Which of the following is a statistical reasoning topic
a. False Discovery Rate (FDR) in Multiple Hypothesis Testing
b. Survivor Bias
c. Gamblers Bias
d. Coninirmation Bias
e. All of the above
The correct answer and explanation is:
The correct answer is a. False Discovery Rate (FDR) in Multiple Hypothesis Testing.
Explanation:
False Discovery Rate (FDR) refers to the proportion of false positives (incorrectly rejecting the null hypothesis) among all positive results in multiple hypothesis testing. When many hypotheses are tested simultaneously, the chance of observing a false positive increases, even if the null hypothesis is true. FDR is used to control this risk by adjusting p-values in multiple comparisons to ensure that the rate of false positives remains below a certain threshold.
FDR is an essential statistical concept in fields like genomics, where thousands of tests may be conducted at once, making it crucial to control for Type I errors. Techniques such as the Benjamini-Hochberg procedure are used to adjust for FDR, ensuring that the discoveries made are more likely to be true.
Survivor Bias is a type of selection bias that occurs when individuals or data points that “survive” a process or condition are disproportionately included in the analysis, while those that do not survive are ignored. This leads to incorrect conclusions about the probability of success or failure, but it’s not inherently a statistical reasoning topic; it is more of a data collection or observational bias.
Gamblers Bias refers to cognitive biases like the gambler’s fallacy, where people incorrectly believe that past events influence future outcomes in a random process (e.g., assuming a coin flip will land heads after several tails). While it’s related to reasoning, it isn’t a statistical concept in the formal sense, but more a psychological bias affecting decision-making.
Confirmation Bias is a cognitive bias where individuals focus on information that supports their existing beliefs while ignoring or downplaying contrary evidence. It’s relevant to data interpretation but is not a formal statistical concept either.
Thus, FDR is the only one of these options that directly relates to statistical reasoning and hypothesis testing.