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Assignment 2 Q 1.3 #14

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almas2019 opened this issue Sep 21, 2019 · 3 comments
Closed

Assignment 2 Q 1.3 #14

almas2019 opened this issue Sep 21, 2019 · 3 comments

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@almas2019
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almas2019 commented Sep 21, 2019

I am a bit confused regarding the instructions for this question:
Filter gapminder to all entries that have experienced a drop in life expectancy. Be sure to include a new variable that’s the increase in life expectancy in your tibble. Hint: you might find the lag() or diff() functions useful.
This seems a bit contradictory.

Does this mean filter out countries that have a drop in life expectancies over all the years or only keep those have experienced a drop?
Is it the whole gapminder dataset and not the filtered one from 1.1? Also are we looking at the general trend over all the years , or just the 1970s?
Thank you in advance.

@armetcal
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Did you mean to close the question? I was wondering something similar. I know we're supposed to use the gapminder dataset, but I'm specifically wondering whether we're supposed to analyze:

  • Any lines in the data that have a reduced life expectancy from the previous line
  • Any countries that have experienced a drop in life expectancy overall
  • Any rows where the country has experienced a drop in life expectancy from year to year (AKA doesn't count lines where we're changing countries)

@almas2019
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almas2019 commented Sep 21, 2019

Oh I posted it here : STAT545-UBC/Discussion#553, I'd appreciate it if you add your comment there as well

@armetcal
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Ah okay, sure!

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