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For EACH QUESTION:

In your group, discuss to surface what is/ are the feature(s) in the graph that is/ are misleading.

Use the “scaffolds” to answer the question.

Each person will put up one post.

It could be different from your member’s as there maybe more than one misleading feature.

[1 Point for each correct part]

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Hint: use terms like sector angle, percentage

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Hint: use terms like sector angle, percentage

# data[].attributes.body
Hint: use terms like sector angle, percentage

# data[].attributes.body
Hint: use terms like sector angle, percentage

# data[].attributes.body
Hint: use terms like sector angle, percentage

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Hint: use terms like sector angle, percentage

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The starting point can be more than 0, causing the reader to think that starting pooint is more than zero, causing to make the readmin inaccurae

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Starting number is not defined, may led to confusion

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The number may be higher than zero, making the graph seem inconsistent.

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When comparing the improvement between each year, we do not know the difference

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The vertical axis is unmarked for each year

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When comparing the difference in the average daily attendance in 2008 and 2010, we do not know how big the difference is; it could be 5 or 50

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The size of some of the segments of the pie chart is disproportionate

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This leads people who do not read the percentages to think that the amount spent on flights was less than the actual percentage.

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The segment "Flights" says 50% yet it does not take up 50% of the graph.

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The person looking at the graph might think that the average daily attendance might be much smaller than the actual value.

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If the person reading the graph does not see the 900 mark, they might think that in 2002 the average was around 500-600, instead of 900-920

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People who are reading the graph are not able to tell the difference between each graph 

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The necessary parts of the graph on the vertical axis are not labeled for each year which can cause confusion reading the graph

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For example, comparing 2002 to 2008, we cannot tell the difference as there is no labeling on the vertical axis for each year, so we cannot find the difference

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This mistake may lead people to believe that the sectors have less or more % than they actually do

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The sum of sector angles is disproportionate to the percentages listed

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The flight sector states 50% but the sector angle is less than 180 degrees on the pie chart

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1) the word "huge" is subjective and could lead people to think the improvement is bigger than it actually is

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if I read "huge" in the title I would assume that the improvement is by at least 300, when in reality the graph shows that the improvement is by about 100

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Between 2002 and 2010, the years 2005,2006,2007 and 2009 are missing. Thus, people can get mislead by thinking that there is a huge improvement immediately after 2004.

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The years 2005 to 2007 and 2009 are missing.

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The reader can get mislead into thinking that after 2004, 2005, has a large jump.

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People will not be able to compare the actual improvement in attendance. 

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There is no marking and there is no starting point of the y axis.

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For example, when comparing the difference in the average attendance between 2004 and 2008, people will think it is a huge improvement while the actual improvement could have just been 1.

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Although the hotel sector is 25% and 90 degrees, the flight sector is 50%, yet is less than 180 degrees. This may confuse viewers as the flight sector should be double that of the hotel, yet they are not depicted as such.

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the flight sector which is 50%, is not half of the circle (an angle of 180 degrees)

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If I were to study the chart, I might think that flights aren't 50% as it is not 180 degrees. Thus, I would not realise that it is 50% or double that of the hotel.

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The insurance plus the appliances is 17% which is the same size as the Hotels (25%). This makes it seem like they are similar, but they might be very different if the total is big.

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If the total is like 1 million, 25% of it and 17% is vastly different.

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The bottom of the y-axis of the graph is unmarked.

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This means that the bottom of the y-axis may not be zero and therefore be misleading.

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For example, if the bottom of the y-axis is actually 800 and not 0, there will not actually have been a "huge" improvement.

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It may lead people to believe that the start of the vertical axis is not 0

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The starting point of the vertical axis on the graph is absent.

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For example, the start of the vertical axis could be 0 or could also be 700, then the improvement in attendance would not actually be that much

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The space that some of the segmentses take up is disproportianate.

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People may be lead to believe that flights are disproportianate to the actual percentage. Which may result in people thinking that less money was spent on flights than the actual percentage.

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The seize of the flight portion is not proportianate when compared to the percentage

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The segment called flights is 50% but it deos not take up 50% of the space

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the pie chart may make people who do not read the % believe that the values are something incorrect.

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the sections of the pie chart are disproportionate and do not match with the percentages

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the flights are supposed to take up 50% of the total pie chart but it does not. therefore it is disproportionate and unaccurate.

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This may lead people to think that there is an equal number of daily attendance from2004 to 2008

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There is a sudden jump in the years 2004 to 2008

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If people see the sudden jump, they would think there is an equal umber of attendance leading to misinterpretation

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The flights section does not look like 50% of the pie chart.

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The section of the pie chart that is marked "flights" is 50% but does not occupy 50% of the pie chart.

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The "flights" section could mislead someone into thinking that it was 30%.

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some parts of the pie chart is not accurate

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the part of the chart labelled flight is said to be 50%. However, it does not take up 50% of the chart

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It is supposed to be 50% but it does not take up 50% of the chart

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The bar in 2002 and 2003 we do not know what is the value of it as there is no number line telling us the exact value

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50% is supposed to have a sector. angle of 180 degree. The total of Insurance and Appliances look like 25%, a quarter of a circle. However, it is only at 17%.

