In k-means clustering, k represents the a. number of clusters. b. mean of the cluster. c. number of observations in a cluster. d. number of variables.

The correct answer to the question is;

a. number of clusters.

Step-by-step explanation:

Clustering is the process of looking for smaller similar groups of observation within a set of data.

K-means clustering is a vector quantization method used in data mining cluster analysis. The objective of k-means clustering is to a given number of observations into k number of clusters whereby an observation is grouped in a cluster having the closest mean value, hence being representative of tha particular cluster. This is in atempt to make observations in a particular group to be similar.

In k-means clustering, the number of clusters is specified as k.

in 4 days he will run   12/14

step-by-step explanation:

0.16 or 16%

step-by-step explanation:

lets take a coin for example.

if you toss it twice, it has a 1/4 chance of landing on heads both times because 1/2 * 1/2 is 1/4.

with the cards, the chance of picking dog is 0.4. having two people pick one is like picking a card twice in a row. so 0.4 * 0.4 is 0.16, or 16%