How is the calculation of expected frequency impacted by sample size?

The calculation of expected frequency is indeed influenced by sample size, and a larger sample size leads to an increase in expected frequency. This is because expected frequency is calculated based on the proportions of different categories in a given population, multiplied by the total sample size.

As sample size increases, the total number of observations allows for a more refined estimate of the proportions in each category, leading to higher expected frequencies. This also enhances the reliability of statistical tests, as larger sample sizes typically provide a more accurate representation of the population and reduce the effects of randomness or sampling error.

In contrast, smaller sample sizes can produce less stable estimates of expected frequencies, which might not reflect the true population parameters. This variability can result in less reliable statistical outcomes, making the insights derived from smaller samples less confident. Thus, larger samples facilitate a greater alignment with true proportions, increasing the expected frequencies calculated.