This document provides demonstrations of calculating the mean, median, mode, and range for various data sets. It explains how to find each average value and compares the strengths and weaknesses of each. The mean averages all values, the median ignores outliers, and the mode represents non-numerical or categorical data. Examples are worked through step-by-step and the key is to order the data before analyzing it using these different averaging methods.
This document contains a lesson on calculating and interpreting measures of central tendency (mean, median, mode) and spread (range) from data sets. It includes definitions of these statistical terms, examples of calculating them for various data sets, and discussions of how outliers impact the mean, median and mode. The key lesson is on identifying which measure of central tendency (mean, median or mode) best describes a particular data set and why.
This document contains a lesson on calculating and interpreting measures of central tendency (mean, median, mode) and range from data sets. It includes definitions of these terms, examples of finding the mean, median, mode and range of various data sets, and discussions of how outliers impact the measures of central tendency. The lesson emphasizes that different measures may be best suited for different data distribution shapes and the presence of outliers.
This document contains a lesson on mean, median, mode, and range. It includes definitions of these statistical terms, examples of calculating them for different data sets, and discussions of how outliers can affect the values. The lesson emphasizes that the mean, median, and mode should be selected based on which measure best describes the distribution of the actual data.
Measures of Central Tendency Final.pptAdamManlunas
Here is the summary of the data set:
Mean = 30
Median = 27
Mode = No mode (each value occurs only once)
The outlier is 118. Removing the outlier, the mean would decrease to 28 and the median would remain 27. The median best describes the data set as it is not greatly affected by outliers and most of the data is clustered around 27.
A measure of central tendency (also referred to as measures of center or central location) is a summary measure that attempts to describe a whole set of data with a single value that represents the middle or center of its distribution. The are some limitations to using the mode. In some distributions, the mode may not reflect the centre of the distribution very well. When the distribution of retirement age is ordered from lowest to highest value, it is easy to see that the centre of the distribution is 57 years, but the mode is lower, at 54 years.
This document discusses various statistical measures used to summarize and describe data, including measures of central tendency (mean, median, mode) and measures of dispersion (range, variance, standard deviation). It provides definitions and examples of calculating each measure. Standardized scores like z-scores and t-scores are also introduced as ways to compare performance across different tests or distributions. Exercises are included for readers to practice calculating and interpreting these common descriptive statistics.
A measure of central tendency (also referred to as measures of centre or central location) is a summary measure that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution.
This document provides a lesson on measures of central tendency and dispersion. It defines mean, median, mode, range, quartiles, interquartile range, and outliers. Examples are provided to demonstrate how to calculate and interpret these measures for data sets. The document also explains how to construct box-and-whisker plots and choose the best measure of central tendency depending on the presence of outliers. Students are then quizzed on applying these concepts to analyze sample data sets.
This document contains a lesson on calculating and interpreting measures of central tendency (mean, median, mode) and spread (range) from data sets. It includes definitions of these statistical terms, examples of calculating them for various data sets, and discussions of how outliers impact the mean, median and mode. The key lesson is on identifying which measure of central tendency (mean, median or mode) best describes a particular data set and why.
This document contains a lesson on calculating and interpreting measures of central tendency (mean, median, mode) and range from data sets. It includes definitions of these terms, examples of finding the mean, median, mode and range of various data sets, and discussions of how outliers impact the measures of central tendency. The lesson emphasizes that different measures may be best suited for different data distribution shapes and the presence of outliers.
This document contains a lesson on mean, median, mode, and range. It includes definitions of these statistical terms, examples of calculating them for different data sets, and discussions of how outliers can affect the values. The lesson emphasizes that the mean, median, and mode should be selected based on which measure best describes the distribution of the actual data.
Measures of Central Tendency Final.pptAdamManlunas
Here is the summary of the data set:
Mean = 30
Median = 27
Mode = No mode (each value occurs only once)
The outlier is 118. Removing the outlier, the mean would decrease to 28 and the median would remain 27. The median best describes the data set as it is not greatly affected by outliers and most of the data is clustered around 27.
