This document outlines a lesson on describing data that involves students collecting and summarizing their own data. The lesson begins with students privately providing their height, weight, and other information to create an anonymous data set. Students then discuss statistical versus non-statistical questions and practice identifying the types of questions. They collect small amounts of additional data in groups to explore variation. Finally, students imagine summarizing larger data sets using graphs, charts, and summary statistics. The goal is for students to understand that data varies and can be organized to answer statistical questions.
This document outlines a lesson on collecting and analyzing data on student fruit preferences. Students will rank their preferences for 4 fruits from most to least preferred. Their rankings will be compiled and different methods will be used to analyze the data, including determining the class favorite fruit based on the mode, median, sums of rankings, and bar graphs. The goal is for students to understand that there are various ways to summarize data and determine patterns or favorites.
This document outlines a lesson on measuring central tendency. The lesson is one hour and involves reviewing measures of central tendency like mean, median, and mode. Students will work through three case studies calculating these measures and discussing their strengths and limitations. Assessments will evaluate students' ability to calculate the measures and understand how they are affected by changes in data. The lesson aims to help students calculate common measures of central tendency, interpret them, and discuss their limitations.
Statistics involves collecting, organizing, presenting, analyzing, and interpreting data to make decisions. Descriptive statistics describes characteristics and properties of a group through gathering, organizing, presenting, and describing data. Inferential statistics draws inferences about a large group based on a sample through inductive reasoning and hypothesis testing. The examples provided illustrate common uses of descriptive and inferential statistics.
This document provides an overview of a lesson on data sources, variables, and measurement scales. The lesson will cover primary and secondary data sources, qualitative and quantitative variables, and nominal, ordinal, interval, and ratio measurement scales. Students will learn to identify data sources, define different variable types, and recognize the appropriate scale of measurement for a given variable. The lesson aims to help students understand how data is collected and analyzed depending on its characteristics.
This document provides an overview of key concepts in probability and statistics. It discusses descriptive versus inferential statistics, different types of variables and data, levels of measurement, sampling techniques, methods of data collection and presentation. Variables are classified as qualitative or quantitative, and quantitative variables are further divided into discrete or continuous. Data can be measured at the nominal, ordinal, interval or ratio level. Common sampling methods include simple random sampling, systematic sampling, stratified sampling and cluster sampling. Data collection is usually done through interviews, questionnaires, registration or observation. Data is often presented textually, in tables or through graphs.
The document discusses the importance and key concepts of statistics. It introduces three main reasons to study statistics: to be an informed consumer of information, to understand and make decisions, and to evaluate decisions that affect one's life. It then defines important statistical terms like population, sample, variable, and data types. It also provides examples of different data sets and ways to organize data, such as through frequency distributions, bar charts, and dot plots.
This document discusses different levels of measurement in statistics:
- Nominal level deals with categorical variables without ordering. Examples include gender and team jersey numbers.
- Ordinal level also deals with categorical variables but includes ordering. Examples include socioeconomic status and exam difficulty.
- Interval level includes order and distance between units but no absolute zero. Examples include Celsius temperature and IQ scores.
- Ratio level includes all properties of interval plus a true absolute zero point. Examples include mass, height, and electric charge.
This document outlines a lesson on collecting and analyzing data on student fruit preferences. Students will rank their preferences for 4 fruits from most to least preferred. Their rankings will be compiled and different methods will be used to analyze the data, including determining the class favorite fruit based on the mode, median, sums of rankings, and bar graphs. The goal is for students to understand that there are various ways to summarize data and determine patterns or favorites.
This document outlines a lesson on measuring central tendency. The lesson is one hour and involves reviewing measures of central tendency like mean, median, and mode. Students will work through three case studies calculating these measures and discussing their strengths and limitations. Assessments will evaluate students' ability to calculate the measures and understand how they are affected by changes in data. The lesson aims to help students calculate common measures of central tendency, interpret them, and discuss their limitations.
Statistics involves collecting, organizing, presenting, analyzing, and interpreting data to make decisions. Descriptive statistics describes characteristics and properties of a group through gathering, organizing, presenting, and describing data. Inferential statistics draws inferences about a large group based on a sample through inductive reasoning and hypothesis testing. The examples provided illustrate common uses of descriptive and inferential statistics.
This document provides an overview of a lesson on data sources, variables, and measurement scales. The lesson will cover primary and secondary data sources, qualitative and quantitative variables, and nominal, ordinal, interval, and ratio measurement scales. Students will learn to identify data sources, define different variable types, and recognize the appropriate scale of measurement for a given variable. The lesson aims to help students understand how data is collected and analyzed depending on its characteristics.
This document provides an overview of key concepts in probability and statistics. It discusses descriptive versus inferential statistics, different types of variables and data, levels of measurement, sampling techniques, methods of data collection and presentation. Variables are classified as qualitative or quantitative, and quantitative variables are further divided into discrete or continuous. Data can be measured at the nominal, ordinal, interval or ratio level. Common sampling methods include simple random sampling, systematic sampling, stratified sampling and cluster sampling. Data collection is usually done through interviews, questionnaires, registration or observation. Data is often presented textually, in tables or through graphs.
The document discusses the importance and key concepts of statistics. It introduces three main reasons to study statistics: to be an informed consumer of information, to understand and make decisions, and to evaluate decisions that affect one's life. It then defines important statistical terms like population, sample, variable, and data types. It also provides examples of different data sets and ways to organize data, such as through frequency distributions, bar charts, and dot plots.
This document discusses different levels of measurement in statistics:
- Nominal level deals with categorical variables without ordering. Examples include gender and team jersey numbers.
