Merge pull request #15 from iuliadmtru/iuliadmtru/docimprove

Add minor rephrasing to README

README.md

@@ -7,30 +7,30 @@
 [![Milestones](https://img.shields.io/badge/-milestones-brightgreen)](https://github.com/xKDR/Survey.jl/milestones)
 
 
-This package is used to study stratified survey data. It is the Julia implementation of the [Survey package in R](https://cran.r-project.org/web/packages/survey/index.html) developed by [Professor Thomas Lumley](https://www.stat.auckland.ac.nz/people/tlum005). 
+This package is used to study complex survey data. It is the Julia implementation of the [Survey package in R](https://cran.r-project.org/web/packages/survey/index.html) developed by [Professor Thomas Lumley](https://www.stat.auckland.ac.nz/people/tlum005).
 
-As the size of survey datasets have become larger, processing the records can take hours or days in R. We endeavour to solve this problem by implementing the Survey package in Julia.  
+As the size of survey datasets have become larger, processing the records can take hours or days in R. We endeavour to solve this problem by implementing the Survey package in Julia.
 
 ## How to install
 
     add "https://github.com/xKDR/Survey.jl.git"
 
 ## Basic usage
 
-In the following example, we will load the Academic Performance Index dataset for Californian schools and produce the weighted mean for each county.  
+In the following example, we will load the Academic Performance Index dataset for Californian schools and produce the weighted mean for each county.
 ```julia
 using Survey
 
 data(api)
 ## This function loads a commonly used dataset, Academic Performance Index (API), as an example.
-## Any DataFrame object can be used with this package. 
+## Any DataFrame object can be used with this package.
 
 dclus1 = svydesign(id = :1, weights = :pw, data = apiclus1)
 
 svyby(:api00, :cname, dclus1, svymean)
 11×3 DataFrame
- Row │ cname        mean     SE       
-     │ String15     Float64  Float64  
+ Row │ cname        mean     SE
+     │ String15     Float64  Float64
 ─────┼────────────────────────────────
    1 │ Alameda      669.0    16.2135
    2 │ Fresno       472.0     9.85278
@@ -45,10 +45,10 @@ svyby(:api00, :cname, dclus1, svymean)
   11 │ Santa Clara  732.077  12.2291
 ```
 
-This example is from the Survey package in R. The [examples section of the documentation](https://xkdr.github.io/Survey.jl/dev/examples/) shows the R and the Julia code side by side for this and a few other examples. 
+This example is from the Survey package in R. The [examples section of the documentation](https://xkdr.github.io/Survey.jl/dev/examples/) shows the R and the Julia code side by side for this and a few other examples.
 
 ## Performance
-We will measure the performance of the R and Julia for example shown above. 
+We will measure the performance of the R and Julia for the example shown above.
 
 **R**
 
@@ -69,7 +69,7 @@ microbenchmark(svyby(~api00, by = ~cname, design = dclus1, svymean), units = "us
 
 **Julia**
 ```julia
-using Survey, BenchmarkTools      
+using Survey, BenchmarkTools
 data(api)
 dclus1 = svydesign(id=:1, weights=:pw, data = apiclus1)
 @benchmark svyby(:api00, :cname, dclus1, svymean)
@@ -82,9 +82,9 @@ BenchmarkTools.Trial: 10000 samples with 1 evaluation.
  Time  (mean ± σ):   81.833 μs ± 190.657 μs  ┊ GC (mean ± σ):  7.62% ±  3.23%
  ```
 
-The julia code is about 171 times faster than R. 
+The Julia code is about 171 times faster than the R code.
 
-We increase the complexity to grouby two variables and then perform the same operations.
+We increase the complexity by grouping the data by two variables and then performing the same operations.
 **R**
 
 ```R
@@ -105,7 +105,7 @@ Unit: microseconds
 
 **Julia**
 ```julia
-using Survey, BenchmarkTools      
+using Survey, BenchmarkTools
 data(api)
 dclus1 = svydesign(id=:1, weights=:pw, data = apiclus1)
 @benchmark svyby(:api00, [:cname, :meals], dclus1, svymean)
@@ -118,14 +118,14 @@ BenchmarkTools.Trial: 10000 samples with 1 evaluation.
  Time  (mean ± σ):   325.100 μs ± 513.020 μs  ┊ GC (mean ± σ):  14.23% ±  8.58%
  ```
 
-The julia code is about 605 times faster than R. 
+The Julia code is about 605 times faster than the R code.
 
 ## Strategic goals
 
 We want to implement all the features provided by the [Survey package in R](https://cran.r-project.org/web/packages/survey/index.html)
 
-The [milestones](https://github.com/xKDR/Survey.jl/milestones) sections of the repository contains a list of features that contributors can implement in the short-term. 
+The [milestones](https://github.com/xKDR/Survey.jl/milestones) sections of the repository contains a list of features that contributors can implement in the short-term.
 
 ## Support
 
-We gratefully acknowledge the JuliaLab at MIT for financial support for this project.
+We gratefully acknowledge the JuliaLab at MIT for financial support for this project.