A measure of central tendency (also referred to as measures of center or central location) is a summary measure that attempts to describe a whole set of data with a single value that represents the middle or center of its distribution. The are some limitations to using the mode. In some distributions, the mode may not reflect the centre of the distribution very well. When the distribution of retirement age is ordered from lowest to highest value, it is easy to see that the centre of the distribution is 57 years, but the mode is lower, at 54 years.
This document discusses various statistical measures used to summarize and describe data, including measures of central tendency (mean, median, mode) and measures of dispersion (range, variance, standard deviation). It provides definitions and examples of calculating each measure. Standardized scores like z-scores and t-scores are also introduced as ways to compare performance across different tests or distributions. Exercises are included for readers to practice calculating and interpreting these common descriptive statistics.
A measure of central tendency (also referred to as measures of centre or central location) is a summary measure that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution.
This document provides a lesson on measures of central tendency and dispersion. It defines mean, median, mode, range, quartiles, interquartile range, and outliers. Examples are provided to demonstrate how to calculate and interpret these measures for data sets. The document also explains how to construct box-and-whisker plots and choose the best measure of central tendency depending on the presence of outliers. Students are then quizzed on applying these concepts to analyze sample data sets.
The document discusses different types of averages including mode, mean, and median. It provides definitions and examples of how to calculate each. The mode is the most common value, the mean is the average found by adding all values and dividing by the total count, and the median is the middle value when data is arranged in order. The document shows how to identify the mode, mean, and median in various data sets and discusses when each measure is most appropriate.
This document provides an outline and summary of key concepts related to data analysis, including measures of central tendency (mean, median, mode), spread of distribution (range, variance, standard deviation), and experimental designs (paired t-test, ANOVA). It explains how to calculate and interpret the mean, median, mode, range, variance, and standard deviation. It also provides brief definitions and examples of paired t-tests and ANOVA.
This document contains a lesson plan on measures of central tendency of ungrouped data for 7th grade mathematics. The lesson plan defines mean, median, and mode, and provides examples of calculating each. It includes an activity that challenges students to solve problems involving finding the mean, median, and mode of various data sets. The activity is meant to assess students' understanding of applying these measures of central tendency to real-world scenarios. The lesson concludes by having students practice defining and calculating measures of central tendency, and applying them to sample data sets and a real-life example.
This document discusses different measures of central tendency including mode, median, and mean. It provides examples and explanations of how to calculate each measure for a set of data. For mode, it explains that the mode is the most frequent value. For median, it describes that the median is the middle value when values are arranged in order. And for mean, it defines the mean as the sum of all values divided by the number of values.
The document defines and provides examples to calculate the mean, median, and mode of data sets. It explains that the mode is the most frequently occurring value, the median is the middle value when data is arranged in order, and the mean is calculated by summing all values and dividing by the total number of data points. Examples are provided to demonstrate calculating the mean, median, and mode of data sets containing test scores, sleeping hours, and death rates in Surabaya in 1999.
Please Subscribe to this Channel for more solutions and lectures
http://www.youtube.com/onlineteaching
Chapter 3: Describing, Exploring, and Comparing Data
3.1: Measures of Center
This document defines and provides examples of calculating four common measures of central tendency: mean, median, mode, and range. The mean is the average and is calculated by summing all values and dividing by the number of values. The median is the middle value when values are arranged in order. The mode is the most frequently occurring value. The range is the difference between the greatest and least values. Examples are provided to demonstrate calculating each measure using a sample data set of numbers.
This document discusses three measures of central tendency: mean, median, and mode. It provides examples and step-by-step explanations for calculating each measure. The mean is the average and is calculated by adding all values and dividing by the number of values. The median is the middle number when values are ordered from least to greatest. The mode is the value that occurs most frequently in a data set.
The document defines and provides examples of calculating the mean, median, and mode of data sets. It discusses how the mean is the average, median is the middle value, and mode is the most frequent value. Examples are provided to demonstrate calculating each measure of central tendency for both ungrouped and grouped data. An assessment with multiple choice and short answer questions is also included to test understanding of these concepts.
This document provides instructions and examples for calculating measures of central tendency (mean, median, mode) using data sets. It begins with objectives and motivation by introducing mean, median and mode. Examples are provided to demonstrate calculating the mean, median and mode of students' test scores. Formulas and step-by-step processes are outlined for each measure. The document concludes by providing practice problems for students to calculate mean, median, mode and range for various data sets.
