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.
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Answer:
Step-by-step explanation:
There are <em>an infinite number of possibilities</em>. Any vector whose dot-product with p is zero will be perpendicular to p.
Let m = 0i +1j +ak. Then we require ...
m·p = 0 = 0×1 +1×2 +a(-2) ⇒ 0 = 2 -2a ⇒ a = 1
m = 0i +1j +1k
__
Let n = 2i +0j +bk
n·p = 0 = 2×1 +0×2 +b(-2) ⇒ 2 -2b = 0 ⇒ b = 1
n = 2i +0j +1k
Answer:
P(Z < 2.37) = 0.9911.
Step-by-step explanation:
We are given that Let z denote a random variable that has a standard normal distribution.
Let Z = a random variable
So, Z ~ Standard Normal(0, 1)
As we know that the standard normal distribution has a mean of 0 and variance equal to 1.
Z = 
~ N(0,1)
where, 
= mean = 0
= standard deviation = 1
Now, the probability that z has a value less than 2.37 is given by = P(Z < 2.37)
P(Z < 2.37) = P(Z < 
) = P(Z < 2.37) = 0.9911
The above probability is calculated by looking at the value of x = 2.37 in the z table which has an area of 0.9911.
Answer:
3. b
2. c
Step-by-step explanation:
The Range (Statistics) The Range is the difference between the lowest and highest values.
The mean is the sum divided by the count.
-20 because after the the thermometer hits zero the more negative the temperature gets the colder it is
