Answer:
Circular shapes - They are those planner shapes that represent the locus of all the points that has a constant distance from a fixed point on the plane. This constant distance is termed as the radius of the circle and the fixed point is known as the center of the circle.
The center of the circle is enclosed by all the points on its periphery.
The circumference of the circle is the total length of its periphery around the center.
Concentric circles are two circles that have the same center
Step-by-step explanation:
Step-by-step explanation:
A famer wants to divide 8085 ha of grazing into 9 or 15 cramp of equal size
Answer:
55
Step-by-step explanation:
Answer:
By the Central Limit Theorem, both would be approximately normal and have the same mean. The difference is in the standard deviation, since as the sample size increases, the standard deviation decreases. So the SRS of 600 would have a smaller standard deviation than the SRS of 200.
Step-by-step explanation:
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean
and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For the sampling distribution of size n of a sample proportion p, the mean is p and the standard deviation is 
Differences between SRS of 200 and of 600
By the Central Limit Theorem, both would be approximately normal and have the same mean. The difference is in the standard deviation, since as the sample size increases, the standard deviation decreases. So the SRS of 600 would have a smaller standard deviation than the SRS of 200.
We will have the following:
Using exponential regression we will have that the line of best fit will be:

Now, we will have that:

So, the approximation using linear regression gives us as solution approximately 29.7 years; thus the closest one to match is then