Statistics in LibrariesStatistics in Libraries

How to use and evaluate statistical information in library research

John McDonaldJohn McDonaldAcquisitions LibrarianAcquisitions Librarian

CaltechCaltech

What can statistics do?What can statistics do?

Statistics are just numbers…But they can provide information to:

Assess Value

Evaluate Impact

Inform Decisions

Justify Actions

Types of Library StatisticsTypes of Library StatisticsGate CountsComputer Use

Session LengthTotal Use

Reference Questions Asked and Answered

CirculationBorrowed, renewed

Collection SizeVolumes Held, Added, Cataloged

Journal UseReshelving, Copying, Circulation, Downloads

CitationsTransaction Logs

OPACs, Databases, Web logs, etc.

StatisticsStatistics

Part I: Research Design

Part II: Statistical Concepts

Part III: Evaluating Library Statistics

Research DesignResearch Design

ValidityHow well an indicator accurately measures the concept being studied. Is the technique appropriate to measure the concept being studied?

ReliabilityHow consistent is the measurement. Does it yield the same results over repeated attempts and by different researchers? How certain are the results?

GeneralizabilityHow well (or likely) can the findings be applied to other situations?

Research Design StepsResearch Design Steps

Research Question

Hypotheses

Data definitions

Data collection

Data analysis

Conclusions

Research QuestionResearch Question

What is the study designed to answer?

Why is the study important?

The more specific, the better!

Example: Should the library increase hours during finals week?

HypothesisHypothesis

A statement about the expected results.

What you will test after collecting data.

Null Hypothesis, that there is no difference between Group 1 & Group 2 or Before/After. Notated Ho = Ha

Alternate Hypothesis, that there is a difference and what that difference will be. Notated Ho ≠ Ha

Can also be directional if theory or prior research indicates : Ho > Ha

Data collectionData collection

Observation

Interviews

Focus Groups

Surveys

Transaction Logs

Others?

Data DefinitionsData DefinitionsData Scales

NominalOrdinalIntervalRatio

Frequency DistributionsFlatNormalSkewed

Variable TypesDependentIndependentExtraneous

Data ScalesData ScalesNominal: scaled without order, indicating that classifications are different. Example: Public & private institutions.

Ordinal: scaled with order, but without distance between values. Example: Carnegie classifications

Interval: scaled with order and establishes numerically equal distances on the scale. Example: Patron classification (freshman, sophomore, etc.)

Ratio: scaled with equal intervals and a zero starting point. Example: Fulltext downloads.

Nominal or ordinal variables are discrete, while interval and ratio variables are continuous

Data DistributionsData DistributionsDescribed by their kurtosis (variability) and skew (extremes)

Normal: bell shaped curve with gradual slopes

Non-normal (skewed): extreme values with steep slopes

VariablesVariables

Dependent: the variable being measured, studied, and predicted.

Independent: variables that can be manipulated or theorized to be predictors of the dependent variable.

Extraneous: variables other than the independent variables that can influence the dependent variable.

Data analysisData analysis

Descriptive statisticsMean, Median, ModeStandard Deviation

Correlational statisticsCorrelation

Inferential statisticsChi-squareRegressionANOVA

Review: Research DesignReview: Research Design Research Question

What will the study answer?

HypothesesWhat do you think the results will be?

Data definitionsWhat scales are the variables, what is the distribution, and what are the dependent, independent & extraneous variables?

Data collectionWhat is the best method for collecting the variables of interest?

Data analysis What are the proper statistical tests to use on the data?

ConclusionsWhat does the data show us or indicate?

Case StudiesCase Studies

Citation AnalysisAntelman, K (2004) “Do Open-Access Articles Have a Greater Research Impact?” College & Research Libraries News 65(5):pp. 372-382

Usage AnalysisBlecic, DD (1999) “Measurements of journal use: an analysis of the correlations between three methods.” Bull Med Libr Assoc 87(1): 20-25.

Service AnalysisNichols, J; Shaffer, B; Shockey, K. (2003). “Changing the Face of Instruction: Is Online or In-class More Effective?” College & Research Libraries, 64:5: 378-389.

““Changing the Face of Instruction…”Changing the Face of Instruction…”

Is an online tutorial as effective in teaching library instruction as a classroom setting?

H3. Students will report as much or more satisfaction with online instruction as students taking traditional instruction.

Research Question

Hypotheses H1. Students will have higher scores in information literacy tests after library instruction.

H2. Students will have the same or higher scores in info-lit tests after taking online tutorials as students taking traditional instruction.

Variables: Test scores & survey resultsData Collection: Pretest/Posttest & Survey

““Changing the Face of Instruction…”Changing the Face of Instruction…”

Variables & Data Collection

Statistical Tests

Conclusions Accept H1: Instruction improves literacy.

Desc Stats incl. mean, standard deviation, standard error, T-tests (1 & 2 tailed)

Accept H3 alternative hypothesis – Student satisfaction is equal with both methods.

Accept H2 alternative hypothesis – Online has no significant difference from traditional.

DiscussionDiscussion

Questions about developing Research Questions? About Data Definitions, Data Collection, or Data Analysis?

What Research Questions need to be answered at the College Library?

Which of these can be analyzed using statistical methods?

My favorite statistic

Baseball is 90% mental – the other half is physical.