Please give me the correct answer.
1 answer:
Answer:
Top Right Graph
Step-by-step explanation:
By looking at the equation, we can see that y = -2x + 1 is in slope-intercept form because it's in a format. If a line can be written in slope-intercept form, then it must be linear, meaning that the graph must be one straight line.
Now, this narrows it down to two graphs. However, remember that in equations written in slope-intercept form, the of the equation, or the coefficient of the x-term, represents the slope. Thus, the slope of the equation is -2. Now, since the slope is negative, then the graph decreases (reading from left to right).
Therefore, since the top right graph is the only graph that is linear and decreases, it must be the answer.
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Answer:
The pvalue of the test is 0.7188 > 0.05, which means that there is not enough statistical evidence based on the sample to dispute the results of the study published in Psychiatry Research.
Step-by-step explanation:
Test if there is enough statistical evidence based on the sample to dispute the results of the study published in Psychiatry Research:
This means that at the null hypothesis we test if the proportion is 62%, that is:
At the alternate hypothesis, we test if the proportion is different from 0.62, that is:
The test statistic is:
In which X is the sample mean, is the value tested at the null hypothesis,
is the standard deviation and n is the size of the sample
62% is tested at the null hypothesis:
This means that
When a random sample of 26 autistic children were observed, 17 were found to be left-handed.
This means that
Value of the test statistic:
Pvalue of test and decision:
The pvalue of the test is the probability of a proportion that differs from the mean by at least 0.6538 - 0.62 = 0.0338, which is P(|z| > 0.36), which is two multiplied by the pvalue of z = -0.36
Looking at the z-table, z = -0.36 has a pvalue of 0.3594
2*0.3594 = 0.7188
The pvalue of the test is 0.7188 > 0.05, which means that there is not enough statistical evidence based on the sample to dispute the results of the study published in Psychiatry Research.