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{{T}}
[[Category:English]]
[[Category:Mean, Median, Mode, and Range]]

{{BR}}
= Introduction =

When you collect data, a long list of values can be difficult to understand. '''Mean''', '''median''', and '''mode''' are measures that help describe the center or a typical value of a data set. The '''range''' is different: it describes spread by showing the distance from the smallest value to the largest value.

In Grades 7–8, these ideas help you summarize survey results, test scores, sports statistics, measurements, prices, and experimental data. More importantly, you learn that different summaries answer different questions. A single number can be useful, but it can also hide important details.

[[File:Comparison mean median mode.svg|500px|frameless|center]]

The diagram above compares the mean, median, and mode in distributions with different shapes. It is a useful reminder that these three measures do not always have the same value.

{{#ev:youtube|https://www.youtube.com/watch?v=e3uY2LraXts|500|center}}

{{BR}}
== Learning Goals ==

By the end of this aiMOOC, you should be able to calculate the mean, median, mode, and range of a numerical data set, explain what each measure tells you, decide which measure is most useful in a given situation, describe how outliers can affect the results, and justify your choice of a statistical summary.

Useful related topics include [[English:Statistics|Statistics]], [[English:Data analysis|Data analysis]], [[English:Arithmetic mean|Arithmetic mean]], [[English:Median|Median]], [[English:Mode (statistics)|Mode]], [[English:Range (statistics)|Range]], [[English:Outlier|Outlier]], [[English:Frequency distribution|Frequency distribution]], and [[English:Box plot|Box plot]].

{{BR}}
= The Four Main Measures =

Consider this data set:

'''4, 6, 6, 7, 9, 12'''

The four measures summarize it in different ways.

{| class="wikitable"
! Measure
! What it describes
! Result for the example
|-
| Mean
| The arithmetic average
| 44 divided by 6, which is about 7.33
|-
| Median
| The middle of the ordered data
| 6.5
|-
| Mode
| The value that occurs most often
| 6
|-
| Range
| The distance from the minimum to the maximum
| 8
|}

{{#ev:youtube|https://www.youtube.com/watch?v=h8EYEJ32oQ8|500|center}}

{{BR}}
== Mean ==

The '''mean''' is found by adding all values and dividing the total by the number of values.

For the data set 4, 6, 6, 7, 9, 12:

'''Sum = 4 + 6 + 6 + 7 + 9 + 12 = 44'''

There are six values, so:

'''Mean = 44 ÷ 6 ≈ 7.33'''

The mean uses every value in the data set. This is one reason it is often useful. It is also why a very large or very small outlier can change the mean noticeably.

A useful way to think about the mean is as a '''fair-share value'''. If the total amount were redistributed equally among all data points, each point would receive the mean.

{{BR}}
=== Mean with Decimals and Negative Numbers ===

The same rule works with decimals and negative numbers. For example, the temperatures −2, 1, 3, 4, and 4 have a sum of 10. Dividing by five gives a mean of 2.

Always keep track of signs, decimal places, and the number of data values. A calculator can help with arithmetic, but you should still understand the method.

{{BR}}
== Median ==

The '''median''' is the middle value after the data has been arranged from least to greatest.

With an odd number of values, the median is the single middle value. For example:

'''2, 5, 7, 9, 14'''

The median is '''7'''.

With an even number of values, there are two middle values. Find their mean. For example:

'''2, 5, 7, 9, 14, 20'''

The two middle values are 7 and 9, so the median is '''8'''.

[[File:Finding the median.png|500px|frameless|center]]

The diagram above illustrates the basic idea of locating the middle of an ordered data set.

{{BR}}
== Mode ==

The '''mode''' is the value that appears most often.

For the data set 4, 6, 6, 7, 9, 12, the mode is '''6''' because 6 occurs twice and every other value occurs once.

A data set can have:
# One mode, when one value occurs more often than all others.
# More than one mode, when two or more values tie for the highest frequency.
# No mode, when no value occurs more often than the others.

