The sum of the probabilities in a probability distribution is always 1.
A probability distribution is a collection of probabilities that defines the likelihood of observing all of the various outcomes of an event or experiment. Based on this definition, a probability distribution has two important properties that are always true:
Each probability in the distribution must be of a value between 0 and 1.
The sum of all the probabilities in the distribution must be equal to 1.
An example: You could define a probability distribution for the observation for the number displayed by a single roll of a die. The probability that the die with show a "1" is
1
6
.
That's because there are six possible outcomes, and only one of those outcomes is a "1". Lets label the probabilities of all the possible outcomes for the single die.
Roll a "1": Probability is
1
6
Roll a "2": Probability is
1
6
Roll a "3": Probability is
1
6
Roll a "4": Probability is
1
6
Roll a "5": Probability is
1
6
Roll a "6": Probability is
1
6
Each probability is between 0 and 1, so the first property of a probability distribution holds true. And the sum of all the probabilities:
1
6
+
1
6
+
1
6
+
1
6
+
1
6
+
1
6
=
1
,
so the second property of a probability distribution holds true.
25 because you would just get rid of the 2/3
Answer:
its 6.75
Step-by-step explanation:
3/10 = 0.3
2/5 = 0.4
0.3 / 0.4 = 0.75
0.75 x 9 = 6.75
hope i helped
Answer:
£21
Step-by-step explanation:
Sarah : Gavyn = 5:3
Sarah's share = 5x
Gavyn's share = 3x
5x - 3x = 14
2x = 14
x = 14/2
x = £ 7
Gavyn's share = 3x = 3 * 7 = £21
<u>ANSWER</u>
<u>EXPLANATION</u>
This very simple to do.
First locate the entry in 
in matrix A. That is the entry in the intersection of the fourth row and first column of matrix A. This entry is 
.
Then multiply by the scalar which is 2 to get,
.
Next we locate the entry in 
in matrix B also. Which is 
. We multiply by the scalar of 
to get,
.
We now add these two corresponding entries to obtain,
See diagram