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The sector angles are not accurate to the percentage.

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People may get confused, thinking that flights is around 35% but not 50%.

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The interval between 2004-2008 and from 2008-2010 is missing

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We don't know how much the increase between the intervals

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from 2004-2008, we dont know how much the daily attendance increased or decreased

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people might not be able to read the graph clearly because of the gaps

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the positioning of each part of the chart is uneven

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I would not be able to read it clearly as the gaps in the pi chart are uneven and the cinemas part is slightly lower than it is meant to be.

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we cannot make a fair comparison as the difference is not clear

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the parts of the vertical axis that is important are not there

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For example, the difference between 2008 and 2004 had a big difference, making people think the daily attendance improve significantly.

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The starting point is missing which can exaggerate the average daily attendance

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The starting point could be 700 or 0, which would cause the ratios of the bar graph to be inaccurate or inconsistent

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People will mistake some of the types of expenditure as they compare it based on size 

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if the total is one thousand, 25 percent of it and 17 percent of it is different

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The piechart is misleading because for flights which consists of 50% of the whole online expenditure does not look like 50%

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The flights which is 50% does not look like half of the pie chart

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Some people may misread the amount of flights as less than 50% as the pie chart looks different

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people may interpret different numbers as the starting point

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the starting point is the vertical axis is absent

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the start of the vertical axis could be any number below 900. which is very misleading and could lead people to getting many different answers

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It is not proportional so it leads to confusion

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Hotels ,insurance, appliances,look lite 50% but insurance and appliances

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if they see that appliances and insurance are 17% totally and do not match

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The bottom of the pi chart is not labled.

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They may assume that the lowest point is 1, or 0. However, it may be much higher

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The bottom of the pi chart is not labled

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The bottom of the pi chart is not labled

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We do not know the average daily attendance between 2004 and 2008 and between 2008 and 2010. Thus, the data may be misleading as people reading the graph may misinterpret the data written in 2008 as from 2005 if they read the graph wrongly.

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The intervals between data collection are not consistent.

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From 2004 to 2008, we don't know how much the daily attendance increased or decreased. 

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The intervals between the data collection is not consistent. The starting point is not present. Title is subjective, may be misleading. The vertical axis is missing data.

# data[].attributes.custom_properties.8jUJDM-4
We do not know the average daily attendance between 2004 and 2008 between 2008 and 2010. Thus, the data may be misleading as people reading the graph may misinterpret the data when written in 2008 as from 2005 if they read the graph wrongly. 

# data[].attributes.custom_properties.RGCxReRY
The intervals between data collection are not consistent.

# data[].attributes.custom_properties.UMO9Srr0
From 2004 and 2008, we don't know how much the daily attendance increased or decreased.

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The title says a huge improvement, but the word huge is subjective and the improvement in attendance doesn't indicate a huge difference.

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I could say my Chinese had a huge improvement, but if my Chinese improved by only 3 marks, the adjective huge is subjective and is misleading.

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the angle sectors are not drawn to scale.

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For example, the expenditure for "Flight" is 50%, but the angle sector is not 180º. Therefore, it is misleading as it does not reflect the true value of the percentage of expenditure used for "Flights".

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We don't know how much the increase between the interval

# data[].attributes.custom_properties.RGCxReRY
Interval between 2004-2008 and from 2008-2010 is missing

# data[].attributes.custom_properties.UMO9Srr0
From 2004-2008, we dont know how much the daily attendance increased or decreased.

# data[].attributes.custom_properties.8jUJDM-4
Some parts of the pie chart are not proportionate to the percentage of the whole. The flight is supposed to be 50% of the whole. However, the part is not half of the whole.

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The flight part of the pie chart is not proportionate

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People readingvthe graph may not interpret the flight part of the pie chart as half of the whole as it is not proportionate.

# data[].attributes.custom_properties.8jUJDM-4
Some parts of the pie chart are not proportionate to the percentage of the whole. The flight is supposed to be 50% of the whole however, the part is not half of the whole. 

# data[].attributes.custom_properties.RGCxReRY
The flight part of the pie chart is not proportionate.

# data[].attributes.custom_properties.UMO9Srr0
People reading the graph may not interpret the flight part of the pie chart as half of the whole as it is not proportionate

# data[].attributes.custom_properties.8jUJDM-4
The piechart is misleading because for flights which consists of 50% of the whole online expenditure does not look like 50%

# data[].attributes.custom_properties.RGCxReRY
The flights which is 50% does no look like half of the pie chart

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Some people may misread the amount of flights as less than 50% of the pie chart looks different

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The amount spent on online expenditures may seem lesser or more then they actually are

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The 50% doesn't actually take up half of the pie chart.  As shown, it is actually 57% with the other half being 42%. This causes the sizes to be inaccurate and inconsistent

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Some parts of the pie chart are not proportional 

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The part of the pie chart that writes "flights'' is supposed to be 50% but it does not take up 50% of the pie chart.

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The segment of the pie chart that writes 50% is not 50% of the pie chart

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Without the starting point, people might think that the attendance rates of the school increased by one third or so in four years

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without the starting point, people would think that the attendance rates of the school increased greatly.