Answer:
<em>As mean and median are equal, so the data will be in normal distribution in shape of a symmetrical "bell curve".</em>
Step-by-step explanation:
The given data: 10 5 8 10 12 6 8 10 15 6 12 18
<u>Mean is the simple average of all data</u>. As, there are total 12 data, so the Mean will be: 
For finding the Median, <u>first we need to rearrange the data according to the numerical order and then identify the middle value</u>. So........
5 6 6 8 8 10 10 10 12 12 15 18
Here the middle values are 10 and 10. So, the median will be the average of those two middle values.
Thus, Median 
We can see that, <u>the relationship between the mean and the median is "they are equal"</u>. So, the data will be in normal distribution and the shape will be symmetrical "bell curve".
Answer:
<h2><em><u>
0.6 = 6/10 = 3/5 is the answer.</u></em></h2>
Step-by-step explanation:
0.6 = 6/10 = 3/5
is the answer
This is because you have to substitute.
Given:
x = 3
y = -1
Unknown:
Final Answer
(x*y^2)/5
((3)(-1*-1)/5
= (3*1)/5
<h2><em><u>
= 3/5</u></em></h2><h2><em><u>
= 6/10</u></em></h2><h2><em><u>
= 0.6</u></em></h2><h2><em><u>
</u></em></h2>
Hope this helped,
Kavitha
Answer:
The answer is 234
Step-by-step explanation:
Answer:
Students collected
pounds of paper;
pounds of cans;
pounds of paper and cans combined in September and October.
Step-by-step explanation:
In September, the students collected 85 pounds of paper and 18 pounds of cans to recycle.
In October, their goal is to collect three times the amount of paper and five times the amount of cans they collected in September.
Hence, in October they collected
pounds of paper;
pounds of cans.
In total, they collected
- pounds of paper;
- pounds of cans;
- pounds of paper and cans combined in September and October.
Answer:
1) you're going to have to flip the coins (or fake numbers) for the experimental trials.
2) for the theoretical, there is 1/2 chance for heads or tails with each toss, so you'd expect that out of 10 tosses, 5 heads, 5 tails. out of 100 tosses- 50 heads, 50 tails.
When tossing 2 coins- 1/2×1/2 = 1/4 (25%) chance that 2 heads, 2 tails, or 1 heads & 1 tails. Deviation value comes from after you done your flipping and recorded your data. So if on 100 flips you actually got 50 and 50 (rarely us that exact ;), the deviation from the expected of 50/50 would be 0.00. If however you flipped 100 heads or 100 tails (impossible), then the deviation value would be 1.00.
|(100-50)| ÷ 50 = 50÷50 = 1.00
So usually you may have data like: 47/53 or something a little off than 50/50, making deviation |(47-50)| ÷ 50 = 3÷50 = 0.06.
Now the number of flips is important for the outcome! So if a coin toss if 10 times had 4 heads, 6 tails, the deviation value would be:
|(4-5)| ÷ 5 = 1÷5 = 0.20
So increasing the # flips DECREASES the deviation value!!
Whether it's from 10 to 100, or from 100 to 200. Look at my example of how the 10-flip deviation of 0.20 decreased to 0.06 with 100-flip
