What the results mean
you are interviewing a sample of respondents drawn from a population,
the mean value you obtain at a certain question may be different from
the mean value you would obtain if all members of the population where
interviewed (true population mean). There is some likelihood, called
the confidence level, that the true population mean falls within a
particular range, called the confidence interval, around the mean value
you obtained from your sample.
example, if you interview 500 people, and obtain a mean value to a
question of 25.0 with a standard deviation of 12.5, and you desire your
confidence level to be 95%, the corresponding confidence interval is ±
1.1. That is to say that you are 95% certain that the true population
mean falls into the range from 23.9 to 26.1.
Step 1: Confidence Level
The value chosen in Step 1 determines the confidence level of your results. It tells you how often the true percentage of the population would fall within the confidence interval of results obtained in your survey. For most marketing research studies, a confidence level of 95% is used.
Confidence level is related to the level of significance (α ). A 95% Confidence level corresponds to α = .05. If the Level of significance (α) = .05, that means that there is one chance in twenty that the true population mean falls outside the range given.
Step 2: Sample Size
This is the number of respondents who answered the question.
Step 3: Enter Observed Mean
This is the mean response given by respondents in the sample.
Step 4: Enter Observed Standard Deviation
This is the standard deviation of the mean entered at Step 3.
It is assumed that your sample represents a random sample of the relevant population.