The answer is B, f(x) = 4x + 4.
If you substitute 2 for x, the resulting answer will be 12, therefore it is correct.
Answer:
C.I = 0.7608 ≤ p ≤ 0.8392
Step-by-step explanation:
Given that:
Let consider a random sample n = 400 candidates where 320 residents indicated that they voted for Obama
probability 
= 0.8
Level of significance ∝ = 100 -95%
= 5%
= 0.05
The objective is to develop a 95% confidence interval estimate for the proportion of all Boston residents who voted for Obama.
The confidence internal can be computed as:

where;
=
= 1.960
SO;






= 0.8 - 0.0392 OR 0.8 + 0.0392
= 0.7608 OR 0.8392
Thus; C.I = 0.7608 ≤ p ≤ 0.8392
Answer: 1:4
Step-by-step explanation:
3:12 written as a fraction is 3/12
Simplify:
3/12 = 1/4
Answer:
78 nickels and 22 dimes
Step-by-step explanation:
Nickels = n, Dimes = d
<u>Number of coins = 100</u>
<u>Total sum in the piggy bank = $6.60 </u>
<u>Consider the first equation in the second:</u>
- 5(100 -d) + 10d = 660
- 500 - 5d + 10d = 660
- 5d = 110
- d = 110/5
- d = 22
- n = 100 - 22
- n = 78
<u>Answer:</u> nickels 78 and dimes 22
Answer:
And we can find this probability using the complement rule:
And in order to find these probabilities we can find tables for the normal standard distribution, excel or a calculator.
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the scores of a population, and for this case we know the distribution for X is given by:
Where
and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability using the complement rule:
And in order to find these probabilities we can find tables for the normal standard distribution, excel or a calculator.