We will be using Google Sheets to simulate anormal distributionwith a mean of 200 and a standard deviation of 7. Please note there are five parts to this question.'t forget to follow the directions in the Technology Corner for "Locking Random Numbers" after creating each sample.

First, generate a random sample of 18 data points from a normally distribution population (using the =norminv command in Google Sheets). Create a histogram where the first bin starts at 180.75 (Horizontal Axis >> Min) and the width of each bin is 3.5 (Histogram >> Bucket Size). Save that histogram as an image file and attach it here. (Please note that even though there is a drop-down for Bucket Size, you can type the value you want.)

Second, generate a random sample of 65 data points from a normally distribution population (using the =norminv command in Google Sheets). Create a histogram where the first bin starts at 180.75 and the width of each bin is 3.5. Save that histogram as an image file and attach it here

Next, generate a random sample of 280 data points from a normally distribution population (using the =norminv command in Google Sheets). Create a histogram where the first bin starts at 180.75 and the width of each bin is 3.5. Save that histogram as an image file and attach it here.

Then, generate a random sample of 2000 data points from a normally distribution population (using the =norminv command in Google Sheets). Create a histogram where the first bin starts at 180.75 and the width of each bin is 3.5. Save that histogram as an image file and attach it here.

In as much detail as possible, explain what you've noticed as the sample size increased. You should address the distribution of the sample..