Submitted by Hailifiknow t3_102je59 in dataisbeautiful
Comments
st4n13l t1_j2u4w3g wrote
>So, is it all a hyped way to look into “granular” data? Why is McKinsey focusing on something so obvious?
Obvious? Most reporting on life expectancy is done by country, so while it may be obvious to you, McKinsey is pointing out why it's important to account for variations at the microregion level and not just generalize at the country level.
Hailifiknow OP t1_j2u7c79 wrote
Right. It just seems obvious to me. Shouldn’t all studies and reports reflect per capita relativity and not mere national boundaries or landmass? Who does that? I guess you’re saying a lot of studies do. I’m just not sure why McKinsey is stating something so fundamental as illuminating considering it’s readership. The graphs even try to illustrate this in blindingly simply ways. I just wandered if I’m misunderstanding, if they’re creating click-bait, or if most people really do get this wrong and it’s worth clarifying. You’d suggest the latter it sounds like. It’s just interesting.
st4n13l t1_j2u8mf3 wrote
I don't think it's click-bait. I haven't seen clickbaity stuff from them before. Plenty of stuff that I thought others realized, but it's important not to assume that our understanding is what everyone else's understanding or level of knowledge is.
Hailifiknow OP t1_j2uazgg wrote
Good point
jubilant-barter t1_j2ya5wh wrote
If you're doing science, you can't rely on "obvious" to be your answer.
You still need to test your assumptions. Sometimes common sense is just wrong. Besides, some of this may simply be the fact that granular data wasn't available before.
New techniques, broader availability of mobile devices and internet connectivity, it could be that the ability to break down granular data simply wasn't possible in a lot of countries.
And even further, what are the patterns which we can learn help people live longer, better lives? Is the divide exclusively rural vs urban or are there other considerations.
eric5014 t1_j2u9ogi wrote
No surprise that using more detailed data shows gives you a better picture.
I've often heard people say what one city is like compared to another (within Australia, which is relatively uniform). I have tended to believe that the difference within a large city is FAR more than the difference between them, and statements about their differences probably reflect what areas or circles of people they observed in the different cities.
Ulyks t1_j2w5k8x wrote
No not misleading at all.
My only gripe is them not labeling their data points with a mouse hover.
It would be interesting to see the names of the micro regions by hoovering the mouse over the dots, especially the ones near the bottom or top.
Also, they should have included the complete dataset table and where they got their data from. Unfortunately almost no articles do this, it seems they guard their data and sources like a hoard of gold.
Hailifiknow OP t1_j2ti0sd wrote
This study by McKinsey Institute seems very misleading. Email headline: “How much does the country you live in affect life expectancy? Not as much as you think.” Goes on in the email: “Microregions matter more In Cambodia, the national average life expectancy was 69.8 years in 2019. But in some microregions along the coast and around the country’s largest cities, life expectancy is 74.6 years—while it dips as low as 61.4 years in rural areas (where 80 percent of the population lives). Find out some possible reasons why in Pixels make the picture: A guided tour through the granular world, Chapter 1 of Pixels of Progress from the McKinsey Global Institute.”
So, is it all a hyped way to look into “granular” data? Why is McKinsey focusing on something so obvious? Click-bait?