A data scientist tracked how many cups of coffee she drank every day at work over the course of a year. She used the data to build a probability distribution where the random variable CCC represents the number of cups of coffee she drank on a given day. Here is the distribution:

C=\# \text{ of cups}C=# of cups 000 111 222 333

P(C)P(C)P, left parenthesis, C, right parenthesis 0.050.050, point, 05 0.100.100, point, 10 0.750.750, point, 75 0.100.100, point, 10

Calculate the mean of CCC.

1.9

Step-by-step explanation:

Given the cups of coffee drunk every day over a r]year represented by the probability distribution.

The  mean number of coffee is the expected value of the probability distribution table above.

Expected Value,

Therefore:

E(C)=(0X0.05)+(1X0.10)+(2X0.75)+(3X0.10)

=0+0.10+1.5+0.3

Expected Value=1.9

Therefore, the mean number of coffee sold =1.9

sine

step-by-step explanation:

for this case we have that by definition, the volume of a cylinder is given by:

where:

r: it's the radio

h: it's the height

we have as data that:

substituting:

so, the cylinder volume is

option d