Available Until 1/22/2025

Using Statistics to Improve Library Science and Services*

For more information or to schedule this course, please contact William Kearns, PhD, at kearns@usf.edu . 

Making considered decisions on future library policy demands an astute administrator with a solid grounding in library management. While many decisions can be made using common sense, the ability to correctly interpret administrative data can enhance your service delivery and the satisfaction of your patrons. Statistical analysis of your data may just be your savior

Produce descriptive information in the form of frequency counts.

Simple frequency counts just scratch the surface and may miss fascinating relationships among measures buried in your hard-won survey or administrative data.

Worse than missing an important finding is when an administrator or researcher believes they see a relationship in their data when there, in fact, is none, and makes claims or creates policy based on erroneous interpretations. 

Used correctly, statistics can improve the reliability of your administrative decisions or research claims and help grow your reputation as an empirical evidence-based researcher in library science.

In this class, we will examine basic statistical concepts, survey instrument types and designs,  types of data, and the basic analytical tools used for each type of data. To do this, we will combine lecture and participant engagement with paper and pencil exercises and the dissection of a case study. The case study will show the value of statistics in reducing masses of data and showing relationships among data so we don’t miss the forest for the trees.

This course is an approved elective for the Level I Data Services Specialization.

Resource URLhttps://www.usf.edu/cbcs/cfs/documents/kearns-w-cv.pdf (Instructor CV)

Learning Objectives

Upon completion, the student will be able to break a research question into its core elements or variables, devise a method for quantifying and measuring those variables, and select an appropriate statistical test to evaluate the reliability of observed differences in those variables.


First half hour

  • Survey instrument types and designs
  • The 4 types of data – Nominal, Ordinal, Interval & Ratio
  • Basic analytical tools used for each type of data

Second half hour

  • Measures of Central Tendency
  • Measures of Variability
  • The simple t-test

Third half hour

  • Determining relationships between measures
  • Overview of Principle Components & Factor Analysis

MLA CE Credits: 1.5