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Selection bias occurs when the participants included in a study or survey are not chosen randomly and thus do not represent the overall population accurately. This can skew the results, as certain groups may be over or underrepresented.
In the case of the budget workshop survey, the attendees selected themselves by choosing to attend the event. This means they are more likely already interested or involved in the issue of sales tax increases, which could lead to biased results. Only those who felt strongly enough about the topic to attend were included, neglecting the opinions of those who did not attend, perhaps because they were indifferent, busy, or unaware.
This bias means the survey's conclusions could be misleading and do not accurately reflect the wider community's views on the sales tax issue.

A representative sample is critical in survey methodology because it ensures that the sample reflects the diversity and range of views in the entire population. This helps in generalizing findings to a larger group.
For this survey, the representation was lacking. The sample consisted merely of individuals who attended the workshop, and these comprised those with specific interests or opinions on the matter. Instead, a scientifically conducted survey would target a group selected to mirror the demographics and varied opinions of the full population, capturing diverse opinions ranging from support to opposition and neutrality.
Without this approach, any conclusions drawn from the survey may misrepresent the broader public perspective.

Random sampling is a technique used to ensure each member of the population has an equal chance of being selected for the survey. This helps to prevent bias and increases the likelihood that the sample will accurately represent the broader population.
In the case of the budget workshop survey, random sampling was not used. Instead, the participants self-selected, which compromised the randomness needed for a scientific survey. To collect scientifically valid data, researchers would ideally use methods such as drawing lots or using computerized random generators to select participants randomly from all citizens.
Implementing such methods helps safeguard against the skewed data that can result from non-random participant selection.

Scientific rigour refers to the meticulous application of careful, systematic, and objective methods during research and surveys to ensure the validity and reliability of findings.
In this instance, the lack of scientific rigour in conducting the survey is evident as there was no attempt to employ unbiased data collection methods. For surveys to have scientific rigour, they need to include standardized questions, random sampling, and a representative sample. The lack of these elements means the survey cannot provide a reliable conclusion about the general population's opinion on raising the sales tax.
In practical terms, implementing scientific rigour means setting up controls to remove biases and distributing surveys in a way that accurately analyzes the entire community's stance.