Measures of central tendency and dispersionAbhinav yadav
This document discusses various measures of central tendency and dispersion. It defines the mean, median, and mode as measures of central tendency, and describes how to calculate the arithmetic mean, geometric mean, harmonic mean, median, and mode. It also discusses measures of dispersion such as variance and standard deviation, and classifies them as either measures of absolute dispersion or relative dispersion.
This document defines and provides examples of different measures of central tendency including range, mean, median, and mode. It then provides 9 questions asking the reader to identify the central tendency measure that best represents given data sets and explain their reasoning. Examples include data on product defects, test scores, puppy weights, commuting methods, snowfall, cereal and property tax bills. The reader is asked to calculate and compare the mean, median, mode, range and identify any outliers for each data set.
UNIT III - Arrays - Measures of Center and Variation (2).pptAjithGhoyal
This document provides information on measures of central tendency and dispersion in data sets. It defines and provides examples of calculating the mean, median, mode, and midrange as common measures of central tendency. It also discusses weighted averages and trimmed means. The document then covers measures of dispersion such as range, variance and standard deviation. It provides formulas and examples of calculating these measures to quantify the spread of data around the central tendency.
This document discusses various measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each measure. The mean is the average and is calculated by summing all values and dividing by the total number of data points. The median is the middle value when data is arranged in order. The mode is the value that occurs most frequently in the data set. Examples are given to demonstrate calculating each measure. The document also discusses advantages and limitations of each central tendency measure.
This document provides an introduction to key statistical concepts for biology, including mean, mode, median, and standard deviation. It defines sample size and population, and gives examples of calculating each statistical measure using a sample of movie ratings from 5 friends. The mean is the average, the mode is the most frequent value, the median is the middle value when numbers are ordered, and the standard deviation measures how spread out values are from the mean.
The document provides information about measures of central tendency for ungrouped data, including definitions and examples of mean, median, and mode. It discusses calculating the mean by summing all values and dividing by the number of observations. Median is defined as the middle value when data is ranked from lowest to highest. Mode is the most frequently occurring value. Examples are provided to demonstrate calculating each measure for sample data sets.
Students will learn how to calculate mean, median, mode, and range from data sets. They will also learn to determine which average (mean, median or mode) best represents a given data set by taking into account outliers. Examples are provided to demonstrate calculating each average and identifying the best representative average for different data sets.
Measures of central tendency by maria diza c. febriomariadiza
This document provides instructions for a lesson on measures of central tendency. It begins by explaining that measures of central tendency include the mean, median, and mode, which are ways to describe the central or typical value in a data set. The objectives are given as helping students develop an understanding of these concepts. Examples and calculations are provided to illustrate finding the mean, median, and mode. Exercises in the form of multiple choice questions test the understanding of calculating and identifying the measures of central tendency.
For this project, students in Mrs. Beile's learning center math class were tasked with creating a Powerpoint presentation that explained how to solve a math problem. The students were expected to select a math concept they were struggling with themselves and pretend they were explaining the concept to a friend. By going through the process, the students were able to develop mastery and reinforce the concept for themselves. Everyone did a fantastic job!
This document discusses measures of central tendency including the mean, median, and mode. It provides examples to calculate and compare the mean, median, and mode for sets of data. The mean is the average value, the median is the middle value, and the mode is the most frequent value. The document explains that the mean may be higher or lower than the median depending on whether there are more values above or below it. It also gives an example of calculating the mean, median, and mode for golf scores to determine which player has the better average score.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
The document discusses different types of averages including mode, mean, and median. It provides definitions and examples of how to calculate each. The mode is the most common value, the mean is the average found by adding all values and dividing by the total count, and the median is the middle value when data is arranged in order. The document shows how to identify the mode, mean, and median in various data sets and discusses when each measure is most appropriate.
This document provides an outline and summary of key concepts related to data analysis, including measures of central tendency (mean, median, mode), spread of distribution (range, variance, standard deviation), and experimental designs (paired t-test, ANOVA). It explains how to calculate and interpret the mean, median, mode, range, variance, and standard deviation. It also provides brief definitions and examples of paired t-tests and ANOVA.
