Answer:
.
Step-by-step explanation:
Probability that the car encounters a green light on the first day:
.
To meet the question's conditions, the car needs to encounter another green light on the second day. Given that the colors of the light on each day are "independent," the chance that there's a green light followed by another green light will be
.
- Condition is met on the first two days and green light on the third day:
. - Condition is met on the first three days and green light on the fourth day:
.
To meet the condition on the fifth day, there needs to be a yellow light. The probability that the condition is met on the first four days and on the fifth day will be
.
To meet the condition on the sixth day, all prior days should meet the conditions. Besides, there needs to be a red light on the sixth day. 
- Seventh day:

- Eighth day:
- Ninth day:
- Tenth day:
The question asks that the condition be met on all ten days. As a result, the probability of meeting the condition will be equal to the probability on the tenth day:
.
You've got 3 values there.
Get the sum of 65, 30 and 25 and divide their sum by the number of values that exist, which in this case is 3.

Answer:
40
Answer:
The probability that the sample mean would differ from the population mean by more than 2.6 mm is 0.0043.
Step-by-step explanation:
According to the Central Limit Theorem if we have a population with mean μ and standard deviation σ and appropriately huge random samples (n > 30) are selected from the population with replacement, then the distribution of the sample means will be approximately normally distributed.
Then, the mean of the distribution of sample mean is given by,

And the standard deviation of the distribution of sample mean is given by,

The information provided is:
<em>μ</em> = 144 mm
<em>σ</em> = 7 mm
<em>n</em> = 50.
Since <em>n</em> = 50 > 30, the Central limit theorem can be applied to approximate the sampling distribution of sample mean.

Compute the probability that the sample mean would differ from the population mean by more than 2.6 mm as follows:


*Use a <em>z</em>-table for the probability.
Thus, the probability that the sample mean would differ from the population mean by more than 2.6 mm is 0.0043.
Answer:
25 inches
Step-by-step explanation:
To find the difference you need to substract one from another
110-85=25 inches