The probability of not surviving a head-on car accident is: 0.903
Step-by-step explanation:
The probabilities of occurrence and non-occurrence of an event add up to one.
If p is the probability that an even will happen and q is the probability that it will not happen
Then

Here,
Probability of surviving = p = 0.097
Probability of not surviving = q = ?

The probability of not surviving a head-on car accident is: 0.903
Keywords: Probability, Inverse
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It’s 5 1/3 because 16 divided by 3 is 5 1/3
Answer:
C) -7/3
Step-by-step explanation:
m=(y2-y1)/(x2-x1)
m=(9-(-5))/(-2-4)=(9+5)/-6=14/-6
simplify -14/6 to -7/3
Answer:
The Correct option is - d. all of the above.
Step-by-step explanation:
To find - In assessing the validity of any test of hypotheses, it is good practice to
a. examine the probability model that serves as a basis for the test by using exploratory data analysis on the data.
b. determine exactly how the study was conducted.
c. determine what assumptions the researchers made.
d. all of the above.
Proof -
All the Given options are correct to study the validity of a hypothesis test.
So,
The Correct option is - d. all of the above.
Answer:
The margin of error is of 0.3012, and it means that we should be 99% confident that the population mean would be within 0.3012 of the sample mean.
Step-by-step explanation:
Margin of error

In which
is the standard deviation and n is the size of the sample.
Standard deviation of 1.3
This means that 
She surveys 124 families
This means that 
Margin of error and meaning:



The margin of error is of 0.3012, and it means that we should be 99% confident that the population mean would be within 0.3012 of the sample mean.