The following data shows the weight in ounces of 10 different bags of candy.
10, 3, 7, 3, 4, 21, 6, 10, 1, 2, 3.

after removing the outlier what does the mean absolute deviation of this data set

a. on average the weight of a bag of candy varies 3.2 ounces from the mean of 4 ounces
b. on average the weight of a bag of candy varies 2.6 ounces from the mean of 5 ounces
c. on average the weight of a bag of candy varies 3.2 ounces from the mean of 5 ounces
d. on average the weight of a bag of candy varies 2.6 ounces from the mean of 4 ounces

C.

Mean= 4.9

Mean Absolute Deviation (MAD): 4.099173553719

Step-by-step explanation:

An outlier is a value that is very different from the other data in your data set. This can skew your results. As you can see, having outliers often has a significant effect on your mean and standard deviation. Because of this, we must take steps to remove outliers from our data sets.

outlier: 21

step-by-step explanation:

let's assume

number of candles set =x

price of of x candles =p(x)

we are given

a candle maker prices one set of scented candles at $10 and sells an average of 200 sets each week

so, we get point as (200,10)

he finds that when he reduces the price by $1, he then sells 50 more candle sets each week

so, we can find slope

now, we can use point slope form of line

now, we can plug values

we can use point

and find b

now, we can plug it back

and we get

now, we can find revenue

we know that

revenue = price*quantity

so, we get