Using the SPSS software, General Social Survey dataset and choose a quantitative variable that interests you. By Day 3 Using SPSS: 1. Take a random sample of 100. 2. Calculate the 95% confidence interval for the variable. 3. Calculate a 90% confidence interval. 4. Take another random sample of 400. 5. Calculate the 95% confidence interval for the variable. 6. 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. Confidence intervals are calculated from a variable of sample data and is an estimate of a range of values which likely include the unknown population parameter (Frankfort-Nachmias, & Leon-Guerrero, 2018) Increasing a sample size decreases the width of the confidence intervals because the standard error decreases. For example, in the sample size of 100 the standard error was 0.284 with a 95% confidence interval that the highest year of school completed was between 13.96 and 15.08. Using a 400-person sample, the standard error becomes 0.158 with a 95% confidence interval that the highest grade completed was between 13.7 and 14.31. In short, a larger sample size is a better estimator of the population parameter. For the statement, " Confidence intervals are underutilized" it means the confidence intervals are not being used to their full potential. Confidence interval has many benefits of use