Answer:
a) 0.1587
b) 0.0475
c) 0.7938
Step-by-step explanation:
Let's start defining our random variable.
X : ''Thickness (in mm) of ancient prehistoric Native American pot shards discovered in a Hopi village''
X is modeled as a normal random variable.
X ~ N(μ,σ)
Where μ is the mean and σ is the standard deviation.
To calculate all the probabilities, we are going to normalize the random variable X.
We are going to call to the standard normal distribution ''Z''.
[(X - μ) / σ] ≅ Z
We normalize by subtracting the mean to X and then dividing by standard deviation.
We can find the values of probabilities for Z in a standard normal distribution table.
We are going to call Φ(A) to the normal standard cumulative distribution evaluated in a value ''A''
a)
Φ(-1) = 0.1587
b)
1 - Φ(1.666) = 1 - 0.9525 = 0.0475
c)
Φ(1.666) - Φ(-1) = 0.9525 - 0.1587 = 0.7938
Answer:
130
Step-by-step explanation:
Percentage of 77% of what = 100.1?
77% × ? = 100.1
? =
100.1 ÷ 77% =
100.1 ÷ (77 ÷ 100) =
(100 × 100.1) ÷ 77 =
10,010 ÷ 77 =
130
Answer:A. provide evidence of a causal relationship between an independent variable and the variable to be forecast
Step-by-step explanation: Casual model tends to show the cause and effect relationship between the dependent variable to be forcasted and the independent variables upon which the dependent variable is dependent.
Casual model is frequently used in the field of Statistics and Economics when making forcasts about future investments or the cause of certain events,knowing what activities to carry out in the future.
Answer:
11
Step-by-step explanation:
Let the no. of helmet be x
cost of 1 helmet = $12.00
cost of x helmet = $12.00*x = $12x
Let the no. of tire pumps be y
cost of 1 tire pumps = $8.00
cost of x tire pumps = $8.00*y = $8y
Given that total no. of helmet and pump is 18
thus
x + y = 18
y = 18-x
also given
total money spent is $188
thus
12x+8y = 188
using y = 18 - x
we have
12x + 8(18-x) = 188
=> 12x+ 144 - 8x = 188
=> 4x = 188-144 = 44
=> x = 44/4 = 11
Thus, no of helmet bought by Margo is 11.