Overview

As you know, you will be taking Exam 2 on Wednesday, 13 November. This page will contain some information about my expectations for that exam - and will provide you with some direction about how to prepare for it. Please remember that the exam is worth 50 out of a PROJECTED total of 500 points.

In this exam, I need to assess how well you are understanding the information covered since the previous exam. The exam will likely consist of a mix of multiple choice questions, short-answer questions, and one or two essays. The essays may be of the nature "support or refute the following statement," where I give you a statement, and look for the way in which you agree or disagree with it.

Bibliographic search techniques

Review your notes concerning Mr. Sacolic's two presentations on the resources of the library. In particular you will be asked questions about services provided through the library's web page, and searching for articles using EBSCOhost, FirstSearch, Lexis-Nexis, and PubMed. The questions will likely be of the multiple-choice, true / false variety.

Introduction to the Internet

Review your notes and the information posted about the session dealing with the development of the Internet. Know about its history, web acronyms, and browsers, and issues related to publishing on the web, based on the links provided on that page. You might also see a BONUS question dealing with an outstanding Op-Ed piece that was published last year in the Beacon.

Data analysis, graphical presentation, inferences

Go through the sessions on this topic.

Review the session on the introduction to data. Know the difference between data, information, knowledge and wisdom. Know why people should care about data. Understand the different types of data (qualitative, quantitative, discrete, continuous). Know the definitions of population data attributes, including histograms, measures of central tendence, and measures of variability. Also know QA/QC, metadata, intellectual issues, and informatics.

Review the sessions on graphical presentation of data. Know the distinction between tabular and graphical formats. For the latter, know the attributes of pie charts and bar charts for univariate data, and when each is appropriate to use. Know the attributes of line graphs, scatterplots, regression diagrams, time series analysis, topographic analyses as discussed in class. Know star diagreams and face diagrams as they relate to multivariate data. Be prepared to identify a figure and discuss the "story" that it tells.

Review the session on drawing inference from data. Explain the relationship between inductive and deductive reasoning. Explain the philosophy behind hypothesis testing. Know the general procedure for conducting a statistical test (collect data, plug data into formula for appropriate test, compare calculated value to value in table, decide to accept or reject hypothesis). Know the pitfalls to avoid when analyzing data.

Questions in this section will be a combination of multiple choice, providing definitions, short essay, and interpreting one or two simple tables / graphs.

Spreadsheets, Excel, and data mining

Review the session in which we further explored Excel. Know the attributes of worksheets and workbooks, the auto-fill feature, menubar commands, and toolbar features TO THE LEVEL EXPLAINED IN CLASS.

This page posted and maintained by Kenneth M. Klemow, Ph.D., Biology Department, Wilkes University, Wilkes-Barre, PA 18766. (570) 408-4758, kklemow@wilkes.edu.