In a recent article, the author states that 71% of adults do not use sunscreen. Although 71% is a large percentage, explain why it could be misleading. As you answer the questions above, identify what types of misrepresentation or misuse have been demonstrated by referring to the bold blue headings in the “Chapter 12 Supplement” (e.g., Suspect Samples, Asking Biased Questions, Misleading Graphs, etc.).
You need a representative sample of all adults, and you need to ask about use of sunscreen in a non-judgemental way. You also need to caqrefully define "use".
We do not have the benefit of your "Chapter 12 supplement" to help answer the question. Many adults use sunscreen purchased by others, and only occasionally.
I use it about once a year. I don't buy it... my wife does. Does that make me a non-user?
Create a math formula showing that if 71% of adult use sunscreen and 71% is a large number how many use or do not use sunscreen?
To explain why the statement that 71% of adults do not use sunscreen could be misleading, we need to consider potential types of misrepresentation or misuse that may be involved. Let's evaluate the claim in light of the different headings from the "Chapter 12 Supplement":
1. Suspect Samples: It is possible that the sample used to obtain the statistic of 71% may not be representative of the entire population of adults. If the sample is biased or does not accurately reflect the demographics of the population, it could lead to an overestimation or underestimation of sunscreen usage.
2. Asking Biased Questions: The wording and phrasing of the questions asked to gather the data may have a bias, leading respondents to answer in a certain way. For example, if the question asked, "Do you always use sunscreen?" it may demotivate individuals who use sunscreen but not religiously to answer in the affirmative, thereby inflating the percentage of non-users.
3. Misleading Graphs: If a graph is used to represent the data, it could potentially present the information in a misleading manner. For instance, if the y-axis of the graph does not start at zero, it can distort the visual representation and magnify the perceived difference between sunscreen users and non-users.
4. Faulty Survey Techniques: If the survey used to gather the data is flawed, it could introduce errors and inaccuracies. For example, if the survey was conducted online and only accessible to tech-savvy individuals, it might exclude older adults who are less likely to use the internet regularly. This exclusion could skew the results and misrepresent the actual sunscreen usage among adults.
5. Misused Averaging: The statistic of 71% could be a result of averaging data from different groups, such as different age ranges or geographical locations, without considering their proportions in the overall population. This type of averaging can lead to a misleading representation of sunscreen usage across the entire adult population.
Overall, without specific information on how the data was collected and analyzed, it is important to critically evaluate the claims made regarding sunscreen usage. Considering the potential misrepresentations and misuses highlighted by the "Chapter 12 Supplement," we can be cautious in accepting the 71% statistic at face value.
To determine why the statistic stating that 71% of adults do not use sunscreen could be misleading, we need to consider potential misrepresentations or misuse of data.
One possible misrepresentation could be the use of suspect samples. In this case, it is crucial to examine how the data was collected and whether it represents a diverse and representative sample of the adult population. If the study only focused on a specific age group, geographical region, or demographic, it might not accurately reflect the overall population.
Another possibility is asking biased questions. The wording and phrasing of the survey questions could influence the respondents' answers. For instance, if the survey question was framed in a way that made sunscreen use appear undesirable, the respondents might be more likely to indicate that they do not use sunscreen, leading to an inflated percentage.
Misleading graphs can also contribute to misinterpretation. Graphs can be manipulated to intentionally or unintentionally distort the data. For example, if the graph is not labeled correctly, the axes are disproportionate, or the scale is manipulated to accentuate the gap between sunscreen users and non-users, it could create a false impression of a larger non-user percentage.
Additionally, selective reporting may occur if the author only highlights the statistic that supports their argument without providing additional context or information. By omitting relevant data or alternative viewpoints, the author may create a biased narrative and mislead readers.
To identify which specific misrepresentation or misuse is being demonstrated in this case, further information about the article and the data source would be necessary. This would give a clearer understanding of how the statistic was obtained and whether any of the aforementioned issues were involved.