Assessment Criteria Not Good Enough (0 score <6) Good (6 score <9) Very Good (9 score 10) Score Deep understanding of theory and its applications, using qualitative methods to answer business questions Demonstrate inadequate understanding of some important concepts, methods or their applications, e.g., choose wrong methods, conduct analysis inappropriately, or interpret results incorrectly. Understand concepts and methods relatively well, analyze data using acceptable methods although not perfect; be able to derive useful information for decision making. Demonstrate sophisticated understanding for the concepts and methods; know the exact scopes and possible limitations of each method; show capability of using data analytics skills to make right business decision. Implementation and interpretation of data analysis techniques Use wrong techniques to analyze data, present inappropriate interpretations or conclusions. Choose acceptable methods to analyze data, interpretations are sensible, derive useful results. Use advanced techniques to conduct thorough and insightful analysis, interpret the results correctly, draw right conclusions based on data analysis. Ability of solving real-world problems using quantitative methods Data is inadequate or unstructured. Use inappropriate methods to analyze data, fail to retrieve useful information. Suggestions are not persuading. Collect and document just enough data, employ appropriate techniques to retrieve insightful information from data, make reasonable recommendations. Gather sufficient relevant data, conduct data analytics using scientific methods, make appropriate and powerful connections between analysis and real-world problems, provide constructive guidance in decision making. Writing and presenting, especially on organization and communication Report is inadequately written and poorly organized. Analysis is insufficient. Conclusions are unconvincing. Report is concise and clearly written. Analyze problems following scientific strategies; provide useful suggestions with detailed explanation. Report is well organized and insightfully written, includes thorough and thoughtful details. Conclusions are convincing. Total Score Comments:
Appendix. Homework Rubric for Data Analytics Course: Part 2 Assessment Criteria Not Good Enough (0 score <6) Good (6 score <9) Very Good (9 score 10) Score Interpretation of Data (qualitative) Little or no attempt to interpret data; or there are significant errors; or some data are over- or Interpret most data correctly; part of conclusions may be suspect; suggestions on future implementation are sound. Data are completely and appropriately interpreted; there is no over- or under-interpretation; draw convincing conclusions. Statistical Analysis (quantitative) Statistical methods are completely misapplied or applied but with significant errors or omissions. Choose inappropriate methods and make wrong predictions. Most statistical methods are correctly applied but more could have been done with the data. Predictions are sensible but may deviate from the true results in a large range. Statistical methods are fully and correctly applied; demonstrate superior data analysis skills; deeply mine the data and obtain useful insights for decision making. Critical evaluation of findings Blindly accept defective results; or recognize defective results but does not know how to fix them. Recognize defective results and figure out the causes; understand the main sources of errors. Show deep understanding for the sources of errors; recognize defective results and eliminates the causes. Ability to draw proper conclusions and make effective suggestions Not draw conclusions; draw incorrect conclusions; suggestions are not acceptable. Draw correct conclusion; suggestions may have potential impact on the future business. Demonstrate substantial understanding of the problem; conduct deep data analytics using correct methods; draw correct conclusions with sufficient explanation and elaboration. Total Score Comments: