10 out of the 20 biggest mergers ever happened in 1998,1999,2000

I will say one of the first questions I ask people is “what do you want the data to say” because visualization of data can tell whatever story you want it to if the end user isn’t paying attention

I’d actually look at the choice of metric as a key way that data is used to mislead, eg reporting on transactions per hour rather than transactions per staff member, which takes no account of shift patterns, number of staff, etc.

There are scammers who manipulates axis representations and data selections, then there are honest man who’s using “T” as standard errors bar and tell you the data is just made up.

Fuckin vodafone? The sim company?

"never attribute to Halon that which is adequately explained by a careless typo"

It's curious that so many on this list are just around the turn of the millennium. Do we have stricter anti-monopolies laws now or big companies don't buy each other out as often?

My only takeaway from studying 1st year statistics at university was that I can confidently not believe any statistics that I see anywhere anytime. Statistics has methods of completely re-representing (is that a word?) the data to the literal opposite of reality, if one simply chooses to do so.

Don't disagree with this nuance!

I would rebuttal this point a bit, since eliminating an axis and replacing it with labels directly on the data points can be an example of improving the data-ink ratio of a data viz, which is generally regarded as a positive in the field.

Edit: Obviously eliminating the axis and having 0 labeling is a no no since the values need to be specified.

Spanish state TV data be like

I work for one of the spin-offs from that merger. Very interesting indeed lol

I think you got it backwards. AOL purchased Time-Warner, since they were worth more at the time. But AOL exec’s let them think it was the other way around, since AOL was young and inexperienced. AOL leveraged their high market cap due to the bubble to make a deal.

Source is from The Fifth Wave. Great read if you ever have time!

This color scheme was chosen as its color blind safe. I can toy around with your idea too.

It's usually less about what the starting Y value is as it is about the scaling for the overall data, coupled with a plot point to close to the starting y value.

I mean, people should be able to critically think through this, but if that were the norm, we would probably have flying cars robot slaves better living conditions less bullshit to deal with.

On the second table why is there even a need for a y2 axis on the right table?

usually a secondary axis is better is the units of measure are different between y1 and y2

I was thinking the same thing. Having two y axis scales left and right is only misleading if the two sets of data are displaying the same information for different groups. If they're displaying two different attributes of a system, different axes are often the only way to make the plot useful.

Would be useful to highlight where the difference is - I knew where to look from the titles but someone else might find it confusing. I'd also consider using colors or stronger dividers, something to show the different vertical sections.

The Dow/DuPont merger was an odd one. Had to do a case study on it in college, worth the Google search.

>These are all expressed in percentage points but they have wildly different ranges and magnitudes. It would make no sense to use one single axis for two or more of those.

And importantly, there is the potential for trends to be highlighted by that sort of chart that wouldn't otherwise be visible, and that are accurately reflected in the data (so its not a manipulation).

3 is fine if the period covered is the relevant period, it's not fine if you are trying to display a continuous trend. It could be problematic, or fine if you are showing a point of change where the previous period isn't relevant (so you aren't after a change in trend from a previous period).

It's often true if you want to show the differences between similarly (usually large..) numbers. Whether it is misleading or not tends to be in the presentato and context. The same applies to things like log scales etc...

Here's a great example I just ran into https://www.advisorperspectives.com/images/content_image/data/a3/a310f2c1738037eb2e55deb0b7a54134.png

May I suggest a different color scheme? Light yellow for noon, going to red for the afternoon, purple for evening, dark blue for midnight and then lighter shades of blue for closing to morning, and yellow for early day?

It would be more intuitive.

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