This document contains a lesson plan on measures of central tendency of ungrouped data for 7th grade mathematics. The lesson plan defines mean, median, and mode, and provides examples of calculating each. It includes an activity that challenges students to solve problems involving finding the mean, median, and mode of various data sets. The activity is meant to assess students' understanding of applying these measures of central tendency to real-world scenarios. The lesson concludes by having students practice defining and calculating measures of central tendency, and applying them to sample data sets and a real-life example.
This document discusses different measures of central tendency including mode, median, and mean. It provides examples and explanations of how to calculate each measure for a set of data. For mode, it explains that the mode is the most frequent value. For median, it describes that the median is the middle value when values are arranged in order. And for mean, it defines the mean as the sum of all values divided by the number of values.
The document defines and provides examples to calculate the mean, median, and mode of data sets. It explains that the mode is the most frequently occurring value, the median is the middle value when data is arranged in order, and the mean is calculated by summing all values and dividing by the total number of data points. Examples are provided to demonstrate calculating the mean, median, and mode of data sets containing test scores, sleeping hours, and death rates in Surabaya in 1999.
Please Subscribe to this Channel for more solutions and lectures
http://www.youtube.com/onlineteaching
Chapter 3: Describing, Exploring, and Comparing Data
3.1: Measures of Center
This document defines and provides examples of calculating four common measures of central tendency: mean, median, mode, and range. The mean is the average and is calculated by summing all values and dividing by the number of values. The median is the middle value when values are arranged in order. The mode is the most frequently occurring value. The range is the difference between the greatest and least values. Examples are provided to demonstrate calculating each measure using a sample data set of numbers.
This document discusses three measures of central tendency: mean, median, and mode. It provides examples and step-by-step explanations for calculating each measure. The mean is the average and is calculated by adding all values and dividing by the number of values. The median is the middle number when values are ordered from least to greatest. The mode is the value that occurs most frequently in a data set.
The document defines and provides examples of calculating the mean, median, and mode of data sets. It discusses how the mean is the average, median is the middle value, and mode is the most frequent value. Examples are provided to demonstrate calculating each measure of central tendency for both ungrouped and grouped data. An assessment with multiple choice and short answer questions is also included to test understanding of these concepts.
This document provides instructions and examples for calculating measures of central tendency (mean, median, mode) using data sets. It begins with objectives and motivation by introducing mean, median and mode. Examples are provided to demonstrate calculating the mean, median and mode of students' test scores. Formulas and step-by-step processes are outlined for each measure. The document concludes by providing practice problems for students to calculate mean, median, mode and range for various data sets.
Measures of central tendency and dispersionAbhinav yadav
This document discusses various measures of central tendency and dispersion. It defines the mean, median, and mode as measures of central tendency, and describes how to calculate the arithmetic mean, geometric mean, harmonic mean, median, and mode. It also discusses measures of dispersion such as variance and standard deviation, and classifies them as either measures of absolute dispersion or relative dispersion.
This document defines and provides examples of different measures of central tendency including range, mean, median, and mode. It then provides 9 questions asking the reader to identify the central tendency measure that best represents given data sets and explain their reasoning. Examples include data on product defects, test scores, puppy weights, commuting methods, snowfall, cereal and property tax bills. The reader is asked to calculate and compare the mean, median, mode, range and identify any outliers for each data set.
UNIT III - Arrays - Measures of Center and Variation (2).pptAjithGhoyal
This document provides information on measures of central tendency and dispersion in data sets. It defines and provides examples of calculating the mean, median, mode, and midrange as common measures of central tendency. It also discusses weighted averages and trimmed means. The document then covers measures of dispersion such as range, variance and standard deviation. It provides formulas and examples of calculating these measures to quantify the spread of data around the central tendency.
This document discusses various measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each measure. The mean is the average and is calculated by summing all values and dividing by the total number of data points. The median is the middle value when data is arranged in order. The mode is the value that occurs most frequently in the data set. Examples are given to demonstrate calculating each measure. The document also discusses advantages and limitations of each central tendency measure.