- Ordinal level also deals with categorical variables but includes ordering. Examples include socioeconomic status and exam difficulty.
- Interval level includes order and distance between units but no absolute zero. Examples include Celsius temperature and IQ scores.
- Ratio level includes all properties of interval plus a true absolute zero point. Examples include mass, height, and electric charge.
This module introduces key concepts in statistics. It will cover defining statistics and related terms, the history and importance of statistics, summation rules, sampling techniques, organizing data in tables, constructing frequency distributions, and measures of central tendency for ungrouped data. The goal is for students to understand how statistics is used in daily life and to learn techniques for collecting, organizing, and analyzing data.
The document provides instructions for organizing and presenting statistical data using frequency tables and histograms. It discusses how to construct a frequency table by grouping raw data into intervals and tallying the frequencies. It then explains how to create a histogram by using the frequency table to draw rectangles whose widths represent intervals and heights represent frequencies. The lesson emphasizes that frequency tables and histograms are useful tools for organizing large data sets and communicating patterns in the data visually.
The document discusses levels of measurement in data collection and summarizing findings. It identifies nominal, ordinal, interval and ratio as the four levels of measurement and provides examples. Nominal involves categorical variables without ordering, ordinal has ordering but no distances, interval has ordering and distances but no true zero point, and ratio has all properties including a true zero. The document also discusses objective and subjective primary data collection and using secondary data from existing records. It aims to identify measurement levels, collect and analyze data to evaluate the validity of the statement about breakfast and quiz performance.
Homework 1
Introduction to Statistics
Be sure you have reviewed this module/week’s lesson and presentations before proceeding to the homework exercises. Number all responses. Review the “Homework Instructions: General” document for an example of how homework assignments must look.
Homework 1 does not include any SPSS output and consists only of Part I.
A confidence interval provides a range of values that is likely to include an unknown population parameter, based on a given confidence level. A 95% confidence level means there is a 95% chance the interval contains the true population parameter. Confidence intervals are useful because they allow researchers to account for sampling error/variability and make inferences about populations based on sample data. The higher the confidence level, the wider the interval needs to be to achieve that level of confidence.
As continuation of Lesson 2 (where we contextualize data) in this lesson we define basic terms in statistics as we continue to explore data. These basic terms include the universe, variable, population and sample. In detail we will discuss other concepts in relation to a variable.
This document describes a lesson on measures of variation. The lesson introduces concepts like standard deviation and variance as measures of risk. Students will analyze stock return data for two stocks (A and B) and calculate summary statistics. They will discover that investing half in each stock reduces risk compared to investing fully in one stock, as the standard deviation is lower for a mixed portfolio. The lesson aims to show students that variation measures provide important information beyond just averages.
This document discusses descriptive statistics and its uses. Descriptive statistics involves collecting, organizing, and interpreting data in a way that is understandable. It aims to summarize important features of a data set without generalizing beyond that group. Some key uses of descriptive statistics mentioned include education, government, medicine, psychology, sociology, and sports. The document also covers topics like variables, frequency distributions, measures of central tendency including mean, median and mode.
This document provides an outline for a course on probability and statistics. It begins with an introduction to key concepts like measures of central tendency, dispersion, correlation, and probability distributions. It then lists common probability distributions and hypothesis testing. The document provides examples of how statistics is used in various fields. It also defines key statistical concepts like population and sample, variables, and different scales of measurement. Finally, it discusses data collection methods and ways to represent data through tables and graphs.
This document provides an outline for a course on probability and statistics. It begins with an introduction to statistics, including definitions and general uses. It then covers topics like measures of central tendency, probability, discrete and continuous distributions, and hypothesis testing. References for textbooks on the subject are also provided. Assignments include calculating measures of central tendency and constructing frequency distributions from raw data. Various scales of measurement and methods of data collection are defined. Graphical representations like histograms, pie charts, and bar graphs are discussed. Formulas are given for calculating the mean, median, and mode of both grouped and ungrouped data.
This document provides information about an introductory statistics course titled Math 1127 taught by Dr. Carlos Almada. It outlines the course format, expectations for students, and an overview of topics to be covered including descriptive statistics, inferential statistics, variables and data types, sampling methods, and the statistical process. A sample data set on employees is also presented to demonstrate variables and data.
The document provides an overview of basic statistical concepts including:
1. It discusses the root words of statistics and who conducted the first census.
2. It explains that statistics has applications in many subjects like business, economics, and commerce.
3. It outlines the main sources of data as primary and secondary, and where each can be obtained.
Statistics is the science of collectionWaleed Liaqat
Statistics involves the collection, analysis, and presentation of numerical data to aid decision-making. It deals with large groups of values and aspects that can be described quantitatively. Descriptive statistics summarizes and describes data through methods like condensing data, graphical displays, and computing measures of center and spread. Inferential statistics makes inferences about populations from samples using techniques like parameter estimation and hypothesis testing, based on probability theory. It distinguishes between populations, parameters, samples, quantitative and qualitative variables, and scales of measurement.
Probability and statistics (basic statistical concepts)Don Bosco BSIT
The document discusses key concepts in probability and statistics. It defines statistical and descriptive methods, and explains that descriptive methods are used to collect and analyze data from a sample, while inferential methods make predictions or decisions with uncertainty. Basic statistical concepts are also introduced, such as populations, samples, parameters, statistics, variables, and measurement scales. Descriptive statistics are used to summarize or describe characteristics of data, while inferential statistics are used to make predictions beyond the immediate data. Examples are provided to illustrate these fundamental probability and statistics terms and concepts.
