Going by the data given, the best center of distribution to use in terms of mean and median is D) Mean for Bakery A because the data is symmetric; median for Bakery B because the data is not symmetric.
<h3>What centers of distribution should be used?</h3>
The mean should be used for data sets that are symmetric while the median should be used for data that is not symmetric.
The data is said to be symmetric when the mean and median are equal or very close.
Bakery A mean:
= (45 + 52 + 51 48 + 61 + 34 + 55 46) / 8
= 49
Bakery A median is 49.5
Bakery B mean:
= (48 42 + 25 45 + 57 + 10 + 43 + 46 ) / 8
= 39.5
Bakery B median is 44.
This shows that Bakery A data is symmetric so the best center of distribution to use is mean.
Bakery B is not symmetric so the center of distribution to use is median.
Find out more on symmetric data at brainly.com/question/7130507
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Answer:
38 candies.
Step-by-step explanation:
Given the following data;
Total number of candy = 874
Total number of children = 23
Since we know that they are all sharing it equally, each child would get;
Each child = 874/23
Each child = 38 candies.
You probably jsut need to use law of cosines in order to solve for angle A
or
200, because the more samples you have the more correct you will be.
Answer: First of all, we will add the options.
A. Yes, because 3 inches falls above the maximum value of lengths in the sample.
B. Yes, because the regression equation is based on a random sample.
C. Yes, because the association between length and weight is positive.
D. No, because 3 inches falls above the maximum value of lengths in the sample.
E. No, because there may not be any 3-inch fish of this species in the pond.
The correct option is D.
Step-by-step explanation: It would not be appropriate to use the model to predict the weight of species that is 3 inches long because 3 inches falls above the maximum value of lengths in the sample.
As we can see from the question, the model only accounts for species that are within the range of 0.75 to 1.35 inches in length, and species smaller or larger than that length have not been taken into consideration. Therefore the model can not be used to predict the weights of fishes not with the range accounted for.