Mode is especially useful when the most common choice or category matters. For example, a store may care about the most common shoe size sold even when calculating a mean shoe size would not be meaningful.

{{BR}}
== Range ==

The '''range''' measures spread using only the smallest and largest values.

'''Range = maximum − minimum'''

For 4, 6, 6, 7, 9, 12:

'''Range = 12 − 4 = 8'''

The range is easy to calculate, but it ignores all values except the two endpoints. That means one extreme value can change the range dramatically.

{{#ev:youtube|https://www.youtube.com/watch?v=vp1wqtfGJuk|500|center}}

{{BR}}
= Ordering Data Correctly =

Ordering data is essential for finding the median and helpful for finding the mode and range.

Suppose the original data are:

'''11, 3, 8, 8, 5, 14, 6'''

Ordered from least to greatest:

'''3, 5, 6, 8, 8, 11, 14'''

Now you can see that the median is 8, the mode is 8, and the range is 11. The mean is 55 divided by 7, or about 7.86.

A common mistake is to choose the middle number from an unordered list. The median is based on position only '''after''' sorting.

{{BR}}
= Outliers and Their Effects =

An '''outlier''' is a value that lies unusually far from most other values in a data set.

Start with:

'''4, 6, 6, 7, 9, 12'''

Now replace 12 with 42:

'''4, 6, 6, 7, 9, 42'''

The median remains 6.5 and the mode remains 6, but the mean rises from about 7.33 to about 12.33. The range rises from 8 to 38.

This example shows an important pattern: the '''mean''' and '''range''' can be strongly affected by extreme values, while the '''median''' is often more resistant to them. Whether a value should be called an outlier depends on context and on the method used to identify unusual values.

[[File:Visualisation mode median mean.svg|500px|frameless|center]]

The visual above shows that mean, median, and mode can occupy different positions when a distribution is not symmetric.

{{BR}}
= Choosing the Best Measure =

There is no single measure that is best for every data set. Your choice should depend on the question and the shape of the data.

The '''mean''' is often useful when every value should contribute to the summary and there are no extreme values that distort the result.

The '''median''' is often useful when data are skewed or contain extreme values, such as house prices or waiting times.

The '''mode''' is useful when you want the most frequent value or category, such as the most common shoe size, survey choice, or product type.

The '''range''' is useful for a quick sense of total spread, but it should not be treated as a measure of center.

[[File:Bivariate mean median mode.svg|500px|frameless|center]]

This point-based example shows mean, median, and mode at different locations in an uneven distribution. You do not need the advanced curve details to notice that different definitions of “center” can lead to different answers.

{{BR}}
== Comparing Two Data Sets ==

Suppose two classes each have a mean quiz score of 80.

Class A: '''78, 79, 80, 81, 82'''

Class B: '''60, 70, 80, 90, 100'''

Both have the same mean and median, but their ranges are very different. Class A has a range of 4, while Class B has a range of 40. The example shows why measures of center and spread should often be considered together.

[[File:Boxplot vs PDF.svg|500px|frameless|center]]

The box plot in the image marks the median and gives another visual way to think about the spread of data. At this level, focus on the median line and the idea that graphs can reveal information that a single average cannot.

{{BR}}
= Real-World Applications =

You can use these measures in many settings.

# [[English:Sports statistics|Sports statistics]]: Compare scoring, times, distances, or repeated performances.
# [[English:School survey|School survey]]: Summarize sleep hours, travel times, screen time, or study time.
# [[English:Science experiment|Science experiment]]: Describe repeated measurements and look for unusual results.
# [[English:Business data|Business data]]: Identify common product sizes, typical prices, or variation in sales.
# [[English:Weather data|Weather data]]: Compare daily temperatures and temperature ranges.

When interpreting real data, ask: '''What does this measure hide?''' A mean alone does not show how spread out the values are. A range alone does not show what is typical. A mode may not represent most of the data if the frequencies are close.