The document is a teaching guide for introducing statistics to senior high school students. It begins with an introduction explaining how statistics is used in decision making. The lesson overview states that by the end, students should be able to identify statistical questions and describe the statistical process. Sample statistical questions are then provided and categorized as either having a definite answer or requiring data. The key aspects of a statistical process are outlined as planning data collection, verifying data quality, summarizing data, and using summaries to support decisions. An example of using the process to answer "Do dogs eat more than cats?" is described. Key points are recapped and an assessment with sample answers is provided to check student understanding.
This document provides information on presenting and analyzing business data. It defines key terms like data, statistics, frequency, and frequency distribution. It explains how to construct a frequency distribution table from a raw data set by tallying the frequency of each value. It also describes how to create a grouped frequency distribution when data covers a wide range, including how to determine the class size and number of classes. Finally, it discusses visualizing frequency distributions through histograms and polygons in Excel.
This document provides notes for online students about quantitative data analysis and SPSS. It discusses that the lecture series will cover basic ideas in quantitative data analysis. It notes that many different statistical software programs are available but that the course will use SPSS because it is easy to use and popular for statistical analysis.
This document provides an overview of statistics and probability as taught in a lecture. It begins by defining statistics as the science of drawing conclusions about phenomena from sample data. Some key points:
- Statistics has many applications across various disciplines.
- The course will cover descriptive statistics, probability, and inferential statistics over 15 lectures.
- Students will complete homework assignments and take midterm and final exams to be graded on their understanding.
- The goal is for students to learn statistical techniques to make data-driven decisions in their fields of study.
This document provides an overview of key concepts in data collection and statistics. It defines important terms like universe, variable, qualitative and quantitative variables. It also distinguishes between discrete and continuous quantitative data. Specifically:
- Universe refers to the entire set of units from which data is collected. A variable is any characteristic that can be measured for each unit.
- Qualitative variables express categories while quantitative variables answer questions of amount and can be measured.
- Discrete data can be counted, while continuous data can be measured to any degree of precision.
- Proper data collection requires protecting confidentiality, clarifying questions, and compiling all responses from a target group.
This document provides an introduction to statistics lesson 1. It defines statistics as a branch of mathematics that deals with collecting, organizing, presenting, analyzing, and interpreting data. It discusses the origins of the word "statistics" and provides examples of its importance in areas like weather forecasting, predicting disease, and political campaigns. The document also covers topics like the difference between population and sample, parameters and statistics, and types of statistical questions.
Real-Life Problems that can be Solved by Statistics.pptxJuvierafanan
Here are 3 examples of problems identified, statistical questions formed, and simple statistical instruments formulated:
1. Problem identified: Students struggling with online classes.
Statistical question: What challenges are students facing with online learning?
Statistical instrument: Open-ended survey questions to students.
2. Problem identified: Traffic congestion on main roads during rush hour.
Statistical question: What times of day experience the worst traffic?
Statistical instrument: Observation of traffic patterns at different times.
3. Problem identified: Lack of fresh food options in local stores.
Statistical question: What fresh foods do community members most want available?
Statistical instrument: Interview questions for community members.
This module introduces key concepts in statistics. It will cover defining statistics and related terms, the history and importance of statistics, summation rules, sampling techniques, organizing data in tables, constructing frequency distributions, and measures of central tendency for ungrouped data. The goal is for students to understand how statistics is used in daily life and to learn techniques for collecting, organizing, and analyzing data.
The document provides instructions for organizing and presenting statistical data using frequency tables and histograms. It discusses how to construct a frequency table by grouping raw data into intervals and tallying the frequencies. It then explains how to create a histogram by using the frequency table to draw rectangles whose widths represent intervals and heights represent frequencies. The lesson emphasizes that frequency tables and histograms are useful tools for organizing large data sets and communicating patterns in the data visually.
The document discusses levels of measurement in data collection and summarizing findings. It identifies nominal, ordinal, interval and ratio as the four levels of measurement and provides examples. Nominal involves categorical variables without ordering, ordinal has ordering but no distances, interval has ordering and distances but no true zero point, and ratio has all properties including a true zero. The document also discusses objective and subjective primary data collection and using secondary data from existing records. It aims to identify measurement levels, collect and analyze data to evaluate the validity of the statement about breakfast and quiz performance.
Homework 1
Introduction to Statistics
Be sure you have reviewed this module/week’s lesson and presentations before proceeding to the homework exercises. Number all responses. Review the “Homework Instructions: General” document for an example of how homework assignments must look.
Homework 1 does not include any SPSS output and consists only of Part I.
A confidence interval provides a range of values that is likely to include an unknown population parameter, based on a given confidence level. A 95% confidence level means there is a 95% chance the interval contains the true population parameter. Confidence intervals are useful because they allow researchers to account for sampling error/variability and make inferences about populations based on sample data. The higher the confidence level, the wider the interval needs to be to achieve that level of confidence.
As continuation of Lesson 2 (where we contextualize data) in this lesson we define basic terms in statistics as we continue to explore data. These basic terms include the universe, variable, population and sample. In detail we will discuss other concepts in relation to a variable.
This document describes a lesson on measures of variation. The lesson introduces concepts like standard deviation and variance as measures of risk. Students will analyze stock return data for two stocks (A and B) and calculate summary statistics. They will discover that investing half in each stock reduces risk compared to investing fully in one stock, as the standard deviation is lower for a mixed portfolio. The lesson aims to show students that variation measures provide important information beyond just averages.
This document discusses descriptive statistics and its uses. Descriptive statistics involves collecting, organizing, and interpreting data in a way that is understandable. It aims to summarize important features of a data set without generalizing beyond that group. Some key uses of descriptive statistics mentioned include education, government, medicine, psychology, sociology, and sports. The document also covers topics like variables, frequency distributions, measures of central tendency including mean, median and mode.