This document provides an introduction to key statistical concepts for biology, including mean, mode, median, and standard deviation. It defines sample size and population, and gives examples of calculating each statistical measure using a sample of movie ratings from 5 friends. The mean is the average, the mode is the most frequent value, the median is the middle value when numbers are ordered, and the standard deviation measures how spread out values are from the mean.
The document provides information about measures of central tendency for ungrouped data, including definitions and examples of mean, median, and mode. It discusses calculating the mean by summing all values and dividing by the number of observations. Median is defined as the middle value when data is ranked from lowest to highest. Mode is the most frequently occurring value. Examples are provided to demonstrate calculating each measure for sample data sets.
Students will learn how to calculate mean, median, mode, and range from data sets. They will also learn to determine which average (mean, median or mode) best represents a given data set by taking into account outliers. Examples are provided to demonstrate calculating each average and identifying the best representative average for different data sets.
Measures of central tendency by maria diza c. febriomariadiza
This document provides instructions for a lesson on measures of central tendency. It begins by explaining that measures of central tendency include the mean, median, and mode, which are ways to describe the central or typical value in a data set. The objectives are given as helping students develop an understanding of these concepts. Examples and calculations are provided to illustrate finding the mean, median, and mode. Exercises in the form of multiple choice questions test the understanding of calculating and identifying the measures of central tendency.
For this project, students in Mrs. Beile's learning center math class were tasked with creating a Powerpoint presentation that explained how to solve a math problem. The students were expected to select a math concept they were struggling with themselves and pretend they were explaining the concept to a friend. By going through the process, the students were able to develop mastery and reinforce the concept for themselves. Everyone did a fantastic job!
This document discusses measures of central tendency including the mean, median, and mode. It provides examples to calculate and compare the mean, median, and mode for sets of data. The mean is the average value, the median is the middle value, and the mode is the most frequent value. The document explains that the mean may be higher or lower than the median depending on whether there are more values above or below it. It also gives an example of calculating the mean, median, and mode for golf scores to determine which player has the better average score.
Similar to Mean-Median-Mode-Range-Demonstration.pptx (20)
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
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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 ...
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Physiology and chemistry of skin and pigmentation, hairs, scalp, lips and nail, Cleansing cream, Lotions, Face powders, Face packs, Lipsticks, Bath products, soaps and baby product,
Preparation and standardization of the following : Tonic, Bleaches, Dentifrices and Mouth washes & Tooth Pastes, Cosmetics for Nails.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
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.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
1. Mean, Median, Mode & Range – Demonstration
This resource provides animated demonstrations of the mathematical method.
Check animations and delete slides not needed for your class.
2. Andy is growing flowers.
After 1 week he measures the height of the flowers.
Which group of flowers grew better?
3. To compare sets of data we use averages:
a number that is used to represent the whole group.
We could use the middle value of the group.
Middle Value
Middle Value
Using the median average the
red flowers grew better.
4. We can represent data (like flower height) using bars instead.
Using the median, which group of flowers grew better?
To help we place the data in size order.
2
3
The pink flowers grew better – they have a better median average.
Is this fair?
5. Place data in size order &
select the middle value.
Median
Does not include every piece of data
Ignores outliers
What can we do if there are 2 middle values?
The median is between the two middle values.
6. Two teams played darts.
Using the mean average the
adults won.
Adults: 32 points Kids: 35 points
Which team won?
To be fair, we want to calculate points scored per player, the mean average.
Total Points ÷ Number of Players
8 points per player 7 points per player
7. We can represent scores from a different dart game using bars.
Using the mean, which team won?
Total the data and divide it by the quantity.
2
The green team won – they have a better mean average.
Is this fair?
2 2 1
3 3
1
5
3
8. Place data in size order &
select the middle value.
Median
Does not include every piece of data
Ignores outliers
Sum data & divide by
the number of values.
Mean
Can be distorted by outliers
Includes all data
9. Ash was practicing darts.
She scored:
1, 5, 20, 1, 1, 1, 5, 1, 1
Is the mean a good representation of this data?
Mean = 36 ÷ 9 = 4
The mean is larger than most of the scores. This is because of the outlier 20.
Instead we can use the mode average: the most common piece of data.
