300; Since EF is the only segment not included in FHE, just subtract the 60 degrees there from 360 to get the sum of the rest of the circle
360-60 = 300
Hopefully this is right, i'm a little rusty on geometry
Answer:
70
Step-by-step explanation:
= First term = 
= Common difference = 
= Number of terms = 20
Sum of arithmetic progression is given by
![S=\dfrac{n}{2}[2a_1+(n-1)d]\\\Rightarrow S=\dfrac{20}{2}\times (2\times \dfrac{1}{3}+(20-1)\dfrac{1}{3})\\\Rightarrow S=70](https://tex.z-dn.net/?f=S%3D%5Cdfrac%7Bn%7D%7B2%7D%5B2a_1%2B%28n-1%29d%5D%5C%5C%5CRightarrow%20S%3D%5Cdfrac%7B20%7D%7B2%7D%5Ctimes%20%282%5Ctimes%20%5Cdfrac%7B1%7D%7B3%7D%2B%2820-1%29%5Cdfrac%7B1%7D%7B3%7D%29%5C%5C%5CRightarrow%20S%3D70)
The sum of the first 20 terms of the arithmetic sequence is 70.
Answer:
standard deviation
Step-by-step explanation:
The standard deviation is defined as the measure of how spread out the numbers are in a given population. In other words, statistics refers to the amount of the dispersion or variation of a set of given values.
It is denoted by the Greek letter sigma, σ.
Thus the standard deviation is the measure of how dispersed the data are in the population which can be used to provide context to a larger data sets.
So the answer is -10.
<em>Look</em><em> </em><em>at</em><em> </em><em>the</em><em> </em><em>attached</em><em> </em><em>picture</em><em>⤴</em>
<em>Hope</em><em> </em><em>this</em><em> </em><em>will</em><em> </em><em>help</em><em> </em><em>u</em><em>.</em><em>.</em><em>.</em>
There could be a strong correlation between the proximity of the holiday season and the number of people who buy in the shopping centers.
It is known that when there are vacations people tend to frequent shopping centers more often than when they are busy with work or school.
Therefore, the proximity in the holiday season is related to the increase in the number of people who buy in the shopping centers.
This means that there is a strong correlation between both variables, since when one increases the other also does. This type of correlation is called positive. When, on the contrary, the increase of one variable causes the decrease of another variable, it is said that there is a negative correlation.
There are several coefficients that measure the degree of correlation (strong or weak), adapted to the nature of the data. The best known is the 'r' coefficient of Pearson correlation
A correlation is strong when the change in a variable x produces a significant change in a variable 'y'. In this case, the correlation coefficient r approaches | 1 |.
When the correlation between two variables is weak, the change of one causes a very slight and difficult to perceive change in the other variable. In this case, the correlation coefficient approaches zero