This document provides an outline for a course on probability and statistics. It begins with an introduction to key concepts like measures of central tendency, dispersion, correlation, and probability distributions. It then lists common probability distributions and hypothesis testing. The document provides examples of how statistics is used in various fields. It also defines key statistical concepts like population and sample, variables, and different scales of measurement. Finally, it discusses data collection methods and ways to represent data through tables and graphs.
This document provides an outline for a course on probability and statistics. It begins with an introduction to statistics, including definitions and general uses. It then covers topics like measures of central tendency, probability, discrete and continuous distributions, and hypothesis testing. References for textbooks on the subject are also provided. Assignments include calculating measures of central tendency and constructing frequency distributions from raw data. Various scales of measurement and methods of data collection are defined. Graphical representations like histograms, pie charts, and bar graphs are discussed. Formulas are given for calculating the mean, median, and mode of both grouped and ungrouped data.
This document provides information about an introductory statistics course titled Math 1127 taught by Dr. Carlos Almada. It outlines the course format, expectations for students, and an overview of topics to be covered including descriptive statistics, inferential statistics, variables and data types, sampling methods, and the statistical process. A sample data set on employees is also presented to demonstrate variables and data.
The document provides an overview of basic statistical concepts including:
1. It discusses the root words of statistics and who conducted the first census.
2. It explains that statistics has applications in many subjects like business, economics, and commerce.
3. It outlines the main sources of data as primary and secondary, and where each can be obtained.
Statistics is the science of collectionWaleed Liaqat
Statistics involves the collection, analysis, and presentation of numerical data to aid decision-making. It deals with large groups of values and aspects that can be described quantitatively. Descriptive statistics summarizes and describes data through methods like condensing data, graphical displays, and computing measures of center and spread. Inferential statistics makes inferences about populations from samples using techniques like parameter estimation and hypothesis testing, based on probability theory. It distinguishes between populations, parameters, samples, quantitative and qualitative variables, and scales of measurement.
Probability and statistics (basic statistical concepts)Don Bosco BSIT
The document discusses key concepts in probability and statistics. It defines statistical and descriptive methods, and explains that descriptive methods are used to collect and analyze data from a sample, while inferential methods make predictions or decisions with uncertainty. Basic statistical concepts are also introduced, such as populations, samples, parameters, statistics, variables, and measurement scales. Descriptive statistics are used to summarize or describe characteristics of data, while inferential statistics are used to make predictions beyond the immediate data. Examples are provided to illustrate these fundamental probability and statistics terms and concepts.
The document is a teaching guide for introducing statistics to senior high school students. It begins with an introduction explaining how statistics is used in decision making. The lesson overview states that by the end, students should be able to identify statistical questions and describe the statistical process. Sample statistical questions are then provided and categorized as either having a definite answer or requiring data. The key aspects of a statistical process are outlined as planning data collection, verifying data quality, summarizing data, and using summaries to support decisions. An example of using the process to answer "Do dogs eat more than cats?" is described. Key points are recapped and an assessment with sample answers is provided to check student understanding.
This document provides information on presenting and analyzing business data. It defines key terms like data, statistics, frequency, and frequency distribution. It explains how to construct a frequency distribution table from a raw data set by tallying the frequency of each value. It also describes how to create a grouped frequency distribution when data covers a wide range, including how to determine the class size and number of classes. Finally, it discusses visualizing frequency distributions through histograms and polygons in Excel.
This document provides notes for online students about quantitative data analysis and SPSS. It discusses that the lecture series will cover basic ideas in quantitative data analysis. It notes that many different statistical software programs are available but that the course will use SPSS because it is easy to use and popular for statistical analysis.
This document provides an overview of statistics and probability as taught in a lecture. It begins by defining statistics as the science of drawing conclusions about phenomena from sample data. Some key points:
- Statistics has many applications across various disciplines.
- The course will cover descriptive statistics, probability, and inferential statistics over 15 lectures.
- Students will complete homework assignments and take midterm and final exams to be graded on their understanding.
- The goal is for students to learn statistical techniques to make data-driven decisions in their fields of study.
This document provides an overview of key concepts in data collection and statistics. It defines important terms like universe, variable, qualitative and quantitative variables. It also distinguishes between discrete and continuous quantitative data. Specifically:
- Universe refers to the entire set of units from which data is collected. A variable is any characteristic that can be measured for each unit.
- Qualitative variables express categories while quantitative variables answer questions of amount and can be measured.
- Discrete data can be counted, while continuous data can be measured to any degree of precision.
- Proper data collection requires protecting confidentiality, clarifying questions, and compiling all responses from a target group.
This document provides an introduction to statistics lesson 1. It defines statistics as a branch of mathematics that deals with collecting, organizing, presenting, analyzing, and interpreting data. It discusses the origins of the word "statistics" and provides examples of its importance in areas like weather forecasting, predicting disease, and political campaigns. The document also covers topics like the difference between population and sample, parameters and statistics, and types of statistical questions.
Real-Life Problems that can be Solved by Statistics.pptxJuvierafanan
Here are 3 examples of problems identified, statistical questions formed, and simple statistical instruments formulated:
1. Problem identified: Students struggling with online classes.
Statistical question: What challenges are students facing with online learning?
Statistical instrument: Open-ended survey questions to students.
2. Problem identified: Traffic congestion on main roads during rush hour.
Statistical question: What times of day experience the worst traffic?
Statistical instrument: Observation of traffic patterns at different times.
3. Problem identified: Lack of fresh food options in local stores.
Statistical question: What fresh foods do community members most want available?
