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2) 30 regular and double stuff Oreos* were sampled and their filling weighed. Table 1. Example frosting mass data. \begin{tabular}{|l|l|l|l|l|l|} \hline \multicolumn{7}{|l|}{ Filling Masses of Regular Oreos (g) } \\ \hline 3.00 & 2.90 & 3.20 & 3.20 & 3.20 & 3.12 \\ \hline 3.15 & 3.15 & 3.01 & 3.19 & 3.01 & 3.17 \\ \hline 3.06 & 3.14 & 3.16 & 3.31 & 3.13 & 3.23 \\ \hline 2.94 & 3.05 & 3.14 & 3.39 & 3.30 & 3.09 \\ \hline 3.10 & 3.11 & 3.24 & 3.18 & 3.10 & 3.15 \\ \hline \multicolumn{6}{|l|}{ Filling Masses of Double Stuff Oreos (g) } \\ \hline 6.11 & 6.19 & 6.27 & 6.18 & 6.34 & 6.21 \\ \hline 6.05 & 6.18 & 6.34 & 6.23 & 6.08 & 6.04 \\ \hline 6.13 & 6.65 & 6.20 & 6.12 & 6.46 & 6.37 \\ \hline 6.19 & 6.01 & 6.21 & 6.27 & 6.46 & 6.15 \\ \hline 6.15 & 6.35 & 6.24 & 6.25 & 6.32 & 6.03 \\ \hline \end{tabular} The mean of a sample measures the middle of all of the numbers. a) Calculate the mean of each sample. Along with the middle, we would like to measure how spread out the numbers are. The standard deviation measures how spread out the numbers are. A quick and dirty estimation of the standard deviation is one-sixth of the range of the data. That is, get the distance between the min and max and then divide that by six. b) Estimate the standard deviation of each sample. c) Which fillings were more spread out? d) Which fillings were more consistent? How did you decide?

          2) 30 regular and double stuff Oreos* were sampled and their filling weighed. Table 1. Example frosting mass data.
\begin{tabular}{|l|l|l|l|l|l|}
\hline \multicolumn{7}{|l|}{ Filling Masses of Regular Oreos (g) } \\
\hline 3.00 & 2.90 & 3.20 & 3.20 & 3.20 & 3.12 \\
\hline 3.15 & 3.15 & 3.01 & 3.19 & 3.01 & 3.17 \\
\hline 3.06 & 3.14 & 3.16 & 3.31 & 3.13 & 3.23 \\
\hline 2.94 & 3.05 & 3.14 & 3.39 & 3.30 & 3.09 \\
\hline 3.10 & 3.11 & 3.24 & 3.18 & 3.10 & 3.15 \\
\hline \multicolumn{6}{|l|}{ Filling Masses of Double Stuff Oreos (g) } \\
\hline 6.11 & 6.19 & 6.27 & 6.18 & 6.34 & 6.21 \\
\hline 6.05 & 6.18 & 6.34 & 6.23 & 6.08 & 6.04 \\
\hline 6.13 & 6.65 & 6.20 & 6.12 & 6.46 & 6.37 \\
\hline 6.19 & 6.01 & 6.21 & 6.27 & 6.46 & 6.15 \\
\hline 6.15 & 6.35 & 6.24 & 6.25 & 6.32 & 6.03 \\
\hline
\end{tabular}

The mean of a sample measures the middle of all of the numbers.
a) Calculate the mean of each sample.

Along with the middle, we would like to measure how spread out the numbers are. The standard deviation measures how spread out the numbers are. A quick and dirty estimation of the standard deviation is one-sixth of the range of the data. That is, get the distance between the min and max and then divide that by six.
b) Estimate the standard deviation of each sample.
c) Which fillings were more spread out?
d) Which fillings were more consistent? How did you decide?

2) 30 regular and double stuff Oreos* were sampled and their filling weighed. Table 1. Example frosting mass data.

7|l| Filling Masses of Regular Oreos (g)

3.00 2.90 3.20 3.20 3.20 3.12

3.15 3.15 3.01 3.19 3.01 3.17

3.06 3.14 3.16 3.31 3.13 3.23

2.94 3.05 3.14 3.39 3.30 3.09

3.10 3.11 3.24 3.18 3.10 3.15

6|l| Filling Masses of Double Stuff Oreos (g)

6.11 6.19 6.27 6.18 6.34 6.21

6.05 6.18 6.34 6.23 6.08 6.04

6.13 6.65 6.20 6.12 6.46 6.37

6.19 6.01 6.21 6.27 6.46 6.15

6.15 6.35 6.24 6.25 6.32 6.03

The mean of a sample measures the middle of all of the numbers.
a) Calculate the mean of each sample.

Along with the middle, we would like to measure how spread out the numbers are. The standard deviation measures how spread out the numbers are. A quick and dirty estimation of the standard deviation is one-sixth of the range of the data. That is, get the distance between the min and max and then divide that by six.
b) Estimate the standard deviation of each sample.
c) Which fillings were more spread out?
d) Which fillings were more consistent? How did you decide?

Added by Tammy J.

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