If Susie is late for school one particular day of the week, the probability she arrives on time the next day is 0.8. If she arrives on time one day, the probability she arrives late the following day is 0.3. Susie was on time on Monday. What is the probability she was late on Thursday

0.273 = 27.3% probability that she was late on Thursday.

Step-by-step explanation:

On time on Monday, late on Thursday:

Possible outcomes (tuesday-wednesday-thursday).

on time(0.7 probability) - on time(0.7 probability) - late(0.3 probability)

on time(0.7 probability) - late(0.3 probability) - late(0.2 probability)

late(0.3 probability) - on time(0.8 probability) - late(0.3 probability)

late(0.3 probability) - late(0.2 probability) - late(0.2 probability).

What is the probability she was late on Thursday?

Sum of these four outcomes. So

0.273 = 27.3% probability that she was late on Thursday.

answer: i cant see the picture

step-by-step explanation:

can u take a better picture

d. 24+-0.114

step-by-step explanation:

the question requires us to calculate the approximate 95% confidence interval for the mean number of ounces of ketchup per bottle in the sample given the following statistics;

sample mean = 24

standard deviation, σ = 0.4

sample size , n = 49

the confidence interval for a population mean is calculated using the formula;

sample mean ± z-score*(σ/sqrt(n))

the z-score associated with a 95% confidence interval, from the standard normal tables, is;

1.96

substituting these values into the formula;

24 ± 1.96*(0.4/7)

= 24 ± 0.112

from the alternatives given, choice d is closest to the above expression;