Statistical instrument: Interview questions for community members.
1) Statistics is the study of collecting, organizing, analyzing, and drawing conclusions from data. It involves sampling, hypothesis testing, and using statistical tests tailored to measurement scales and hypothesis types.
2) Descriptive statistics describe and summarize data quantitatively, while inferential statistics allow generalizing from samples to populations through statistical testing and other methods.
3) The document discusses differences between statistics and statistical data, types of data, levels of measurement, sampling techniques, and uses of statistics.
This presentation is about Basic Statistics-related to types of Data-Qualitative and Quantitative, and its Examples in everyday life- By: Dr. Farhana Shaheen
There are three main measures of central tendency:
1. The mean is the average and is calculated by adding all values and dividing by the total number of values. It is affected by outliers.
2. The median is the middle value when data is arranged in order. It is not affected by outliers.
3. The mode is the most frequent value in the data set. Data can have more than one mode. It indicates the category with the highest frequency but does not account for all values.
The main differences are that the mean can be affected by outliers, the median is not affected by outliers, and the mode
Statistics can be used to analyze data, make predictions, and draw conclusions. It has a variety of applications including predicting disease occurrence, weather forecasting, medical studies, quality testing, and analyzing stock markets. There are two main branches of statistics - descriptive statistics which summarizes and presents data, and inferential statistics which analyzes samples to make conclusions about populations. Key terms include population, sample, parameter, statistic, variable, data, qualitative vs. quantitative data, discrete vs. continuous data, and the different levels of measurement. Important figures in the history of statistics mentioned are William Petty, Carl Friedrich Gauss, Ronald Fisher, and James Lind.
This document provides an introduction to basic statistics concepts. It instructs students to collect data on the ages of classmates, organize it into a frequency table or graph, and answer questions about the distribution of ages. The document explains that statistics involves gathering, arranging, and presenting numeric data systematically, such as through tables, graphs or by sorting data in ascending or descending order. It defines statistics as the study of collecting, analyzing and interpreting data to address research questions.
The document discusses different types of data and measurement scales in statistics. It defines quantitative, qualitative, discrete, continuous, time series, cross-sectional, primary, secondary data. It also explains nominal, ordinal, interval, and ratio scales used to measure data. Each scale permits different statistical tools depending on the logical properties and operations they satisfy such as counting, ordering, finding differences, or the presence of a natural zero.
This document provides an introduction to a course on statistical methods in nursing. It outlines the general objectives of understanding the nature and definition of statistics, its brief historical development, distinguishing samples from populations, types of variables, and the importance of statistics in research. It includes a pre-test to assess students' basic knowledge of statistical concepts before beginning the lessons.
This document discusses statistical and non-statistical questions, explaining that statistical questions can be answered by collecting and analyzing data, while non-statistical questions have definite answers that do not require data. It provides examples of statistical and non-statistical questions, and explains the different types of data - numerical, categorical, discrete, and continuous - that can be collected to answer statistical questions. Steps for solving problems statistically are outlined as collecting data, organizing and summarizing it, and interpreting results.
This document discusses statistical and non-statistical questions, explaining that statistical questions can be answered by collecting and analyzing data, while non-statistical questions have definite answers that do not require data. It provides examples of statistical and non-statistical questions, and explains the different types of data - numerical, categorical, discrete, and continuous - that can be collected to answer statistical questions. Steps for solving problems statistically are outlined as collecting data, organizing and summarizing it, and interpreting results.
Statistics can be used in many fields to collect and analyze numerical data. It has applications in business, government, research, and more. Statistics involves collecting data, organizing it, presenting it visually through tables and charts, analyzing it using methods like averages and correlations, and interpreting the results. The scope of statistics has expanded significantly over time from just government administration to almost every area of research and decision making where quantitative information is involved.
Statistics can be used in many fields to collect and analyze numerical data. It has applications in business, government, research, and more. Statistics involves collecting data, organizing it, presenting it visually, analyzing it, and interpreting the results. The key stages of a statistical investigation are collection, organization, presentation, analysis, and interpretation. Statistics is both a science, in that it uses scientific methods, and an art, in that it involves applying statistical knowledge to solve problems. Its scope has expanded greatly over time from just government administration to many other domains where quantitative data is relevant.
Statistics is the study of collecting, organizing, analyzing, and interpreting numerical data. It has two main branches: descriptive statistics, which describes characteristics of a data set, and inferential statistics, which draws conclusions about a population based on a sample. Key concepts in statistics include populations, samples, parameters, statistics, variables, and data types.
This document outlines a daily lesson log for a 7th grade mathematics class. The objectives are for students to draw conclusions from graphic and tabular data on measures of central tendency and variability. The lesson content includes graphic and tabular data on these measures. Learning resources listed include textbooks, additional materials, and a laptop/LCD projector. The procedures describe introducing, demonstrating, practicing, and evaluating the concepts. The reflection section considers student performance and ways to improve instruction.
mamali national high school
mamali lambayong sultan kudarat
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This document provides an overview of descriptive statistics as taught in a statistics course (STS 102) at Crescent University, Nigeria. It covers topics like statistical data collection methods, presentation of data through tables and graphs, measures of central tendency and dispersion. The key objectives of descriptive statistics are to summarize and describe characteristics of data through measures, charts and diagrams. Inferential statistics is also introduced as a way to make inferences about populations based on samples.
The document provides information on the vision, mission, and core values of Tinago National High School. It then summarizes the school's current situation, including its background, profile in terms of access, quality, and governance. Some key points include: the school was established in 1971 and serves students from fishing and laborer families; enrollment has increased over the past three years; dropout rates have fluctuated with the main cause being student vices; and test scores have generally improved but some subjects still lag behind national standards.
