Just remember that in the form of 
, you get 
.
Using proportions, it is found that it takes 886 more mini-bears than regular-bears to have the same weight as one super-bear.
<h3>What is a proportion?</h3>
A proportion is a fraction of a total amount, and the measures are related using a rule of three. Due to this, relations between variables, either direct(when both increase or both decrease) or inverse proportional(when one increases and the other decreases, or vice versa), can be built to find the desired measures in the problem, or equations to find these measures.
10 mini-bears weights to 12.1 grams, hence the weight of a mini-bear is of:
12.1/10 = 1.21 grams.
10 regular bears weights to 23.1 grams, hence the weight of a regular bear is of:
23.1/10 = 2.31 grams.
1 super bear weights to 2250 grams, hence the proportion between the <u>weight of a super bear and the weight of a mini-bear</u> is:
2250/1.21 = 1860.
The proportion between the <u>weight of a super bear and the weight of a regular bear</u> is:
2250/2.31 = 974.
The difference of proportions is given by:
1860 - 974 = 886.
It takes 886 more mini-bears than regular-bears to have the same weight as one super-bear.
More can be learned about proportions at brainly.com/question/24372153
#SPJ1
Answer:
store B, C, and D
Step-by-step explanation:
Awnser:
9,12,18
Step-by-step explanation:
you have to add the smallest numbers together and it has to be greater that the greatest number.
9+12= 21
21>18
Answer:
The degrees of freedom are given by:
The significance level is 
and then the critical value can be founded in th chi square table we need a quantile that accumulates 0.05 of the area in the right tail of the distribution and for this case is:
And if the chi square statistic is higher than the critical value we can reject the null hypothesis in favor of the alternative.
Step-by-step explanation:
We have the followign system of hypothesis:
Null hypothesis: 
Alternative hypothesis: 
The degrees of freedom are given by:
The significance level is and then the critical value can be founded in th chi square table we need a quantile that accumulates 0.05 of the area in the right tail of the distribution and for this case is:
And if the chi square statistic is higher than the critical value we can reject the null hypothesis in favor of the alternative.
