Answer:
We conclude that the mean is greater than 25.
Step-by-step explanation:
We are given the following in the question:
Population mean, μ = 25
Sample mean, = 27
Sample size, n = 100
Alpha, α = 0.05
Sample standard deviation, s = 6.5
First, we design the null and the alternate hypothesis
We use One-tailed(right) z test to perform this hypothesis.
Formula:
Putting all the values, we have
Now,
Since,
We reject the null hypothesis and accept the alternate hypothesis.
Thus, the mean is greater than 25.
The null hypothesis is the mean is equal to 25 and the alternative is that the mean is greater than 25. Using a one-sample t-test and 0.05 significance level, the calculated statistic results in rejection of the null hypothesis. Thus, there is sufficient evidence to suggest that the mean daily census in pediatrics is greater than 25.
1. The hypotheses for this scenario are that the null hypothesis (H0): the mean daily census in the pediatrics service is equal to 25, and the alternative hypothesis (H1): the mean daily census in the pediatrics service is greater than 25.
2. The appropriate test for this scenario would be a one-sample t-test, given that we have a sample mean, a population mean, a standard deviation, and we're examining a single group of hospitals.
3. The decision rule would be: if the p-value of our t-test is less than the significance level (α=.05), we reject H0 and accept H1.
4. The test statistic is calculated as follows: t = (Sample Mean-Population Mean)/(Sample Standard Deviation/ √number of observations), this would give us (27-25)/(6.5/√100) = 3.08.
5. Since 3.08 is greater than the critical value for a 0.05 significance level, we reject the null hypothesis. Therefore, there is sufficient evidence to conclude that the mean daily census in the pediatrics service is greater than 25.
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Answer:
a. non response bias
This is one of the usually cause when we use a non-random sample, sinc the probability of selection for all the individuals on the population is not the same when we use this, we are comitting non response bias since we are not taking in count some people in the possible target sample.
Nonresponse bias is "the bias that results when respondents differ in meaningful ways from nonrespondents. Nonresponse is often problem with mail surveys, where the response rate can be very low".
Step-by-step explanation:
Random sample
For this method we need the following two conditions:
(1) "Every element in our population has a nonzero probability of being selected as part of the sample."
(2)" We have accurate knowledge of this probability, known as the inclusion probability, for each element in the sampling frame".
Non random sample
It's the opposite of random sample and we have these problems associated:
(1) "It is relatively unusual to have a sampling frame available to you when you’re conducting market studies".
(2) "Ensuring that every individual in a population has a nonzero probability of being selected is just as difficult to accomplish; knowing every sampling unit’s exact inclusion probability is even more difficult. The individuals that cannot be selected as part of a sample are generally referred to as excluded units".
Assuming the following options:
a. non response bias
This is one of the usually cause when we use a non-random sample, sinc the probability of selection for all the individuals on the population is not the same when we use this, we are comitting non response bias since we are not taking in count some people in the possible target sample.
Nonresponse bias is "the bias that results when respondents differ in meaningful ways from nonrespondents. Nonresponse is often problem with mail surveys, where the response rate can be very low".
b. parameter
False we are looking for a cause related to non random sample. The parameter is just a value that we want to find but is not a cause related to the non random sample.
c. statistics
False, we can associate a cause of non random sample with the statistics. The term "statistics" is a big concept that involves a lot of methods and ways to analyze information, and is not the correct cause associated to the non-random sample.
d. population
False, we can associate the population as a cause of the non random sample. We use sampling methods in order to estimate some population parameters. But the population is not a cause of the non-random sample.
The equation for line n is y = 3x + c
An equation of a straight line is given by y = mx+c, where m is the slope and c is the intercept on the y axis.
In the question it is given that
Lines m and n are parallel to each other.
The equation of line m is y=3x+3
The equation of line n =?
The parallel lines m an n will have same slope but different intercept.
So the slope in the line equation y=3x+3 is 3
m = 3
Taking c as the intercept by the line n on y axis.
The equation for line n is y = 3x + c
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Answer:
y=3x-1
Step-by-step explanation:
You would have to change the y-intercept but that's all. Also, I put this answer into my ttm and got it right.
C. Associative Property
B. Distributive Property
D. Commutative Property
Property of Multiplication that is shown on the expression (5 + 3) x 2 = 5 x 2 + 3 x 2 is Distributive Property (option b)
The property of multiplication that is shown in the given equation is the Distributive Property. The Distributive Property states that multiplication distributes over addition. In other words, when we multiply a number by the sum of two other numbers, it is the same as multiplying the number by each of the individual addends and then adding the results together.
In the given equation, we have "(5 + 3) x 2 = 5 x 2 + 3 x 2." Let's break down the left-hand side first. "(5 + 3)" represents the sum of 5 and 3, which is 8. So, we have "8 x 2." By applying the Distributive Property, we can rewrite this as "5 x 2 + 3 x 2."
Now, on the right-hand side, we have "5 x 2 + 3 x 2." Here, we are multiplying 5 by 2 and 3 by 2 individually and then adding the products together. This aligns with the Distributive Property, which states that the result will be the same as on the left-hand side.
So, the Main Answer is option B. Distributive Property
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Answer:
B. Distributive Property of Multiplication
Step-by-step explanation:
The given equation shows that two similar expressions are equal to each other.
How? Well, they both equal 16 to start. These are the same expressions - one is just distributed out!
and...
In the equations, the only difference is that we distributive 2 and multiplied in by 5 and 3!
I hope I was of assistance! #SpreadTheLove <3