The document summarizes a 3-day school-based seminar on developing strategic intervention modules to be held at Tinago National High School in Leyte, Philippines. The seminar aims to (1) train teachers to develop materials addressing students' least learned skills; (2) improve teacher competency, efficiency and student performance; and (3) assist at-risk students through individualized learning plans. All Tinago teachers must participate in sessions on strategic module characteristics, development, and uses. Presentations, workshops and feedback will be used to help teachers create intervention modules to help struggling students.
The document describes the logo, meaning, and slogan of the Project VILMA program. It provides detailed explanations of each element of the logo and how it symbolizes different aspects of the program. The logo represents the strong bonds between internal and external stakeholders and learners. It depicts teachers equipping learners with knowledge and cultivating their growth and development with the support of all stakeholders. The overall logo symbolizes the program's goal of capturing learners' interest, caring for their lives, and cultivating their future through collaborative efforts to improve education.
Silvestre T. Lumarda - The Working Mayor of the Booming Municipality of InopacanPerla Pelicano Corpez
This document provides a biography of Honorable Silvestre T. Lumarda, the mayor of Inopacan municipality in Leyte, Philippines. It discusses his background growing up in a low-income family and working various jobs before entering politics. As mayor, he focused on improving infrastructure like roads, water access, and buildings. He also emphasized livelihood projects to help residents increase income from activities like vegetable farming after their main crop of abaca was affected by disease. Through these initiatives and prioritizing community relationships, Mayor Lumarda transformed Inopacan and improved living standards for residents over his three terms in office.
This document provides information on conducting a personal SWOT analysis. A SWOT analysis identifies an individual's strengths, weaknesses, opportunities, and threats. It can help people recognize their valuable qualities, areas for improvement, potential career advantages, and external risks. The document recommends individuals identify these factors themselves and have others evaluate them as well. It also outlines how to prioritize the SWOT elements and develop action plans to enhance strengths, address weaknesses, pursue opportunities, and mitigate threats. Conducting regular SWOT analyses can aid career development and decision-making.
1. The document outlines the key functions of management including planning, organizing, staffing, directing, coordinating, and controlling.
2. It describes each function in detail, noting that planning involves defining objectives and strategies, organizing involves structuring work, staffing involves recruiting and placement, directing involves leadership, communication, motivation and supervision, coordinating involves aligning group efforts, and controlling involves monitoring performance.
3. The functions are interrelated and continuous, aiming to achieve organizational goals through the coordinated efforts of people.
This document contains a list of words containing the letter Q organized by letter count. It includes 198 words with 7 letters containing Q, 106 words with 6 letters containing Q, 126 words with 5 letters containing Q, 88 words with 4 letters containing Q, 15 words with 3 letters containing Q, and 2 words with 2 letters containing Q. It also lists words containing Q but without the letter U by letter count.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
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
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.
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.
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.)
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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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.
1. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 1
Chapter 1:
Describing Data
Lesson 1: Variation in Data
TIME FRAME: 1 hour session
OVERVIEW OF LESSON
In this activity, students will be asked to provide some data that will be submitted for
consolidation by the teacher for future lessons. Data on heights and weights, for instance, will be
used for calculating Body Mass Index in Lesson 3. Students will also discuss the concept of
statistical questions (in relation to non-statistical ones), then work in groups to discover variation
in data. Students will be asked to imagine that the data they obtained in their groups would now
be collected for much larger groups (the entire class, all grade 11 students in school, all grade 11
students in the district), and to discuss how data could be summarized.
LEARNING COMPETENCIES: At the end of the lesson, the learner should be able to:
distinguish statistical questions from non-statistical questions,
recognize that data possess variability,
identify methods for summarizing data to answer statistical questions, i.e., sort, classify,
and organize data in tabular form and present this into a pictographs, bar charts, etc.
LESSON OUTLINE:
0. Preliminaries
1. Introduction on Statistics as the Science that Studies Data
2. Initial Lesson: Statistical and Non Statistical Questions
3. Main Lesson: Data and Statistics
4. Small Data Collection Activity and Planning for Data Analysis
DEVELOPMENT OF THE LESSON
(A)Preliminaries (for Future Lessons)
Before the lesson and course starts, prepare a sheet of paper listing everyone’s name in class
with a “Student Number” (see next page). The student number is a random number chosen
in the following fashion:
(a) Make a box with “tickets” listing the numbers 1 up to the number of students in class.
(b) Shake the box, get a ticket, and give the number in the ticket to the first person in the
list.
(c) Shake the box again, get another ticket, and give the number of this ticket to the next
person in the list.
(d) Do (c) until you run out of tickets in the box.
2. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 2
Once the list (see next page) is finished, make sure to inform students confidentially of their
student numbers. Perhaps, when the attendance is called, each student can be provided a
separate piece of paper that lists her/his name and student number. Tell students to
remember their student number, and to always use this throughout the class whenever data
are requested of them. Explain to students that in data collection specific identities are not
required, especially because people have a right to confidentiality, but there should be a way
to develop and maintain a database to check quality of data provided, and verify from
respondent in data collection activity the data provided.
Explanatory Note: These preliminary steps for generating a student number and informing
students confidentially of their student number are essential for the “data collection”
activities to be taken in this lesson and other lessons so that students can be uniquely
identified, without having to obtain their names. In statistical activities, facts are collected
from respondents for purposes of getting aggregate information, but confidentiality should
be protected. This way, respondents can be truthful in giving information, and the researcher
can give a commitment to respondents that the data they provide will never be released to
anyone in a form that will identify them without their authorization.
3. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 3
Student Name Student Number
1.
