Descriptive Epidemiology

Distribution of weight

The distribution of weight appears skewed to the left.

ggplot(data = linelist_clean, mapping = aes(x = wt_kg)) + geom_histogram(binwidth = 5, fill = "skyblue", color = "black") + labs(title = "Distribution of weight")
## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_bin()`).

## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_boxplot()`).

The box plot shows a longer tail on the left confirming that the distribution is skewed to the left

ggplot(data = linelist_clean, mapping = aes(x = wt_kg)) + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_bin()`).

ggplot(data = linelist_clean, mapping = aes(x = age)) + geom_histogram(binwidth = 5, fill = "skyblue", color = "black") + labs(title = "Distribution of age")
## Warning: Removed 107 rows containing non-finite outside the scale range
## (`stat_bin()`).

## Distribution of age

The distribution of age appears skewed to the right

Th box plot for age has a longer tail on the right

ggplot(data = linelist_clean, mapping = aes(x = age)) + geom_boxplot() + labs(title = "Distribution of age")
## Warning: Removed 107 rows containing non-finite outside the scale range
## (`stat_boxplot()`).

ggplot(data = linelist_clean, mapping = aes(x = wt_kg, y = ht_cm)) + geom_point() + labs(title = "Relationship betweem height and weight")
## Warning: Removed 7 rows containing missing values or values outside the scale range
## (`geom_point()`).

## Relationship between height and weight

This shows a positive correlation between weight and height

Relationship between age and weight

The relationship between weight and age also shows a positive correlation

ggplot(data = linelist_clean, mapping = aes(x = age, y = wt_kg)) + geom_point() + labs(title = "Relationship between age and weight")
## Warning: Removed 107 rows containing missing values or values outside the scale range
## (`geom_point()`).

linelist_clean %>% count(gender)
ggplot(data = linelist_clean, mapping = aes(x = gender)) + geom_bar() + labs(title = "Count gender")