See image attached below ked

.13%

68.26%

2.28%

47.72%

49.87%

34.13%

Step-by-step explanation:

1.) standardize by subtracting the mean and dividng by the standard deviation

(625-1000)/125= -3

go to a ztable to get .0013 or (1-.9987)

this is equal to .13%

2.)

875<x<1125

standardize both seperately and subtract them

(875-1000)/125= -1  whose probability is .1587 (or 1-.8413)

(1125-1000)/125= 1  whose probability is .8413

.8413-.1587= 68.26%

3.)

Find the probability that someone paid less than 1250 and take its compliment

(1250-1000)/125= 2 which has a probability of .9772

take its compliment (1-.9772)= .0228= 2.28%

4.)

Same process as question 2

(750-1000)/125= -2 which has a probability of (1-.9772) = .0228

(1000-1000)/125= 0 which has a probability of .5

.5-.0228= .4772= 47.72%

5.) same deal as the previous question

(625-1000)/125= -3 which has a probability of (1-.9987)= .0013

(1000-1000)/125= 0 which has a probability of .5

.5-.0013= .4987= 49.87%

6.)same deal the previous question

(875-1000)/125= -1 which has a probability of (1-.8413)=.1587

(1000-1000)/125= 0 which has a probability of .5

.5-.1587= .3413= 34.13%

the answer is 2/54

step-by-step explanation:

whole number data type

step-by-step explanation:

as whole number type represents whole number

like 1, 2 ,3, 4

in other words the whole numbers are those numbers which cannot be written infraction.

since we can take days as a whole number i.e 1 day 2 day and we cannot write 1.2 day hence we will use whole number data type