WIP: Abstract type for summary statistics (Mean)

[nadiaenh]

Resolves #275, #184, #274 Partial implementation of @smishr's confidence interval function Implemented Mean structure as an abstract SummaryStat

Remaining to do on this PR :

• [ ] Implement "t" and "margin" confidence intervals
• [ ] Add more attributes to Mean structure (standard error of estimate, ...)
• [ ] Add support for ReplicateDesign
• [ ] Write test/SummaryStats.jl
• [ ] Make sure documentation is in order
• [ ] Delete mean.jl once all functionality is implemented in Mean struct ?

Can implement Total, Quantile, and Ratio later

[ayushpatnaikgit]

Have you considered how this would work with domain estimation? Where we have mean(:variable, :domain, design)?

[ayushpatnaikgit]

Overall, I think it's a good idea to be able to do ans.estimate, ans.CI and ans.SE. Need to think through the implementation.

It will need a few show methods to make it beautiful.

[ayushpatnaikgit]

I suggest having

struct Estimate
   value::Number
   SE::Number
end

Instead of SummaryStat and Mean

mean, quantile and total can be factory functions for the structure.

For domain estimation, we'll need a separate struct perhaps

struct DomainEstimates
   values::Vector{Number}
   SE::Vector{Number}
end

After this, we can have a function confint(x::Estimate).

[smishr]

struct Estimate
    value::Number
    SE::Number
end

How does this broadcast to estimates which are vectors?

[asinghvi17]

Any reason not to use https://github.com/JuliaPhysics/Measurements.jl here? It's fundamentally the same data structure but probably supported more widely across the ecosystem. In this case a vector estimate would be a vector of Measurements.

[codecov-commenter]

Codecov Report

Merging #277 (bc220b2) into next_release (e9362f9) will decrease coverage by 4.48%. The diff coverage is 0.00%.

@@               Coverage Diff                @@
##           next_release     #277      +/-   ##
================================================
- Coverage        100.00%   95.52%   -4.48%     
================================================
  Files                12       14       +2     
  Lines               200      268      +68     
================================================
+ Hits                200      256      +56     
- Misses                0       12      +12     

Impacted Files	Coverage Δ
src/SummaryStats.jl	0.00% <0.00%> (ø)

... and 3 files with indirect coverage changes

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[smishr]

Any reason not to use https://github.com/JuliaPhysics/Measurements.jl here? It's fundamentally the same data structure but probably supported more widely across the ecosystem. In this case a vector estimate would be a vector of Measurements.

Ayush and I looked at the Measurements.jl package, we see where you are coming from. Except for the pretty printing of uncertainty, their class would not be useful for other aspects of Survey.jl. But some ideas can be adapted from them