Answer:
x = 20° and y = 12°
Step-by-step explanation:
3y + 15° = 5y - 9° ( being opposite angles of parallelogram)
5y - 3y = 15° + 9°
2y = 24°
y = 24° / 2
y = 12°
Now
5x + 29° = 7x - 11° ( being opposite angles of parallelogram)
7x - 5x = 29° + 11°
2x = 40°
x = 40° / 2
x = 20°
Hope it will help :)❤
If each garden takes 20 minutes to clean, it will take him (20 x 4) to clean the gardens.
20 x 4 = 100
80 minutes
or 1 hour and 10 minutes.
Maybe i have that you wanted
We can represent the situation like that:
Y=-15 and x=-20
Then When y=12 x=?
We make x(The unknown) *-15=12*(-20)
We have an simple équation to solve
Thus x=(12*(-20))/-15
X=16
Cosine theta equals the negative square root of three over two; tangent theta equals the negative square root of three over three is the correct answer.
<h3>What is angle measurement?</h3>
An angle measure is the measurement of the angle created by two rays or arms at a shared vertex in geometry. A protractor is used to measure angles in degrees (°).
Given data;
sin(1/2) = π/6
The value of the trignometric function are;
cos(π/6) = (√3)/2
tan(π/6) = 1/√3 = (√3)/3
In the second quadrant, where the cosine and tangent signs are both negative, is the angle of interest.
θ = 5π/6
cos(5π/6) = -(√3)/2
tan(5π/6) = -(√3)/3
Hence. cosine theta equals the negative square root of three over two; tangent theta equals the negative square root of three over three is the correct answer.
To learn more about the angle measurement, refer to the link;
brainly.com/question/14684647
#SPJ1
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.