2,
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32,
33.
34.
35.
4. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 4
(B) Introduction
Provide students their “student numbers” and ask them to fill out Activity Sheet 1-01a. After
3-5 minutes, tell students to submit the Sheet to you so you can put all records on the Class
Recording Sheet. Explain to students that compiling all these records from everyone in the
class is an example of a census since data has been gathered from every student in class.
Mention that the government, through the Philippine Statistics Authority (PSA), conducts
censuses to obtain information about socio-economic conditions in the country. This helps
government makes plans, such as how many schools and hospitals to build. Censuses of
population and housing are conducted every 10 years on years ending in zero (e.g., 1990,
2000, 2010) to obtain population counts, and demographic information about all Filipinos.
Mid-decade population censuses have also been conducted since 1995. Censuses of
agriculture, and of Philippine business and industry, are also conducted by the PSA to obtain
information on production and other relevant economic information.
Inform students that the student numbers they were given are meant to identify them without
having to know their specific identities in the class recording sheet (which will contain the
consolidated records everyone provided). This helps protect confidentiality of information.
Mention that the PSA is bound by law to protect the confidentiality of information provided
by respondents. Even market research organizations in the private sector and individual
researchers also guard confidentiality as they merely want to obtain aggregate data.
Ask students what comes to their minds when they hear the term “data” (which may be
viewed as a collection of facts from experiments, observations, sample surveys and
censuses, and administrative reporting systems).
Give them a follow up question about whether data, such as the facts they gave in activity
sheet 1-01a, would be the same or varying from person to person. Even if the data varies,
some numbers may show up more than once in the entire data set. The frequency of a
particular data value is the number of times the data value occurs.
(C)Initial Lesson: Statistical Questions and Non-Statistical Questions
Tell students that data are collected to answer statistical questions, the answers of which can
change depending on who it is asked to, and when it is asked (Non-statistical questions are
questions that anticipate a single answer.)
Give a 5 minute exercise to the students on distinguishing statistical questions from non-
statistical questions.
Ask students which of the following are statistical questions and why:
How old is student number 3 (in the class list)? (Not a statistical question since only
a particular fact, the age of student number 3, is of interest)
How old are the people who watch the most recent episode of the television show
“Maalaala Mo Kaya?” (Statistical question since this will require getting data on
ages of all viewers of the tv show)
5. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 5
Do dogs eat more than cats? (Statistical question since this will require getting
data on the amount of food eaten by dogs and cats, maybe a sample of them, for
a reference period, say past week, or past month)
Is the vehicle of the Mayor of our city/town/municipality bigger than the vehicle used
by the President of the Philippines? (Not a statistical question since only a particular
fact, size of mayor’s car in relation to size of vehicle of president, is of interest)
How many days are there in December? (Not a statistical question since only a
particular fact, number of days in December, is of interest)
Does it rain more in Cebu than in Davao? (Statistical question since this will
require getting rainfall data on the two cities in a reference period, say past
month, past year)
Do I have a college degree? (Not a statistical question since only a particular fact,
whether or not I have a college degree, is of interest)
How much was the Supreme Court Chief Justice’s last paycheck for? Not a statistical
question since only a particular fact, the amount of income received by the SC CJ in
the last paycheck, is of interest)
Do math teachers earn more than science teachers? (Statistical question since
this will require getting data on income/wages of either all math and science
teachers, or even a sample of these teachers)
How many searches on Google do residents in Makati City (or some other city
near the school) conduct each day? (Statistical question since this will require
getting data on the frequency of Google searches of residents of Makati or
whatever city of interest)
What is the weight of Student A, say Ana (or whatever random name you can get
from the list of student names)? (Not a statistical question since only a particular fact,
weight of Student A is being asked)
What is the proportion of students in class who are underweight or overweight
for their age? (Statistical question since this will require getting data on the
weights of all students in class, comparing these weights to a reference weight for
student ages, and determining the percentage of students that are underweight
or overweight for their age)
(D)Main Lesson: Data and Statistics
Suggest to students that data may be viewed as the facts (counts, measurements, or opinions)
obtained to answer a statistical question.
Define Statistics is a science that studies data, and what we can do with data. Suggest that
this involves processes from collecting, processing (including performing quality checks),
analyzing, interpreting and communicating data.
Trivia: The word “statistics” actually comes from the word “state”— because governments
have been involved in the statistical activities, especially the conduct of censuses either for
military or taxation purposes. The need for and conduct of censuses are recorded in the pages
of holy texts. In the Christian Bible, particularly the Book of Numbers, God is reported to
have instructed Moses to carry out a census. Another census mentioned in the Bible is the
6. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 6
census ordered by Caesar Augustus throughout the entire Roman Empire before the birth of
Christ.
Inform students that uncovering patterns in data involves not just science but also art, and
this is why some people may think “Stat is eeeks!” and may view any statistical procedures
and results with much skepticism. (See Figure 1-1.)
Make known to students that statistical methods enable us to
characterize persons, objects, situations, and phenomena;
explain relationships among variables ;
formulate objective assessments and comparisons; and,
make evidence-based decisions and predictions.
and that the main tasks of a statistician include:
Designing the collection of data to answer statistical questions in a way that
maximizes information content and minimizes bias;
Verifying the quality of the data after it is collected
Examining data so that insight and meaningful information can be produced to
support decision making.
Figure 1-1. Cartoon: " ...recommended by 4 out of 5 quacks!"
(Source: http://www.cartoonstock.com)
7. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 7
(E) Small Data Collection Activity and Planning for Data Analysis
Divide students into groups of five. Tell students to share with each other some opinions and
facts to answer about three questions (that will not yield a “sensitive” response). They may
use questions for Activity Sheet 1-01a:
What is their height (in cm?) and weight (in kg)? the age of their mother?