{{#ev:youtube|https://www.youtube.com/watch?v=0cHCpgQD_8k|500|center}}

{{BR}}
= Worked Examples =

{{BR}}
== Example: Student Reading Time ==

Five students read for 20, 25, 25, 30, and 40 minutes.

The mean is 140 divided by 5, which is 28 minutes. The median is 25 minutes. The mode is 25 minutes. The range is 20 minutes.

Each result answers a different question. The mean gives an equal-share average, the median gives the middle reading time, the mode gives the most common time, and the range shows the gap between the shortest and longest times.

{{BR}}
== Example: A Strong Outlier ==

Consider the values:

'''5, 6, 6, 7, 8, 50'''

The mean is about 13.67, the median is 6.5, the mode is 6, and the range is 45.

If these values represented the number of minutes students waited for a bus, the median would usually describe a typical wait more clearly than the mean because 50 is far above the other values.

{{BR}}
== Example: No Mode ==

Consider:

'''3, 5, 7, 9, 11'''

Every value occurs once, so there is no mode. The mean and median are both 7, and the range is 8.

Do not invent a mode when every value has the same frequency.

{{BR}}
= Common Errors and How to Avoid Them =

A reliable method is more important than speed.

# [[English:Sorting data|Sorting data]]: Put data in order before finding the median.
# [[English:Counting values|Counting values]]: Count how many values are present before dividing to find the mean.
# [[English:Finding the range|Finding the range]]: Subtract the minimum from the maximum rather than counting how many values are listed.
# [[English:Identifying the mode|Identifying the mode]]: Look for the most frequent value, not the largest value.
# [[English:Interpreting outliers|Interpreting outliers]]: Check whether an extreme value changes the mean or range before deciding which summary is most informative.

{{BR}}
= Interactive Tasks =

{{BR}}
== Quiz: Test Your Knowledge ==

{{MC}}

'''What is the mean of 4, 6, 8, and 10?'''
(7)
(!6)
(!8)
(!28)

{{E}}
<br>

{{MC}}

'''What must you do before finding the median?'''
(Order the data)
(!Add all values)
(!Find the largest value)
(!Count only repeated values)

{{E}}
<br>

{{MC}}

'''What is the median of 3, 5, 7, 9, and 12?'''
(7)
(!5)
(!9)
(!12)

{{E}}
<br>

{{MC}}

'''What is the median of 2, 4, 8, and 10?'''
(6)
(!4)
(!8)
(!24)

{{E}}
<br>

{{MC}}

'''What is the mode of 2, 3, 3, 4, 5, 5, and 5?'''
(5)
(!3)
(!4)
(!22)

{{E}}
<br>

{{MC}}

'''What is the range of 7, 9, 12, and 18?'''
(11)
(!9)
(!18)
(!46)

{{E}}
<br>

{{MC}}

'''Which measure is usually most resistant to one extremely high value?'''
(Median)
(!Mean)
(!Range)
(!Maximum)

{{E}}
<br>

{{MC}}

'''Which measure uses only the smallest and largest values?'''
(Range)
(!Mean)
(!Median)
(!Mode)

{{E}}
<br>

{{MC}}

'''A data set has no repeated values. What can be true about its mode?'''
(It has no mode)
(!Its mode is zero)
(!Its mode is the mean)
(!Its mode is the largest value)

{{E}}
<br>

{{MC}}

'''Two classes have the same mean but very different ranges. What does this show?'''
(Their spreads can differ)
(!Their data sets are identical)
(!Their medians must differ)
(!Their modes must be equal)

{{E}}
<br>

{{BR}}
== Memory Game ==

<div class="memo-quiz">
{|
|-
| Mean || Sum of all values divided by the number of values
|-
| Median || Middle value or middle pair average after ordering
|-
| Mode || Most frequently occurring value
|-
| Range || Maximum value minus minimum value
|-
| Outlier || Value unusually far from most other observations
|-
| Dataset || Collection of values being studied
|}
{{E}}
<br>

