You have 2+2 in each 2 there are 1's so
2=(1+1) 2=(1+1) =4
4=1+1+1+1
2+2=4
think of 2's as 1's when adding did you know 2x2= 4 as well.
Answer:
<u>D) (f o g)(x) = 10x² - 60x + 93</u>
Step-by-step explanation:
f(x) = 10x² + 3
g(x) = x - 3
⇒ (f o g)(x)
⇒ f(x - 3)
⇒ f(x - 3) = 10(x - 3)² + 3
⇒ f(x - 3) = 10(x² - 6x + 9) + 3
⇒ f(x - 3) = 10x² - 60x + 90 + 3
⇒ <u>(f o g)(x) = 10x² - 60x + 93</u>
Answer: 37 percent of waste is disposed of in some form of a landfill, 8 percent of which is disposed of in sanitary landfills with landfill gas collection systems
The U.S. is the king of trash, producing a world-leading 250 million tons a year—roughly 4.4 pounds of trash per person per day Collectively, out of the 254 million tons of trash Americans can produce in one year, we recycle about 34.3 percent of it. For our average individual, 710.6 pounds are recycled and 1,361.4 pounds of trash are tossed out every year — about the weight of a grizzly bear Every year, U.S. landfills are filled with 139.6 million tons of waste, including 30.63 million tons of food. 26.82 million tons of plastic. 18.35 million tons of paper and paperboard.
don't mark brainiest
Answer:
3040
Step-by-step explanation:
given arithmetic progression is
70,100,130,...
here
first term (a)=70
common difference (d)=100-70=30
number of term n=100
using the formula of arithmetic progression
an=a+(n-1)d
a100=70+(100-1)30
a100=70+99×30
a100=70+2970
a100=3040
Answer:
The difference between the sample statistic and population parameter is called sampling error.
Step-by-step explanation:
We are given the following in the question:
- A sample is a part of population, it is a subset of population.
- A sample statistic describes the sample. It is a characteristic of sample and different from the population.
- A parameter describes the population. It is characteristic of a population.
- A sample may not be able to represent the whole population and this may lead to error.
- Thus, sampling error is the difference between the sample statistic and population parameter.
- It arises when the sample is not able to describe the population.
The difference between the sample statistic and population parameter is called sampling error.
