Bias refers to scenarios which might affect the ability of a statistical experiment to generalize, hence affecting the validity of research. Non-response bias occurs when majority of subjects <em>fail to respond during a survey</em>. Hence, a likely scenario is ; <em>surveys were mailed to 500 people, and 200 of the surveys were completed and </em><em>returned</em><em>.</em><em> </em>
- Non - response bias has to do with a situation whereby a large percentage of the selected samples from a population do not respond or fail to participate in the experiment or survey.
- If 200 surveys were returned, then 300 of the sample participants did not respond. Which means <em>60% of the sample are non-responsive</em>.
Therefore, a scenario where <em>surveys were mailed to 500 people, and 200 of the surveys were completed and </em><em>returned</em><em> </em>exemplifies a non - response bias.
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Answer:
The answer is 180°. Hope this helps!
Answer: 
Step-by-step explanation:
Let p be the population proportion for the graduates from private nonprofit colleges in the region had at least one outstanding student loan at the time of graduation.
Given : Tristan is an administrator for a private nonprofit college and read a surprising statistic that 74% of graduates from private nonprofit colleges in the region had at least one outstanding student loan at the time of graduation.
i.e. 
He believes that percentage is high and claims that the proportion of graduates at his college is less than the regional rate.
i.e. 
Since, the null hypothesis is a statement which always takes equal sign or generally shows " no difference " where as alternative hypothesis takes unequal signs.
Then, the null and alternative hypotheses for this hypothesis test :-

A;
[(4 x 6) + (5 x 2)] - [(14 x 2) + 7]
B;
[(4 x 6) + (5 x 2)] - [(14 x 2) + 7]
[24 + 10] - [28 + 7]
34- 21
13
answer: $13