Answer:=
y^(97)
Step-by-step explanation:
Given the expression
(y 3)2 *y 7* y17* y12 *y42 *y13
We can apply the law of indices for the multiplication of the given expression
The law one to be specific states that If the two terms have the same base (in this case y) and are to be multiplied together their indices are added.
Y^m*y^n= y^(m+n)
=(y 3)2 *y 7* y17* y12 *y42 *y13
=y 6 *y 7* y17* y12 *y42 *y13
=y^(6+7+17+12+42+13)
=y^(97)
<u><em>An equation:</em></u>
It is used to express exact values.
Therefore, we will use an equation when when know that the quantity given is strictly equal to a given value.
<u>Examples:</u>
1- Price of a kilo of apples is $2
This is translated as ........> cost of 1 kilo = $2
2- The length of a ruler is 30 cm
This is translated as ......> length = 30 cm
<u><em>An inequality:</em></u>
It is used to show relation or compare between a quantity and a value. Therefore, we use it when we find keywords as "at least, at most, greater than, less than, ..... etc"
<u>Example:</u>
1- The distance between two cities is at least 20 miles.
This means that the distance can be 20 miles or more
This is translated as:
distance ≥ 20 miles
Hope this helps :)
I would say that the new two in sequence are S and 36.
There are two numbers between A and D, three between D and H, four between H and M, which means that S is the fifth number after M.
I think you are missing number 9 between D and H, which means that 4 + 5 =9, 9 + 7 = 16, 16 + 9 = 25, and 25 + 11 = 36, 2 is added to each number.
Answer: the probability that a randomly selected Canadian baby is a large baby is 0.19
Step-by-step explanation:
Since the birth weights of babies born in Canada is assumed to be normally distributed, we would apply the formula for normal distribution which is expressed as
z = (x - µ)/σ
Where
x = birth weights of babies
µ = mean weight
σ = standard deviation
From the information given,
µ = 3500 grams
σ = 560 grams
We want to find the probability or that a randomly selected Canadian baby is a large baby(weighs more than 4000 grams). It is expressed as
P(x > 4000) = 1 - P(x ≤ 4000)
For x = 4000,
z = (4000 - 3500)/560 = 0.89
Looking at the normal distribution table, the probability corresponding to the z score is 0.81
P(x > 4000) = 1 - 0.81 = 0.19