What Are Library Statistics?
Library statistics consist of quantitative and qualitative data regarding library services, their use, and the users themselves. This data serves as a crucial tool for making informed decisions. Essentially, statistics is a mathematical discipline focused on collecting, analyzing, interpreting, and drawing conclusions from data. In a library context, these methods are used to measure the direct benefits the library provides to its users and the community.
The Need for Library Statistics and Reporting
Collecting and reporting statistics is vital for the effective operation and advocacy of a library. The key reasons include:
- Effective Management: Statistics help in planning and controlling library activities, determining growth, and evaluating staff performance.
- Advocacy and Promotion: They are essential for promoting library services to a wide range of stakeholders, including policy makers, funding bodies, library staff, and users.
- Strategic Planning: Reports aimed at managers and funders are crucial for making decisions about service levels and future strategic planning.
- Demonstrating Value: In economic terms, statistics allow a library to perform a cost-benefit analysis, measure its value to the community, and present a strong justification for its budget. They can reveal "hidden success stories" by showing how libraries provide access to information for all population groups.
- Accountability: By measuring inputs (like buildings, staff, collections) and outputs (usage of services), statistics demonstrate the authorities' commitment and show whether the library is operating in a cost-effective way.
- Benchmarking: The data allows for comparisons between a library's current and past activities, as well as comparisons with other libraries.
Types and Sources of Library Statistics
Types of Statistics
Library statistics are primarily categorized into two types:
- Use Studies: These studies focus on assessing the usage patterns of information sources like books, databases, and periodicals. Examples include tracking how many books are issued or how many times a database is accessed. Data for these studies is often collected through observation and analysis of records from various library sections.
- User Studies: These studies aim to understand the overall pattern of interaction with the user community. They seek feedback on questions like how many users visited the library, what services are most important, or how satisfied users are with the services. This data is often collected through methods like questionnaires or interviews.
Combining data from both use and user studies helps library leadership make well-rounded decisions regarding staff performance, library value, and service improvements.
Sources of Statistics
Statistical data can be generated from nearly every section of a library. Key sources include:
- Internal Library Sections: Acquisition (documents purchased), processing (books processed), circulation (book issuance), and reference/periodical sections (user satisfaction, journal usage).
- Primary and Secondary Sources: Diaries, daily, weekly, monthly, and quarterly reports, gate registers, written library documents, and library software.
Data Collection and Quality
Data Collection Methods
There are several standard methods for collecting data for library statistics:
- Observation Method: Gathering data by watching behaviors or events in their natural setting, such as observing a user's search process. This can be overt (subjects are aware) or covert (subjects are unaware).
- Interview Method: A systematic way of talking to and listening to people to gather in-depth data on attitudes and beliefs. Interviews can be structured (pre-defined questions), semi-structured (key themes are covered flexibly), or unstructured (more like a casual conversation).
- Questionnaire Method: Using written or online surveys to collect data on phenomena that are not directly observable, such as opinions, values, and interests. Questionnaires can reach large groups at a low cost but do not allow for in-depth probing. A good questionnaire should be specific, short, simple, and logically ordered. It is highly recommended to pilot test a questionnaire before wide distribution.
Data Quality
The usefulness of library statistics depends on their quality. Key characteristics of high-quality data include:
- Accuracy and Timeliness: Data must be correct, reliable, comparable, and collected in a timely manner.
- Sufficient Sample Size: The larger the sample population, the more accurate the results will be.
- LibQUAL+: This is a specific suite of services offered by the Association of Research Libraries (ARL) that helps libraries solicit, track, and act upon user opinions of service quality. It uses a rigorously tested web-based survey to help libraries assess services, compare performance with peer institutions, and identify best practices.
Data Representation and Reporting
After data is collected, it must be presented clearly. The format depends on whether the data is qualitative or quantitative. A good graphical presentation should depict data correctly, summarize large datasets coherently, and be integrated with tables and verbal descriptions.
- Tables: Frequency distribution tables are commonly used to list categories and their corresponding frequencies or percentages.
- Graphical Representation of Qualitative Data:
- Pie Chart: A disk divided into proportional pieces, best used for displaying nominal (unordered) data.
- Bar Graph: Displays categories with bars that do not touch each other. It is ideal for ordinal (ordered) data.
- Graphical Representation of Quantitative Data:
- Histogram: Similar to a bar graph, but the bars touch each other to represent grouped, continuous data.
- Line and Area Graphs: Ideal for representing continuous and cumulative data over time, such as monthly usage statistics over a year.
Application and Analysis
Once collected, data can be entered into a statistical software package like MS-Excel or SPSS for analysis. These tools allow librarians to create tables and graphs to visualize data, such as the frequency of user visits or levels of user satisfaction. By calculating statistics like the mean (average) and standard deviation, librarians can analyze trends. For example, a change in the mean satisfaction score from one year to the next can indicate whether service improvements have been effective.
Ultimately, the application of statistics helps libraries measure their efficiency and performance, guide future actions, and demonstrate their value to the community and funding bodies.