I'm doing some kmeans clustering:

**Regardless of how many clusters I choose to use, the percentage of point variability does not change:**

Here's how I am plotting my data:

```
# Prepare Data
mydata <- read.csv("~/student-mat.csv", sep=";")
# Let's only grab the numeric columns
mydata <- mydata[,c("age","Medu","Fedu","traveltime","studytime","failures","fam
mydata <- na.omit(mydata) # listwise deletion of missing
mydata <- scale(mydata) # standardize variables ibrary(ggplot2)
# K-Means Clustering with 5 clusters
fit <- kmeans(mydata, 5) #to change number of clusters, I change the "5"
# Cluster Plot against 1st 2 principal components
# vary parameters for most readable graph
library(cluster)
clusplot(mydata, fit$cluster, color=TRUE, shade=TRUE,
labels=0, lines=0)
```

**How do we affect the percentage of point variability?**