Week 7: Apply it to your data 6

Import data

myData <- read_xlsx("../00_data/myData.xlsx")

Introduction

Questions

Variation

Visualizing distributions

ggplot(data = myData) + 
    geom_bar(mapping = aes(x = condition))

myData %>% count(condition)

## # A tibble: 6 × 2
##   condition                               n
##   <chr>                               <int>
## 1 Cataract surgery outcome               56
## 2 Colonoscopy care                       56
## 3 Electronic Clinical Quality Measure    56
## 4 Emergency Department                  672
## 5 Healthcare Personnel Vaccination      112
## 6 Sepsis Care                           280

ggplot(data = myData, mapping = aes(x = Column1, colour = score)) +
    geom_freqpoly()

## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.

ggplot(data = myData) + 
    geom_histogram(mapping = aes(x = Column1))

## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.

Typical values

Unusual values

Missing Values

Covariation

A categorical and continuous variable

Two categorical variables

Two continous variables

Patterns and models