In the context of this exercise on determining the necessary data during the data science process, what are common values used for margin of error and confidence level?
Depending on how accurate you wish the data to be, you can essentially choose whatever values you want for margin of error and confidence. However, there is always a tradeoff, as more accurate data requires more work due to a larger sample size needed.
The margin of error determines how much the true value is from what we obtained in our survey. As you increase the margin of error, you will need a smaller sample size, but it will be less accurate, so smaller values are better. Usually, a value of around 5% is used for the margin of error.
The confidence level is used to give the probability that the margin of error contains the true proportion of the population. The larger this value, the more accurate, and “confident”, we can be that the data is closer to the actual population’s. The most common value used for confidence level is 95%. However, 90% and 99% are also commonly used.