Final answer:
To determine the amount of falsified responses, we need to understand the concept of a double coin flip differential model. The dataset does not provide the outcomes, so we cannot determine the amount of falsified responses accurately without additional information.
Step-by-step explanation:
To determine the amount of falsified "yes/no" responses in the dataset, we need to understand the concept of a double coin flip differential model. This model involves flipping two coins and recording the outcomes as either heads (H) or tails (T). In a fair model, we would expect an equal number of heads and tails in the dataset. However, if the coin is biased or unfair, the distribution of heads and tails may deviate from the expected distribution.
In the given dataset, the outcomes are not provided, so we cannot determine the amount of falsified responses. However, if the percentage of heads or tails is significantly different from 50%, it may indicate the presence of falsified responses.
To determine the amount of falsified responses accurately, we would need information about the actual outcomes of the double coin flips.