Answer:
Positive linear.
Step-by-step explanation:
The points are gradually rising as x increases.
The number of ways we can have five people line up at a checkout counter in a supermarket is 120 ways.
Since order is important, we use permutations to answer the question
<h3>What are permutations?</h3>
These are the number of ways, x of arranging n objects. It is given by ⁿPₓ = n(n - 1)(n - 2)(n - 3)...(n - x + 1) = n!/(n - r)!
Since we have five people to be arranged in line, there are 5 people to be arranged in 5 places.
So, there are 5 places for the first person, 4 places for the second person, 3 places for the third person, 2 places for the fourth person and 1 place for the last person.
So, we number of permutations or number of ways of arranging them in line is ⁵P₅ = 5 × 4 × 3 × 2 × 1
= 120 ways
So, the number of ways we can have five people line up at a checkout counter in a supermarket is 120 ways.
Learn more about permutations here:
brainly.com/question/5708836
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Answer:
The standard error of the sampling distribution of sample mean is: 6.5
Step-by-step explanation:
We use the Central limit theorem to solve this question.
The Central Limit Theorem estabilishes that, for a random variable X, with mean and standard deviation , a large sample size can be approximated to a normal distribution with mean and standard deviation, which is also called standard error of the sampling distribution of sample mean is
In this problem, we have that:
The standard error of the sampling distribution of sample mean is: 6.5
Answer:
allows us to accept the null hypothesis
Explanation:
The z test(in a normal distribution) score for the critical region determines whether we reject the null hypothesis(H0) or accept the null hypothesis(reject or fail to reject the null hypothesis). If we fail to reject the null hypothesis, then we have accepted the alternative hypothesis (H1). The critical region rejection for z test is calculated using alpha and z score, if z score is greater or less than alpha(positive or negative), we reject the null hypothesis.