Question

someone help me i dont know how to start

Answer 1

Write a paragraph that explains why taking 10 measurements better represents the weight of an average adult than just taking one measurement.

· Explain why repeated trials help ensure accuracy in your conclusions.

· Explain what might happen if scientists relied only on the first measurement and never carried out repeated trials.

Answer 2

Part I

Listed in the table are the weights of 10 random adults. You are going to find the average weight from our list. So, here you will add up the 10 weight values and then divide by 10 to get the average. When finished, add this to the beginning of the next assignment, Part II.

Adult Weight (in pounds)
James 156
Ohn 93
Emily 115
Donna 165
Oliver 202
Sai 180
Raiden 106
Gary 178
Greta 120
Yasmine 150

Total Weight:1,420 ÷ 10 = 142 average weight

Answer 3

@ganeshie8

Answer 4

@dumbcow

Answer 5

is this math English or ???

Answer 6

environmental science

Answer 7

is it like chemistry

Answer 8

i guess

Answer 9

then move it to chemistry

Answer 10

Well, Social Sciences do use a lot of statistics. They do rely on the importance of a sample size.

In any sociological study, there are flaws. One way to limit the flaws is to get a better sample. A larger percentage of the population can help because it is more representative. If I wanted to take the average of 3 people in my family, well, they all have a common genetic heritage so they do not represent the public. If I measured 50 people in my town, picked at random, they are still going to have some environmental factors, but they will be a lot less than the 3 in my family. When you do say 5000 people, picked at random from a mix of about a dozen cities that cover different population bases in one state, well, then you are beginning to get some real data that is a diversified sample but still a manageable number of people to work with.

Now, you will notice that other factors, like if people were my relatives or in my town, do play a part. Still, sample size is key. The larger the sample, the greater percentage of the whole it is and the more accurate it represents the whole. It is also something that can be controlled to make things managable.

Lest say you wanted to ask everyone in a country a question. The quality of the data would be great, but unless it was a small country it would be hard to deal with the volume. Even if there were only 10 million people, it would be hard to do. So lets ask half of them... say eliminate anyone under 13 because it is a political question, then see how many others you have to randomly eliminate. Now you have 5 million.... still huge! What if I had dropped 90% and only asked 10%? That is 1 million, a far more manageable number. And 1%, or 100,000, is easier still.

So there is this balance between how accurate your data will be and how easy it will be to collect. Mathematicians have spent years finding out how accurate these sorts of samples are and have made tons of formulas and charts relating to this. It is such a large endeavor that the branch of Mathematics has been given a special name: statistics.

I hope that covers the concept in general. It applies to how statistics are used in any science.