Answer:
a. Mean = 155.1 grams
b. Standard deviation = 0.37
c. Fractional uncertainty = 0.074
Step-by-step explanation:
a. Average weight
This is same as the mean weight;
Mathematically, that would be; sum of the weights/ the number of weights
= (155.1 + 154.8 + 155.5 + 155.3 + 154.6)/5 = 775.3/5 = 155.06 which is approximately 155.1
b. Standard deviation
Mathematically; we calculate that using the formula;
√{(x-mean)^2/(N-1)}
Please check attachment for for the complete breakdown of this
c. Fractional uncertainty
= Standard deviation/number of measurements = 0.37/5 = 0.074
In the first equation, you can tell that the x's are being multiplied by 3 to get to the y's so the blank will be 9. The second table would not be a function since all the x values are not being multiplied by the same number to get the y value. Hope this helps!
Answer:
2nd answer choice No, 6/2 does not equal 2/24 :)
Step-by-step explanation:
6/2=3 while 24/10=2.4
Another way you could think about it:
6*2=12
2+2=4
6*3=18
4+2=6
6*4=24
6+2=8
So 24 ounces of the shake would only be 8 grams of protein.
1. seven and fifty-five hundredths
2. two and seven hundredths
3. four and five hundredths
4. two and eighty-six hundredths
5. nine and eighteen hundredths
6. one and ninety hundredths or one and nine tenths
Using conditional probability, it is found that there is a 0.1165 = 11.65% probability that a person with the flu is a person who received a flu shot.
Conditional Probability
In which
- P(B|A) is the probability of event B happening, given that A happened.
is the probability of both A and B happening.
- P(A) is the probability of A happening.
In this problem:
- Event A: Person has the flu.
- Event B: Person got the flu shot.
The percentages associated with getting the flu are:
- 20% of 30%(got the shot).
- 65% of 70%(did not get the shot).
Hence:
The probability of both having the flu and getting the shot is:
Hence, the conditional probability is:
0.1165 = 11.65% probability that a person with the flu is a person who received a flu shot.
To learn more about conditional probability, you can take a look at brainly.com/question/14398287
