1. The dataset contains ten measurements of student readiness for college in columns B-K. The description of each one of them is available in the file.
2. To analyze this data, you need to create additional columns and recode the data, making low a 1, moderate, a 2, and High a 3 (you can use an IF function to do this). In this format, the highest the number, the more prepared the student is.
3. Once the data is recoded, prepare a table in ascending order of the average for each of these ten measurements.

Numbers 1-3 are done and the table is provided. Please provide a summary based on the findings?

\begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|} \hline & Org_level & Class_level & Ccol_level & InCom_level & Stress_level & Test_level & ASE_level & Connect_level & Inst_level & Bars_level \\ \hline Org_level & 1 & & & & & & & & & \\ \hline Class_level & 0.511452046 & 1 & & & & & & & & \\ \hline Ccol_level & 0.266242639 & 0.37289516 & 1 & & & & & & & \\ \hline InCom_level & 0.270193283 & 0.375236849 & 0.353154852 & 1 & & & & & & \\ \hline Stress_level & 0.060194236 & 0.222519253 & 0.03410245 & 0.155408919 & 1 & & & & & \\ \hline Test_level & -0.057455573 & 0.030053048 & -0.088584793 & -0.072647759 & 0.500071581 & 1 & & & & \\ \hline ASE_level & 0.297713949 & 0.459135623 & 0.316256046 & 0.316723379 & 0.328413558 & 0.203519964 & 1 & & & \\ \hline Connect_level & 0.159479509 & 0.316190769 & 0.213185133 & 0.374201284 & 0.305017536 & 0.163145026 & 0.337374355 & 1 & & \\ \hline Inst_level & 0.293023626 & 0.446907837 & 0.196230713 & 0.241298286 & 0.359934441 & 0.201785406 & 0.382752109 & 0.312425106 & 1 & \\ \hline Bars_level & 0.217665155 & 0.388376344 & 0.310405403 & 0.240950104 & 0.192570952 & 0.091285067 & 0.431324131 & 0.282561859 & 0.344441649 & 1 \\ \hline \end{tabular}