Mode = 1
10. A shop recorded the flowers it sold.
pink, red, red, red, blue, pink, blue, red
Can we calculate a mean or median?
For non-numerical data,
we can calculate the mode: the most common piece of data.
Mode = Red
11. Averages: One value to represent the group.
Mean
Sum of values divided by quantity
7, 1, 4, 1, 2
Median
The middle value.
2 middle values = take the mean of those.
Mode
The most common value.
7, 1, 4, 1, 2
7+1+4+1+2
5
= 3
1, 1, 2, 4, 7
7, 1, 4, 1, 2
1, 1, 2, 4, 7
= 2
= 1
4, 5, 0, 2, 9, 1
4, 5, 0, 2, 9, 1
4+5+0+2+9+1
6
= 3.5
0, 1, 2, 4, 5, 9
4, 5, 0, 3, 9, 1
0, 1, 2, 4, 5, 9
= 3
= No Mode
12.
13.
14. Mr Smith gave two classes the same science test.
Which class do you think he is more proud of?
Class A
Mean = 34 marks
Median = 32 marks
Highest score = 29 marks
Lowest score = 38 marks
Class B
Mean = 33 marks
Median = 34 marks
Highest score = 71 marks
Lowest score = 15 marks
The mean & median are very similar.
However Class B has a wide range of results.
Class A were more consistent.
Range = 7 marks Range = 56 marks
15. We can represent test results using bars.
Which class was more consistent?
Class X has a bigger range:
the difference between the highest result & the lowest result.
Class X Class Y
A range represents the spread of the data, it is not an average.
16. A range only considers the highest & lowest values.
The range for Class A is greater, but the class was actually more consistent.
Class A Class B
What may be the problem using range?
17. Calculating MMMR
Find the Mean, Median, Mode & Range for
this set of data.
DEMO
1, 0, 6, 2, 1
Mean =
= 10 ÷ 5
0, 1, 1, 2, 6
Median =
(0+1+1+2+6) ÷ 5
1
Mode = 1
Range = 6 – 0
= 6
place in
order
= 2
18. Calculating MMMR
Find the Mean, Median, Mode & Range for
this set of data.
DEMO
7, 2, 4, 3, 9
Mean =
= 25 ÷ 5
2, 3, 4, 7, 9
Median =
(2+3+4+7+9) ÷ 5
4
Mode = No Mode
Range = 9 – 2
= 7
place in
order
= 5
19. Calculating MMMR
Find the Mean, Median, Mode & Range for
this set of data.
DEMO
8, 3, 10, 4, 2, 6, 2
Mean =
= 35 ÷ 7
2, 2, 3, 4, 6, 8, 10
Median =
(2+2+3+4+6+8+10) ÷ 7
4
Mode = 2
Range = 10 – 2
= 8
place in
order
= 5
20. Calculating MMMR
Find the Mean, Median, Mode & Range for
this set of data.
DEMO
6, 3, 1, 4, 7, 0, 3, 8
Mean =
= 32 ÷ 8
0, 1, 3, 3, 4, 6, 7, 8
Median =
(0+1+3+3+4+6+7+8) ÷ 8
(3+4) ÷ 2
Mode = 3
Range = 8 – 0
= 8
place in
order
= 4
= 3.5
21. Calculating MMMR
Find the Mean, Median, Mode & Range for
this set of data.
DEMO YOUR TURN
6, 3, 1, 4, 7, 0, 3, 8
Mean =
= 32 ÷ 8
0, 1, 3, 3, 4, 6, 7, 8
Median =
(0+1+3+3+4+6+7+8) ÷ 8
(3+4) ÷ 2
Mode = 3
Range = 8 – 0
= 8
place in
order
= 4
= 3.5
Find the Mean, Median, Mode & Range for
this set of data.
3, 1, 5, 1, 1, 3, 7
Mean =
= 21 ÷ 7
1, 1, 1, 3, 3, 5, 7
Median =
(1+1+1+3+3+5+7) ÷ 7
3
Mode = 1
Range = 7 – 1
= 6
place in
order
= 3
22. Calculating MMMR
Find the Mean, Median, Mode & Range for
this set of data.
