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Selection bias occurs when the individuals chosen for a survey do not represent the entire target population, leading to skewed results. In a survey about job satisfaction like the one mentioned in the exercise, if certain groups of workers, like those in a particular industry or with a specific job type, are overrepresented or underrepresented, the findings might not accurately reflect the broader sentiment among all working Americans.

To improve upon this, it's crucial for researchers to employ a sampling technique that ensures each member of the target population has an equal chance of being selected. One way to achieve this is through random sampling, where participants are chosen purely by chance, mitigating the risk that the sample will be biased towards a particular subset of the population.

Nonresponse bias emerges when the individuals who choose not to respond to a survey differ significantly in their views from those who do respond. For example, in the job satisfaction survey, if those who are most discontent with their working conditions are also the least likely to return the survey, the outcomes may falsely indicate a higher level of overall job satisfaction.

Survey designers can attempt to reduce nonresponse bias by making the survey as accessible as possible, sending reminders, and providing incentives. Additionally, assessing the characteristics of non-respondents against respondents can help identify and adjust for this bias in the analysis phase.

Response bias refers to a variety of biases that influence a survey respondent to answer untruthfully or inaccurately. These can stem from the phrasing of questions, the social desirability effect (the tendency to answer questions in a manner that will be viewed favorably by others), or the desire to give 'correct' answers on topics they know little about. In the given survey about job satisfaction, response bias could have been introduced if the questions led employees to believe they should express satisfaction or if the questions were worded ambiguously.

To counteract response bias, researchers should craft clear, neutral questions and consider anonymous surveys, which can encourage more honest and less socially influenced answers.

Survey methodology encompasses the various techniques and principles employed in designing and conducting surveys, aiming to collect data that accurately reflects the opinions or behaviors of a population. Key aspects include the sampling method, question design, data collection process, and analysis technique. An effective survey methodology is critical for obtaining valid, reliable, and unbiased results.

In the case of the job satisfaction survey, improving the methodology could involve using stratified random sampling to better capture different sectors of the workforce, enhancing question clarity to reduce misunderstandings, employing various modes of data collection to increase response rates, and applying proper statistical adjustments to account for detected biases.