Answer:
A) Sheri has the faster commute by 6.2 miles/hr.
Step-by-step explanation:
Given
John's commute to work
Sheri's commute to work

John's commute to work in miles per hour = 
Sheri's commute to work in miles per hour =
We can see that Sheri has a faster commute.
Difference between the rates =
∴ Sheri has the faster commute by 6.2 miles/hr.
The correct answer would be choice A: 1.
When 3 coins are flipped, there are 8 possible outcomes.
0 Tails = 1 ways
1 Tails = 3 ways
2 Tails = 3 ways
3 Tails = 1 ways
If you add up all the different tails, you could get 12 tails. Divide 12 by 8 and you have 1.5 which is the average number of tails you could expect to get by flipping 3 coins.
Answer:
0.0003W/cm°C
Step-by-step explanation:
The question is not properly written. Here is the correct question.
The batting wang xiu ying uses to fill quilts has a thermal conductivity rate of 0.03 watts (W) per meter(m) per degree celsius. what is the batting thermal conductivity when w/cm•c
Given the thermal conductivity in W/m°C to be 0.03W/m°C
We are to rewrite the value in W/cm°C
The difference is the unit. The only thing we need to do is to simply convert the unit (metres) in W/m°C to centimeters (cm)
Since 100cm = 1m, 0.03W/m°C can be expressed as shown below;
= 0.03W/m°C
= 0.03 × W/1m×°C
Note that 1m = 100cm, substituting this conversion into the expression, it will become;
= 0.03 × W/100cm × °C
= 0.03/100 × W/cm°C
= 0.0003W/cm°C
Hence the battling thermal conductivity in W/cm°C is 0.0003W/cm°C
Answer:
$2.64
Step-by-step explanation:
Selling them at 5 cents each ($0.05), he could sell 1 dozen buttons for
12 * $0.05 = $0.60
As he bought them at $0.38 per dozen, the profit per dozen would be
$0.60 - $0.38 = $0.22
As 12 dozen is 1 gross, the profit per gross would be
12 * $0.22 = $2.64
Answer:
The probability of getting a sample with 80% satisfied customers or less is 0.0125.
Step-by-step explanation:
We are given that the results of 1000 simulations, each simulating a sample of 80 customers, assuming there are 90 percent satisfied customers.
Let
= <u><em>sample proportion of satisfied customers</em></u>
The z-score probability distribution for the sample proportion is given by;
Z =
~ N(0,1)
where, p = population proportion of satisfied customers = 90%
n = sample of customers = 80
Now, the probability of getting a sample with 80% satisfied customers or less is given by = P(
80%)
P(
80%) = P(
) = P(Z
-2.24) = 1 - P(Z < 2.24)
= 1 - 0.9875 = <u>0.0125</u>
The above probability is calculated by looking at the value of x = 2.24 in the z table which has an area of 0.9875.