • For example, if the data spans a wide range, a suitable scale ensures that the bars are not too compressed or elongated, maintaining visual balance.

Example 1: Favourite Colour Survey

  • Students were surveyed about their favourite colours to decide the school building’s colour.
  • The data is represented using a bar graph, with each bar corresponding to the frequency of a particular colour choice.
  • Choosing a suitable scale ensures that the graph effectively communicates the distribution of colour preferences among the students.

Example 2: Total Marks Obtained

  • Data representing the total marks obtained by students is visualized using a bar graph.
  • Again, selecting an appropriate scale ensures that each bar accurately reflects the marks achieved by each student.
  • The graph provides a clear comparison of individual performance within the dataset.

Understanding Bar Graphs:

  • Bar graphs serve not only as a visual aid but also as a tool for analyzing data patterns and making informed decisions.
  • They allow for quick comparisons between different categories or groups within a dataset.
  • Choosing the right scale is crucial for maintaining the integrity and accuracy of the visual representation.

Double Bar Graphs:

  • Double bar graphs are introduced, providing a way to compare two sets of related data side by side.
  • Each category or group is represented by two adjacent bars, allowing for direct comparison and analysis.
  • Double bar graphs are useful for visualizing trends, patterns, and differences between two datasets.
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