What is their favorite color?
How do they feel today?
Or other questions (that will not yield a sensitive response):
Are the five students satisfied with the way the mayor does his/her job? (yes, no,
unsure, no opinion)
How many hours did the students watch television during the past seven days?
How many hours did they go on facebook yesterday?
Explanatory Note about Data Collection Activity: The questions listed above are indicative
to help students learn that data has variation. It is crucial to ask questions of interest that are
not culturally sensitive.
After 5 minutes of sharing answers with each other, ask students whether the answers shared
with each other were the same, or whether they varied.
Tell students to imagine that these same questions would now be asked of all grade 11
students in the entire school, or in the entire district.
Ask them how they would summarize the information collected.
Possible Answers:
Histogram for heights and weights of students
Histogram for ages of their fathers and for their mothers
Bar chart or Pie Chart for (Distribution of) favorite color
Pictogram/Pie chart/Bar chart on satisfaction with the mayor
Bar chart/Pie chart for hours spent watching television in the past 7 days
Bar chart for hours spent on facebook yesterday
KEY POINTS
Difference between a statistical question and a non-statistical question
The bedrock of statistics (the science that studies data) is data, which is characterized by
variation.
We can summarizing data collected to answer a statistical question by way of
o Graphs (pictographs, bar graphs)
o Summary numbers (median, mode)
8. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 8
REFERENCES
Albert, J. R. G. (2008).Basic Statistics for the Tertiary Level (ed. Roberto Padua, Welfredo
Patungan, Nelia Marquez), published by Rex Bookstore.
Workbooks in Statistics 1: 11th
Edition, Institute of Statistics, UP Los Banos, College Laguna
4031
https://www.khanacademy.org/math/probability/statistical-studies/statistical-
questions/v/statistical-questions
https://www.illustrativemathematics.org/content-standards/tasks/703
9. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 9
ACTIVITY SHEET NUMBER 1-01a
Students should completely fill out the following:
1. Student Number : _________________________
2. Sex (put a check or cross):
________ Male ________ Female
3. Number of siblings : _________________________
4. Weight (in kilograms) : _________________________
5. Height (in meters) : _________________________
6. Age of mother (as of her last birthday in years) : _________________________ (if mother
deceased, provide age if she were alive)
7. Daily allowance in school (in pesos) : _________________________
8. Daily food expenditure in school (in pesos) : _________________________
9. Usual number of text messages sent in a day : _________________________
10. Favorite color (put a check or cross; choose only one):
____White ____Red ____ Pink ____ Orange ____Yellow ____Green
____Blue ____Purple ____Brown ____Gray ____Black
11. Usual Sleeping Time (on weekdays): _________________________
12. On a scale from 1 (very unhappy) to 10 (happiest), how do you feel today? : ____________
10. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 10
ACTIVITY SHEET 1-01b.
Groups should fill out responses to some questions :
Student ID
Question
1.
2.
3.
Are the responses varying or the same?
How can we summarize the data collected for each of the questions above (especially if we
consolidate the data from the entire class) ?
11. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 11
CLASS RECORDING SHEET 1-01a (for the Teacher)
(PRINT MORE THAN 1 copy, if necessary)
Student
Number
Sex
( 1=
male; 2
female)
Number
of
siblings
Reported
Weight
(in kg)
Reported
Height
(in m)
Age of
mother
(in
years)
. Daily
allowance
in school
Daily food
expenditure
in school
Usual
number
of text
messages
sent in a
day
Usual
Sleeping
Time (on
weekdays)
Rating
on
Feeling
Today (1
very
unhappy,
10
happiest)
Actual
Weight
(in
kg)*
Actual
Height
(in
m)*
* to be obtained in next lesson
12. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 12
ASSESSMENT
1. Name at least one difference between a statistical question and a non statistical question.
ANSWER: Statistical questions are answered by collecting data with variation (and consequently
summaries for the data will be required), while non-statistical questions are questions where answer
require specific facts (and not data with variation), so summary statistics and graphs will not be needed
for non-statistical questions.
2. Ten persons were randomly selected and asked how many letters were in their middle names,
and we received the following data: 6, 6, 7, 12, 15, 7, 8, 7, 6, 7
Ask students to make a bar graph with this data
Answer:
01234
Frequency
5 10 15
letters
13. C h a p t e r 1 D e s c r i b i n g D a t a – L e s s o n 1 Page 13
3. Martin collected data over the last 10 days on the amount of hours of sleep he had every night,
and made a line plot of these data.
What was the most sleep he got in one night? __________________ Answer: 12 hrs
What was the least amount of sleep he got in one night? ________________ Answer: 7 hrs
What is the most common amount of sleep I get? _________________ Answer:8 hrs
How many nights did he sleep less than 9 hours? _________________ Answer: 6 nights
How many nights did he sleep more than 9 hours? _____________ Answer: 2 nights
4. Ronald collected information about favorite sports among his friends
What is the most popular type of dog from the data? Answer: Basketball
How many of Ronald’s friends that were questioned do not consider Basketball or Football
as their favorite sport? Answer: 5
How many friends did Ronald question? Answer : 12
Explanatory Note: Teachers have the option to just ask this assessment orally to the entire class, or
to group students and ask them to identify answers, or to give this as homework, or to use some
questions/items here for a chapter examination.
0
1
2
3
4
5
6
Favorite Sport
Frequency
Sport
Chess Basketball Football Volleyball
Hours of Sleep per Night:
x
x
x x x
x x x x x
6 7 8 9 10 11 12
x – one night