Jasper is using the following data samples to make a claim about the house values in his neighborhood: house value a $150,000 b $175,000 c $200,000 d $167,000 e $2,500,000 based on the data, should jasper use the mean or the median to make an inference about the house values in his neighborhood?

Jasper should use the the median because it is in the center of the data.

Step-by-step explanation:

We have been given that Jasper is using the following data samples to make a claim about the house values in his neighborhood:

HouseValue

A             $150,000

B             $175,000

C             $200,000

D             $167,000

E             $2,500,000

We can see that value of house E is far more than other houses, so value of house E is an outlier for our given data.

Since we know that median is the best measure for the center a data set with large or small value outliers as median is less affected by outliers.

Since mean is the average of all the values, so mean of a data set with a large valued outlier will be greater than the center of data set.

Since our data set has an outlier, therefore, Jasper should use median to find the house values in his neighborhood.

85.560%

step-by-step explanation:

conditional probability is defined as:

p(a|b) = p(a∩b) / p(b)

in other words, the probability that a occurs, given that b has occurred = the probability that both a and b occur / the probability that b occurs.

in this example:

p(turns 64 | turns 44) = p(turns 64 & turns 44) / p(turns 44).

if someone turns 64, they must have already turned 44, so:

p(turns 64 | turns 44) = p(turns 64) / p(turns 44)

on page 42, we see that of the original 100,000, 94944 turn 44, and 81234 turn 64.   therefore:

p(turns 64 | turns 44) = 81234 / 94944

p(turns 64 | turns 44) = 0.85560