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Review of the Semester

Review of the Semester. We in this class are part of a rising trend. Some Good News.

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Review of the Semester

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  1. Review of the Semester We in this class are part of a rising trend

  2. Some Good News • “Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions.”

  3. The Bad News: There is competition“In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates.” http://nyti.ms/146mC6R

  4. Does this look familiar? • As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, • master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem. • Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

  5. Entrepreneurial:“The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.” • Job Examples: for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity. • Or apply their skills to e-commerce, where data about users’ browsing history is gold.

  6. Regression:“This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,”

  7. More Good News • Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. • There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data. • “This has become relevant to every company,” said Michael Chui, a principal at McKinsey who has studied the field. “There’s a war for this type of talent.”

  8. So is it working?

  9. You’ve come to the right place!

  10. Anonymous feedback: • “While it was not clear to me during my time at Le Moyne that I was receiving a superior education, it became very clear once in graduate school at XXX University. I had a firm grasp on research methods, thanks to Dr. XXX and the time he spent with me…. In fact, credit can be given to all of Le Moyne's staff. By the time I got to graduate school, I could focus on subject matter instead of form. A majority of students from other undergraduate programs could not say the same. Most importantly, Le Moyne enabled me to be confident, to believe in myself, to take chances, and to be successful in whatever I do!”

  11. Course Objectives • This course is intended to refine your applied academic skills to better prepare you for professional careers of leadership in public administration, business administration, economics, criminal justice and consulting. Upon completion of this course, class members should be able to: • Explain the use of the CLASS scale (Community Need, Logical Approach, Assessment Plan, Sustainability Plan and Special interest area) in philanthropy and grantmaking relating to the career area of your choice. • (Community Need) Gather, tally and present data in charts and graphs to show basic numerical information and explain how these skills are important in needs assessment and other program/policy applications. • (Logical Approach) Create and demonstrate the use of Logic Models for program/policy design and evaluation. • (Assessment Plan) Demonstrate ability to design an appropriate evaluation design. This includes articulating the difference between formative and summative evaluation, and differentiating between experimental, quasi-experimental, and non-experimental evaluation designs. • (Assessment Plan) Demonstrate ability to select and apply appropriate statistical approaches to evaluating results in the policy process, including using SPSS to perform Chi-Square, T-Test, OLS and Logistic Regression analyses. • (Sustainability Plan) Produce a flexible budget spreadsheet to accommodate a hypothetical social program and use this spreadsheet to display the importance of budgeting in social policies and programs. • OPTIONAL -(Special Interest Area) Locate, access, and import policy-relevant data into ArcView GIS and present this data in comprehensible geographic format.

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