Question 1

Which of the following is an example of subject matter competence?

Accepted Answer

Subject matter competence refers to having a solid understanding of the theoretical or empirical basis of your research topic. Creating a new dependent measure without reviewing established measures or conducting a statistical analysis without understanding the assumptions of the test can lead to errors and inaccuracies, and may indicate a lack of subject matter competence.

Question 2

Questionable research practices can occur during

Accepted Answer

Questionable research practices can occur at any stage of the research process, including data collection, data entry, and data analysis. It is important for researchers to be aware of these practices and take steps to prevent them.

Question 3

_________ refers to collecting data on a large number of variables but focusing only on the statistically significant relations found among them.

Accepted Answer

Data dredging is the process of extensively searching through large amounts of data in order to find statistically significant patterns or correlations, often without a prior hypothesis. This approach can lead to misleading conclusions if the findings are presented as if they were the result of testing a pre-specified hypothesis.

Question 4

__________refers to the practice of formulating hypotheses based on a study's outcome but treating them as a priori hypothesis when reporting the results of the research.

Accepted Answer

HARKing (Hypothesizing After Results are Known) is a common issue in research where researchers formulate hypotheses based on the study's outcome but report them as if they were a priori hypotheses. This can lead to false discoveries, inflated effect sizes, and difficulty replicating results.

Question 5

Professor Nowitzki writes a journal article reporting the results of studies that he never conducted. He is guilty of

Accepted Answer

Professor Nowitzki is guilty of data forgery, which involves fabricating or manipulating research data to produce false results.

Question 6

Professor Nowitzki discards data that do not support the hypothesis of his study. He reasons that doing so has produced clearer results. He is guilty of

Accepted Answer

Professor Nowitzki is engaging in data trimming, which involves selectively discarding data in order to produce clearer or more significant results. This is generally considered a form of scientific misconduct as it can lead to biased or distorted results. Data dredging, on the other hand, involves analyzing data in multiple ways until a significant result is found, and data forgery involves fabricating or falsifying data. Data torturing is a less commonly used term, but generally refers to manipulating data in some way in order to produce a desired result.

Question 7

Professor Werner drops the scores of some participants so that her results better fit her predictions. She is guilty of

Accepted Answer

Professor Werner is guilty of data trimming, which involves removing or manipulating data in order to fit a preconceived idea or hypothesis. Data dredging involves analyzing large amounts of data to find significant relationships, data forgery involves falsifying data, and data torturing involves manipulating data to fit a particular conclusion.

Question 8

Professor Werner does not initially get statistically significant results from her data, so she keeps doing different types of statistical tests until significant results turn up. She is guilty of

Accepted Answer

Data torturing refers to the practice of manipulating data through repeated testing or analysis until statistically significant results are obtained, often leading to misleading conclusions.

Question 9

Data torturing consists of

Accepted Answer

Data torturing involves repeatedly conducting different types of statistical tests on a data set until significant results turn up, which can lead to false positives and unreliable findings. Choices A, B, and C also involve unethical practices but do not specifically relate to data torturing.

Question 10

Professor Wiley periodically checks his results and, once his findings have reached significance, he stops data collection. Which questionable research practice has he engaged in?

Accepted Answer

Data snooping refers to the practice of repeatedly checking data as it is collected and deciding to stop collecting data once the results appear significant, without having predetermined a specific sample size or stopping rule. This can lead to biased results and inflated type I error rates.

Question 11

Data trimming consists of

Accepted Answer

The answer of Data trimming consists of
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Question 12

Which of the following is an example of accentuating the positive about one's research results?

Accepted Answer

Focusing on statistically significant findings highlights the positive results without manipulating the data or ignoring conflicting results. A and C both involve questionable research practices and are not examples of accentuating the positive in an ethical and valid way. D includes these questionable practices as well.

Question 13

Why is data snooping a problem?

Accepted Answer

Data snooping involves testing multiple hypotheses and selecting the one that appears to be significant, which increases the probability of detecting a false positive (Type I error). This can lead to overestimation of the significance of findings and incorrect conclusions.

Question 14

Which type of outlier might be better labeled an "accurate" data point?

Accepted Answer

Interesting outliers are data points that are significantly different from the rest of the data, but their deviation is legitimate and not an error. These outliers can provide valuable insights and information to the analysis and should be further investigated. Therefore, they can be labeled as accurate data points.

Question 15

Which of the following is NOT an appropriate method for handling outliers?

Accepted Answer

Analyzing data with and without outliers to selectively report results that best support a hypothesis is not an appropriate method because it introduces bias and undermines the integrity of the research.

Question 16

_________ is the process of transforming extreme values in a data set to a specified percentile of the range of scores.

Accepted Answer

Winsorization is a technique used to deal with outliers in a dataset. It involves transforming extreme values in the dataset to a specified percentile of the range of scores. This means that the extreme values are replaced with values that are closer to the rest of the data, thereby reducing the impact of outliers on the analysis. Piecemeal recentering, tail clipping, and HARKing are not methods of dealing with outliers.

Question 17

Which of the following about handling outliers is TRUE?

Accepted Answer

It is not recommended to remove outliers unless there is a valid reason to do so, such as if they are due to measurement error or extreme data entry mistakes. However, if outliers are removed, it is important to report the results of both analyses (with and without outliers) to ensure transparency and to avoid false conclusions.

Question 18

Data forgery consists of

Accepted Answer

Data forgery involves fabricating data or results, such as reporting results from a study that was never actually conducted.

Question 19

Professor Bulwark conducted a study of the effects of reading level on comprehension, but found no significant differences between the experimental and the control group. She changed her manipulation and ran the study again, but still found no significant differences. After once again making changes to her manipulation, the third study produced the expected results. She reports only results from Study Three. Professor Bulwark

Accepted Answer

Professor Bulwark engaged in methodological tuning, which involves adjusting the study's methods across different attempts to achieve the desired outcome. This practice can raise concerns about the reliability and validity of the findings, as it may not provide a true representation of the phenomenon being studied. Reporting only the results from the study that produced the expected outcomes without acknowledging the previous attempts can be misleading and is not considered a best practice in research ethics.

Question 20

Professor Belanger was studying age differences in depression. She hypothesized that older people would have higher depression scores than younger people, but her results showed the opposite. She rewrote her introduction to show that the unexpected finding was actually her a priori prediction. Professor Belanger has engaged in

Accepted Answer

HARKing (Hypothesizing After the Results are Known) refers to researchers altering their original hypothesis after seeing the results of their study. In this case, Professor Belanger revised her introduction to make her unexpected findings appear to be her original hypothesis, which is an example of HARKing.

Quiz 4: The Professional and Social Responsibilities of Scientists