{{BR}}
== Drag and Drop ==

<div class="lueckentext-quiz">

{| class="wikitable"
! Match the correct terms.
! Topic
|-
| '''Arithmetic average'''
| Mean
|-
| '''Middle after sorting'''
| Median
|-
| '''Most frequent value'''
| Mode
|-
| '''Maximum minus minimum'''
| Range
|-
| '''Extreme observation'''
| Outlier
|}
{{E}}

<br>
...
<br />

{{BR}}
== Crossword Puzzle ==

<div class="kreuzwort-quiz">
{|
|-
| Average || Which everyday word is often used for the arithmetic mean?
|-
| Median || Which measure is found from the middle of ordered data?
|-
| Mode || Which measure identifies the most frequent value?
|-
| Range || Which measure equals maximum minus minimum?
|-
| Outlier || What do you call a value unusually far from most of the data?
|-
| Dataset || What is a collection of values called?
|}
{{E}}
<br>

{{BR}}
== LearningApps ==

<iframe> https://learningapps.org/index.php?s=Mean+Median+Mode+and+Range </iframe>

{{BR}}
== Cloze Text ==

<quiz display=simple>
{'''Complete the text.'''<br>
|type="{}"}
The { mean } is calculated by adding all data values and dividing by the number of values. The { median } is found by ordering the data and locating the middle. The { mode } is the value that occurs most often. The { range } is calculated by subtracting the minimum from the maximum. A very extreme value may be called an { outlier }. An outlier can strongly change the { mean } because every value contributes to that calculation. The median is often more { resistant } to extreme values. Measures of center and { spread } can work together to describe a data set more completely.
</quiz>

<br>

{{BR}}
= Open-Ended Tasks =

{{BR}}
=== Easy ===
# [[English:Classroom Data Hunt|Classroom Data Hunt]]: Collect one simple numerical data set with at least eight values from your classroom or home, calculate all four measures, and explain what each one means.
# [[English:Statistics Poster|Statistics Poster]]: Create a one-page poster that teaches mean, median, mode, and range using your own example data and clear visual cues.
# [[English:Human Number Line|Human Number Line]]: Give classmates data-value cards, arrange yourselves from least to greatest, and demonstrate how the median is found for odd and even group sizes.
# [[English:Mini Survey|Mini Survey]]: Ask at least ten people one numerical question such as daily reading minutes, then summarize the responses with mean, median, mode, and range.

{{BR}}
=== Standard ===
# [[English:Outlier Experiment|Outlier Experiment]]: Start with a data set of at least six values, add one extreme value, recalculate all four measures, and explain which measures changed most.
# [[English:Sports Data Study|Sports Data Study]]: Choose a player or team, collect a small set of numerical performance data from a reliable source, calculate relevant measures, and decide which summary is most informative.
# [[English:Data Story Video|Data Story Video]]: Produce a short video in which you explain one data set, show your calculations, and justify which measure best represents a typical value.
# [[English:Compare Two Groups|Compare Two Groups]]: Collect the same type of data from two groups, compare their centers and ranges, and write a conclusion that goes beyond simply naming the larger mean.

{{BR}}
=== Advanced ===
# [[English:Misleading Average Investigation|Misleading Average Investigation]]: Find or invent a realistic example in which reporting only the mean could mislead an audience, then rewrite the claim using a more responsible statistical summary.
# [[English:Statistical Interview|Statistical Interview]]: Interview a coach, teacher, shop worker, researcher, or other person who uses data, and ask how they decide which averages or measures of spread to report.
# [[English:Data Display Project|Data Display Project]]: Create a dot plot or box plot for a data set, label key features, and explain how the visual display supports or challenges the mean, median, mode, and range.
# [[English:Research and Recommendation|Research and Recommendation]]: Investigate a real decision such as choosing a typical travel time or product size, analyze relevant data, and make a recommendation supported by at least two statistical measures.

