I'm not sure how to write the rule, but every time you add one more to the sum of the last two. First, you add 1, then 2, then 3. 1+1=2 2+2=4 4+3=7 7+4=11 and so on. I hope this helps!
Answer:
Step-by-step explanation:
Hint: 1- 2sin²x = Cos 2x
LHS = 1 - 2Sin² (π/4 - Ф/2)
= Cos 2 *(π/4 - Ф/2)
= Cos 2*π/4 - 2*Ф/2
= Cos π/2 - Ф
= Sin Ф = RHS
B = 100(1 + 0.04)^12 = 100(1.04)^12 = 100(1.601) = $160.10
Answer:
From least to greatest
23* 1/4, 23* 2/2, 23* 13/5
Explanation
In order to do this without multiplication, place the fractions in ascending order.
The denominators of these fractions have 20 as a common multiple.
2/2 • 10 = 20/20
1/4 • 5 = 5/20
13/5 • 4 = 52/20
From this it logically follows that the fractions in ascending order are:
1/4, 2/2, 13/5
Therefore the products in ascending order are:
23* 1/4, 23* 2/2, 23* 13/5
Answer:
The probability that the sample mean would differ from the population mean by more than 2.6 mm is 0.0043.
Step-by-step explanation:
According to the Central Limit Theorem if we have a population with mean μ and standard deviation σ and appropriately huge random samples (n > 30) are selected from the population with replacement, then the distribution of the sample means will be approximately normally distributed.
Then, the mean of the distribution of sample mean is given by,

And the standard deviation of the distribution of sample mean is given by,

The information provided is:
<em>μ</em> = 144 mm
<em>σ</em> = 7 mm
<em>n</em> = 50.
Since <em>n</em> = 50 > 30, the Central limit theorem can be applied to approximate the sampling distribution of sample mean.

Compute the probability that the sample mean would differ from the population mean by more than 2.6 mm as follows:


*Use a <em>z</em>-table for the probability.
Thus, the probability that the sample mean would differ from the population mean by more than 2.6 mm is 0.0043.