Drag the blue labels onto the table to identify the data that is relevant to each hypothesis. then use the pink labels to indica
te whether each hypothesis is supported or not supported by the data answers
2 answers:
Below is the answer from the indication whether each hypothesis is supported or not supported by the data answers
<h3>Further explanation </h3>Testing hypotheses. To test their hypotheses, the researchers examined the data they collected during the period of study.
Using the information available, they assessed whether the population sizes of cliff swallows and potential scavengers living near highways had changed over time. They determined how traffic patterns on these roads had changed over time. They also measured the bodies of cliff swallows that had been killed on the roads and compared their features to the features of cliff swallows in the general population. The table below summarizes the researchers' findings.
First, you will drag all the hypothesis-relevant labels highlighted in 'blue' onto the table. Then by looking at the table now filled with blue-label items, you should be able to figure a few things out. By using the pink labels, you will be able to indicate whether a hypothesis is supported or not.
- Hypothesis 1 => data collected: The wing shapes of swallows killed on road differ from those of the general population. Hypothesis supported? No (probably not a factor)
- Hypothesis 2 => data collected: The total number of cliff swallow nests near roads increased during this time. Hypothesis supported? Yes (additional data may be needed)
- Hypothesis 3 => data collected: Avian scavengers did not increase during this time, and terrestrial scavengers probably did not increase. Hypothesis supported? Yes (additional data may be needed)
- Hypothesis 4 => data collected: Car traffic stayed the same or increased during this time. Hypothesis supported? Yes (additional data may be needed)
- Learn more about hypothesis brainly.com/question/11555274
- Learn more about the population sizes brainly.com/question/9696567
- Learn more about Testing hypotheses brainly.com/question/8169133
Grade: 9
Subject: mathematics
Chapter: Testing hypotheses
Keywords: hypothesis, the population sizes, Testing hypotheses, the blue labels, pink labels
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Answer:
a)
The mean of adults aged 18 to 32 that continue to be dependent on their parents is 0.3
The mean of adults aged 18 to 32 that continue to be dependent on their parents is greater than 0.3
b) 34%
c) practically 0
d) Reject the null hypothesis.
Step-by-step explanation:
a)
Since an individual aged 18 to 32 either continues to be dependent on their parents or not, this situation follows a Binomial Distribution and, according to the previous research, the probability p of “success” (depend on their parents) is 0.3 (30%) and the probability of failure q = 0.7
According to the sample, p seems to be 0.34 and q=0.66
To see if we can approximate this distribution with a Normal one, we must check that is not too skewed; this can be done by checking that np ≥ 5 and nq ≥ 5, where n is the sample size (400), which is evident.
<em>We can then, approximate our Binomial with a Normal </em>with mean
and standard deviation
Since in the current research 136 out of 400 individuals (34%) showed to be continuing dependent on their parents:
The mean of adults aged 18 to 32 that continue to be dependent on their parents is 0.3
The mean of adults aged 18 to 32 that continue to be dependent on their parents is greater than 0.3
So, this is a r<em>ight-tailed hypothesis testing. </em>
b)
According to the sample the proportion of "millennials" that are continuing to be dependent on their parents is 0.34 or 34%
c)
Our level of significance is 0.05, so we are looking for a value such that the area under the Normal curve to the right of
is ≤ 0.05
This value can be found by using a table or the computer and is = 1.645
<em>Applying the continuity correction factor (this should be done because we are approximating a discrete distribution (Binomial) with a continuous one (Normal)), we simply add 0.5 to this value and </em>
corrected is 2.145
Now we compute the z-score corresponding to the sample
where
= mean of the sample
= mean of the null hypothesis
s = standard deviation of the sample
n = size of the sample
The sample z-score is then
The p-value provided by the sample data would be the area under the Normal curve to the left of 33.7759 which can be considered zero.
d)
Since the z-score provided by the sample falls far to the left of we should reject the null hypothesis and propose a new mean of 34%.