Assume that the readings on the thermometers are normally distributed with a mean of 0 degrees and standard deviation of 1.00degreesC. Assume 3.3% of the thermometers are rejected because they have readings that are too high and another 3.3% are rejected because they have readings that are too low. Draw a sketch and find the two readings that are cutoff values separating the rejected thermometers from the others.

Step-by-step explanation:

Hello!

The variable of interest is the readings on thermometers. This variable is normally distributed with mean μ= 0 degrees C and standard deviation σ= 1.00 degrees C.

The objective is to find the readings that are in the top 3.3% of the distribution and the lowest 3.3% of the distribution.

Symbolically:

The lower value P(X≤a)=0.033

Top value P(X≥b)=0.033

(see attachment)

Lower value:

The accumulated probability until "a" is 0.03, since the variable has a normal distribution, to reach the value of temperature that has the lowest 3.3%, you have to work under the standard normal distribution.

First we look the Z value corresponding to 0.033 of probability:

Z= -1.838

Now you reverste the standardization using the formula Z= (a-μ)/δ

a= (Z*δ)+μ

a= (-1.838*1)+0

a= -1.838

Top value:

P(X≥b)=0.033

This value has 0.033 of the distribution above it then 1 - 0.033= 0.967

is below it.

You can rewrite the expression as:

P(X≤b)=0.967

Now you have to look the value of Z that corresponds to 0.967 of accumulated probability:

b= (Z*δ)+μ

b= (1.838*1)+0

b= 1.838

The cutoff values that separates rejected thermometers from the others are -1.838 and 1.838 degrees C.

I hope it helps!

9.55 degrees.

step-by-step explanation:

the given angle is

1 cycle is equal to 2π radians. so 4π will be equal to two cycles.

5.166667π-4π = 1.166667π

hence, this angle goes a little more than negative x axis.

1.166667π-π= 0.166667π

hence, the reference angle is 0.166667π radians.

1 radian = 57.2958 degrees

now, in degrees, this should be equals to 9.55 degrees.

1/3 + 1/5 = 8/15.

step-by-step explanation:

hope it