As its name implies, confidence intervals provide a range of values, along with a level of confidence, to serve as an estimate of some unknown population value. Since it is rare to have access to the entire population, you must frequently rely on the confidence interval of the sample to make some inference about the population of interest. Before making accurate inferences to the population, we need to fully understand how the three key components of the interval—variability in the data, sample size, and confidence level—impact the width of the interval.For this Discussion, you will explore the relationship between these components and understand the trade-off between reducing risk in our confidence of estimates and increasing precision. Using the SPSS software, General Social Survey dataset and choose a quantitative variable that interests you.By Day 3Using SPSS:Take a random sample of 100.Calculate the 95% confidence interval for the variable.Calculate a 90% confidence interval.Take another random sample of 400.Calculate the 95% confidence interval for the variable.Calculate a 90% confidence interval.Post your results and an explanation of how different levels of confidence and sample size affect the width of the confidence interval. Next, consider the statement, “Confidence intervals are underutilized” and explain what the implications might be of using or not using confidence intervals. Provide examples based on the results of your data. Also, use your research to support your findings.Document: Data Set 2014 General Social Survey (dataset file)Note: You will need the SPSS software to open this dataset.
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