DEMO YOUR TURN
6, 3, 1, 4, 7, 0, 3, 8
Mean =
= 32 ÷ 8
0, 1, 3, 3, 4, 6, 7, 8
Median =
(0+1+3+3+4+6+7+8) ÷ 8
(3+4) ÷ 2
Mode = 3
Range = 8 – 0
= 8
place in
order
= 4
= 3.5
Find the Mean, Median, Mode & Range for
this set of data.
5, 9, 0, 2, 11, 4, 1, 8
Mean =
= 40 ÷ 8
0, 1, 2, 4, 5, 8, 9, 11
Median =
(0+1+2+4+5+8+9+11) ÷ 8
(4+5) ÷ 2
Mode = No Mode
Range = 11 – 0
= 11
place in
order
= 5
= 4.5
23. Calculating MMMR
Find the Mean, Median, Mode & Range for
this set of data.
DEMO YOUR TURN
6, 3, 1, 4, 7, 0, 3, 8
Mean =
= 32 ÷ 8
0, 1, 3, 3, 4, 6, 7, 8
Median =
(0+1+3+3+4+6+7+8) ÷ 8
(3+4) ÷ 2
Mode = 3
Range = 8 – 0
= 8
place in
order
= 4
= 3.5
Find the Mean, Median, Mode & Range for
this set of data.
6, 5, 1, 5, 7, 1, 3, 8
Mean =
= 36 ÷ 8
1, 1, 3, 5, 5, 6, 7, 8
Median =
(1+1+3+5+5+6+7+8) ÷ 8
(5+5) ÷ 2
Mode = No Mode
Range = 8 – 1
= 7
place in
order
= 4.5
= 5
24. Calculating MMMR
Find the Mean, Median, Mode & Range for
this set of data.
DEMO YOUR TURN
6, 3, 1, 4, 7, 0, 3, 8
Mean =
= 32 ÷ 8
0, 1, 3, 3, 4, 6, 7, 8
Median =
(0+1+3+3+4+6+7+8) ÷ 8
(3+4) ÷ 2
Mode = 3
Range = 8 – 0
= 8
place in
order
= 4
= 3.5
Find the Mean, Median, Mode & Range for
this set of data.
10, 4, 5, 7, 4, 8, 16, 4, 5
Mean =
= 63 ÷ 9
4, 4, 4, 5, 5, 7, 8, 10, 16
Median =
(4+4+4+5+5+7+8+10+16) ÷ 9
5
Mode = 4
Range = 16 – 4
= 12
place in
order
= 7
25. A 1 2 2 3 7 B 1 4 6 8 5 2 2
Calculate the Mean, Median, Mode & Range for each set of data.
Mean = 3 Median = 2
Mode = 2 Range = 6
Mean = 4 Median = 4
Mode = 2 Range = 7
C
8 10 9 7
3 0 5 6
D
8 4 3 5 2
3 6 1 0 3
Mean = 6 Median = 6.5
Mode = No Mode Range = 10
Mean = 3.5 Median = 3
Mode = 3 Range = 8
E
−5 7 8 13 5
0 6 −10 3
F
23 21 24 20 22 20
20 23 22 24 21 24
Mean = 3 Median = 5
Mode = No Mode Range = 23
Mean = 22 Median = 22
Mode = No Mode Range = 4
26.
27. A 5 5 6 8 9 B 15 6 4 8 12 6 10
Calculate the Mean, Median, Mode & Range for each set of data.
Mean = 6.6 Median = 6
Mode = 5 Range = 4
Mean = 8.7 Median = 8
Mode = 6 Range = 11
C
9.5 8 1.5 7
4 16 2 11
D
9 11 5.5 7.2 24.8
7.2 16 8.4 13.5 10.4
Mean = 7.4 Median = 7.5
Mode = No Mode Range = 14.5
Mean = 11.3 Median = 9.7
Mode = 7.2 Range = 19.3
E
−6.6 0.7 8.2 9.9 4.7
4.2 6 −7.8 −13.4
F
58 50 60 52 57
52 57 56 58 50
Mean = 0.7 Median = 4.2
Mode = No Mode Range = 23.3
Mean = 55 Median = 56.5
Mode = No Mode Range = 10
(1dp)