Answer: see below
<u>Step-by-step explanation:</u>
To find the frequency, simply count the number of leaves
Brisbane:
Stem Leaf Frequency
0 0
1 0
2 8,6,5 3
3 5 1
4 8,8,4,2 4
5 9,2,0,0 4
6 7,6,2,2,1,1 6
7 6,2,2,1,1,1,0,0 8
8 9,9,9,8,2 5
Brisbane Graph:
Parth:
Stem Leaf Frequency
0 0,0,1,1,2,2 6
1 0,2,4,5 4
2 0,7,8,9 4
3 0,1,4,6 4
4 1,2,5,5,9 5
5 1,3,3,6,7 5
6 0,1,2 3
7 0
8 0
Parth Graph:
Answer:
125 cups
Step-by-step explanation:
We're given a total of 250 as the goal, and the product being sold is 2 per, hence, we'll use the following inequality:
To find the amount of hot chocolate they need to sell to satisfy the inequality, we solve for x:
The debate team has to sell atleast 125 of the product to meet their goal.
<em>Hope this helped! Have a good day.</em>
Answer:
Let X the random variable of interest "number of cars with side airbags among the next 4", on this case we now that:
The probability mass function for the Binomial distribution is given as:
Where (nCx) means combinatory and it's given by this formula:
And the distribution is given by:
With
Step-by-step explanation:
Previous concepts
A Bernoulli trial is "a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is conducted". And this experiment is a particular case of the binomial experiment.
The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".
Solution to the problem
Let X the random variable of interest "number of cars with side airbags among the next 4", on this case we now that:
The probability mass function for the Binomial distribution is given as:
Where (nCx) means combinatory and it's given by this formula:
And the distribution is given by:
With
