N-100 95% CL:
N-100 99% CL:
N-400 95% CL:
N-400 99% CL:
Confidence Intervals Assessment
N=100, 95% CI= 8.78 to 10.16 – (9.47 +/- 1.96(.35))
N=100, 99% CI= 8.62 to 10.58 – (9.60 +/- 2.58(.38))
N=400, 95% CI= 8.55 to 9.29 – (8.92 +/-1.96(.19))
N=400, 99% CI= 8.55 to 9.63 – (9.09 +/- 2.58(.21))
Confidence Intervals Explained
By using confidence intervals, it is easily to tell where the random samples will fall (Frankfort-Nachmias, Leon-Guerrero, & Davis,
2020). By using the 95% confidence level, it can be said that 95% of the data will fall between +/- 1.96 standard deviation of the mean. And
by using the 99% confidence level, it can said that 99% of the data will fall between +/- 2.58 standard deviation of the mean (Frankfort-
Nachmias, Leon-Guerrero, & Davis, 2020). For example, in the above data, it can be said that 95% of the responses from 100 people rating
their trust in the government will fall between 8.78 and 10.16.
When comparing intervals of 95% and 99%, the Estimated Standard Error of the Mean is lower for the 95% confidence level and
higher for the 99% confidence level. When looking at sample size and how that impacts the confidence interval, it can be noted that the
intervals are more spread apart with lower sample size and more closely together in a larger sample size.
I think that confidence intervals can be pretty effective. However, the saying “take it with a grain of salt” can also be beneficial here.
Confidence intervals predict the 95% and 99%probability of a score being between two scores, but it doesn’t account for all scores.
However, since the percentages are high, they can be effective.
References
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.
