Answer: d. There is no relationship between education level and smoking habits.
Step-by-step explanation:
The null hypothesis is the affirmation that two parameters or phenomena do not have a relation between them.
Here the parameters are smoking and having a bachelor's degree or higher education.
Then the null hypothesis says that those two things do not have any relation, this would imply that the probability of being a smoker does not depend on having a degree or not.
Then the correct option is d "There is no relationship between education level and smoking habits."
The percentage of men is more than 72 inches tall will be 0.15866.
<h3>What is the z-score?</h3>
The z-score is a statistical evaluation of a value's correlation to the mean of a collection of values, expressed in terms of standard deviation.
The z-score is given as
z = (x – μ) / σ
Where μ is the mean, σ is the standard deviation, and x is the sample.
Suppose the mean height for men is 70 inches, with a standard deviation of 2 inches.
Then the percentage of men are more than 72 inches tall will be
z = (72 – 70) / 2
z = 1
The percentage of men is more than 72 inches tall will be
P(x > 72) = P(z > 1)
P(x > 72) = 1 – P(x < 72)
P(x > 72) = 1 – 0.84134
P(x > 72) = 0.15866
Thun, the percentage of men are more than 72 inches tall will be 0.15866.
More about the z-score link is given below.
brainly.com/question/15016913
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Answer:
Total distance = 30.3 units
Step-by-step explanation:
Coordinates for the location of Alanah, Mia, Teresa and Arena are,
Alanah → (2, 8)
Mia → (8, 16)
Teresa → (8, 2)
Arena → (14, 4)
Distance between two points and is given by the formula,
d =
Distance between Alanah and Mia =
=
= 10 units
Distance between Mia and Teresa =
= 14 units
Distance between Teresa and Arena =
=
= 6.3 units
Total distance of Alanah's trip to Arena = 10 + 14 + 6.3
= 30.3 units
Answer:
When selecting a sample for a survey, the way you choose your sample: <u>A) may lead to biased results</u>.
Step-by-step explanation:
The way you choose your sample matters a lot in order to help limit the bias in sampling data.
There are <em>four types</em> of <u>random</u> samples: simple, stratified, cluster, and systematic.
There are <em>two types </em>of <u>non-random</u> samples: voluntary response and convenience.
You always want to have a random sample in order to have accurate, non-biased results. Therefore, A) May lead to biased results is the best answer.