Answer:
They would meet each other at
PM.
Step-by-step explanation:
- Erik took a trip to see his friend Mike who lives 308 miles away.
- He left his place at 10 AM driving at 70 mph.
- In 2 hours, his friend Mike left his place driving towards Erik at an average speed of 50 mph.
As Erik left his house at 10 AM driving at 70 mph and in 2 hours, his friend Mike left his place driving towards Erik at an average speed of 50 mph. It means
Erik left his place at 12:00 PM noon.
so, at 12:00 PM Erik had already traveled:

Miles left 
Let 't' be the time when they meet
so





so
or
hour and
minutes after
noon
i.e.

Therefore, they would meet each other at
PM.
Supposing a normal distribution, we find that:
The diameter of the smallest tree that is an outlier is of 16.36 inches.
--------------------------------
We suppose that tree diameters are normally distributed with <u>mean 8.8 inches and standard deviation 2.8 inches.</u>
<u />
In a normal distribution with mean
and standard deviation
, the z-score of a measure X is given by:
- The Z-score measures how many standard deviations the measure is from the mean.
- After finding the z-score, we look at the z-score table and find the p-value associated with this z-score, which is the percentile of X.<u>
</u>
<u />
In this problem:
- Mean of 8.8 inches, thus
. - Standard deviation of 2.8 inches, thus
.
<u />
The interquartile range(IQR) is the difference between the 75th and the 25th percentile.
<u />
25th percentile:
- X when Z has a p-value of 0.25, so X when Z = -0.675.




75th percentile:
- X when Z has a p-value of 0.75, so X when Z = 0.675.




The IQR is:

What is the diameter, in inches, of the smallest tree that is an outlier?
- The diameter is <u>1.5IQR above the 75th percentile</u>, thus:

The diameter of the smallest tree that is an outlier is of 16.36 inches.
<u />
A similar problem is given at brainly.com/question/15683591
The answer is 7/8 find a common denominator or cross multiply
The experiment with the least number of trials.
Experimental probability is more accurate and more close to theoretical probability by having the most trials. More trials = more accuracy. Less trials = less accuracy.