{{:Open Task - Create a MOOC}}

{{BR}}
= Learning Assessment =

# [[English:Explain a Choice|Explain a Choice]]: Given a data set with one extreme value, calculate the mean and median and argue which one better represents a typical value in context.
# [[English:Compare Center and Spread|Compare Center and Spread]]: Analyze two data sets that have the same mean but different ranges and explain what the equal means do not reveal.
# [[English:Detect an Error|Detect an Error]]: Review a worked solution containing one incorrect step in finding mean, median, mode, or range, identify the error, and correct the reasoning.
# [[English:Create a Counterexample|Create a Counterexample]]: Construct two different data sets with the same median but different means and ranges, then explain how you know they meet the conditions.
# [[English:Interpret Real Data|Interpret Real Data]]: Use a small real-world data set to calculate at least three measures, identify any unusual values, and write a conclusion appropriate for the context.
# [[English:Transfer to a New Context|Transfer to a New Context]]: Explain how a school principal, sports coach, or shop manager could make a poor decision by using only one summary statistic, and recommend a better approach.

<br>
<br>

{{BR}}
= Evidence of Learning =

Strong evidence of learning includes accurate calculations, correctly ordered data, clear explanations of what each measure represents, and sensible choices about which measure to use.

You should be able to show:
# '''Knowledge''': Definitions and procedures for mean, median, mode, range, and outliers.
# '''Skills''': Sorting data, calculating summaries, checking arithmetic, comparing data sets, and interpreting results in context.
# '''Products''': Completed data tables, posters, graphs, survey reports, videos, or investigations that communicate statistical reasoning.
# '''Reasoning''': Explanations of why the mean, median, mode, or range is more useful for a particular question.
# '''Transfer''': Ability to apply these ideas to unfamiliar data from school, science, sports, business, media, or everyday life.

<br>
<br>

{{BR}}
= OERs on the Topic =

The following English Wikipedia pages provide further background on the main ideas.

<iframe> https://en.m.wikipedia.org/wiki/Arithmetic_mean </iframe>

<iframe> https://en.m.wikipedia.org/wiki/Median </iframe>

<iframe> https://en.m.wikipedia.org/wiki/Mode_(statistics) </iframe>

<iframe> https://en.m.wikipedia.org/wiki/Range_(statistics) </iframe>

<br>

{{BR}}
= Linked Learning Areas =

{| align=center
{{:D-Tab}}
'''[[English:Mean, Median, Mode, and Range|Mean, Median, Mode, and Range]]'''
# [[English:Arithmetic mean|Arithmetic mean]]
# [[English:Median|Median]]
# [[English:Mode (statistics)|Mode]]
# [[English:Range (statistics)|Range]]
# [[English:Statistics|Statistics]]
# [[English:Data analysis|Data analysis]]
# [[English:Outlier|Outlier]]
# [[English:Frequency distribution|Frequency distribution]]
# [[English:Box plot|Box plot]]
|}

These topics connect to [[English:Mathematics|Mathematics]], [[English:Statistics|Statistics]], [[English:Data visualization|Data visualization]], [[English:Probability|Probability]], [[English:Science|Science]], [[English:Business education|Business education]], [[English:Sports science|Sports science]], and [[English:Digital literacy|Digital literacy]]. They also prepare you for later work with quartiles, interquartile range, variance, standard deviation, and more advanced statistical reasoning.

{{BR}}
= aiMOOC Projects =
[[Category:English]]
[[Category:Mean, Median, Mode, and Range]]
[[Category:Mathematics]]
[[Category:Statistics]]
[[Category:Data analysis]]
[[Category:Grades 7-8]]
[[Category:AI_MOOC]]
[[Category:GPT aiMOOC]]
{{MT}}

English:Mean, Median, Mode, and Range - Versionsgeschichte

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