The OECD Programme for International Student Assessment (PISA) surveys collected data on students’ performances in reading, mathematics and science, as well as contextual information on students’ background, home characteristics and school factors which could influence performance. This publication includes detailed information on how to analyse the PISA data, enabling researchers to both reproduce the initial results and to undertake further analyses. In addition to the inclusion of the necessary techniques, the manual also includes a detailed account of the PISA 2006 database and worked examples providing full syntax in SPSS.

Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

SPSS Data sets for study 1 to 3

This publication provides all the information required to understand the PISA 2003 educational performance database and perform analyses in accordance with the complex methodologies used to collect and process the data. It enables researchers to both reproduce the initial results and to undertake further analyses. The publication includes introductory chapters explaining the statistical theories and concepts required to analyse the PISA data, including full chapters on how to apply replicate weights and undertake analyses using plausible values; worked examples providing full syntax in SPSS®; and a comprehensive description of the OECD PISA 2003 international database. The PISA 2003 database includes micro-level data on student educational performance for 41 countries collected in 2003, together with students’ responses to the PISA 2003 questionnaires and the test questions. A similar manual is available for SAS users.

This dataset is about books. It has 2 rows and is filtered where the book is Data analysis with SPSS : a first course in applied statistics. It features 7 columns including author, publication date, language, and book publisher.

The 2008 National Survey of Drinking and Driving Attitudes and Behaviors was composed of a single questionnaire administered to a sample of randomly selected individuals 16 and older, with ages 16 through 24 over-sampled. The respondents were asked about their drinking behavior, their drinking and driving behavior, use of designated drivers, their hosting events in which drinking occurred, risks they perceive associated with drinking and driving, experience with anti-DWI enforcement activity, and their attitudes concerning major intervention strategies.The survey was administered from September 10, 2008 to December 22, 2008. A total of 6,999 respondents completed the survey, including 5,392 landline interviews and 1,607 cell phone interviews. The total number of completed interviews for each of the four Census regions (Northeast, Midwest, South, and West) was 1,409, 1,654, 2,390, and 1,546, respectively.

Data set from PLOS ONE Article Published Entitled: Western Lowland Gorillas Signal Selectively Using Odor

This site contains a series of SPSS assignments, which will take you from the basics of opening data files to the complexities of creating a professional conference poster. These assignments use real data that were collected at the University of Nevada, Las Vegas. Each assignment has two parts: the first includes step-by-step instructions and the second provides extra practice. In later assignments, you will re-use the skills you learned in earlier assignments. After completing these assignments, you will be better prepared for the rigors of the workplace and for graduate-level research.

The data set is the data acquired through a survey among chatbot users of online travel agencies (OTAs) in India.

This SPPS document has been processed from an Excel spreadsheet questionnaire about the frequency, form of procrastination, and influences on behaviour when trying to undertake stages of a design process that was completed by 146 students and 9 staff within a UK design and creative arts school.

This is a dataset analysis regarding our previous research and the current research. it is the result of our observations over 3 years of monitoring and is provided briefly within our 1st publication: https://doi.org/10.5281/zenodo.10407923.

Raw data used for analysis

GENERAL INFORMATION

Title of Dataset: A dataset from a survey investigating disciplinary differences in data citation

Date of data collection: January to March 2022

Collection instrument: SurveyMonkey

Funding: Alfred P. Sloan Foundation

SHARING/ACCESS INFORMATION

Licenses/restrictions placed on the data: These data are available under a CC BY 4.0 license

Links to publications that cite or use the data:

Gregory, K., Ninkov, A., Ripp, C., Peters, I., & Haustein, S. (2022). Surveying practices of data citation and reuse across disciplines. Proceedings of the 26th International Conference on Science and Technology Indicators. International Conference on Science and Technology Indicators, Granada, Spain. https://doi.org/10.5281/ZENODO.6951437

Gregory, K., Ninkov, A., Ripp, C., Roblin, E., Peters, I., & Haustein, S. (2023). Tracing data:
A survey investigating disciplinary differences in data citation. Zenodo. https://doi.org/10.5281/zenodo.7555266

DATA & FILE OVERVIEW

File List

• Filename: MDCDatacitationReuse2021Codebookv2.pdf
  Codebook
• Filename: MDCDataCitationReuse2021surveydatav2.csv
  Dataset format in csv
• Filename: MDCDataCitationReuse2021surveydatav2.sav
  Dataset format in SPSS
• Filename: MDCDataCitationReuseSurvey2021QNR.pdf
  Questionnaire

Additional related data collected that was not included in the current data package: Open ended questions asked to respondents

METHODOLOGICAL INFORMATION

Description of methods used for collection/generation of data:

The development of the questionnaire (Gregory et al., 2022) was centered around the creation of two main branches of questions for the primary groups of interest in our study: researchers that reuse data (33 questions in total) and researchers that do not reuse data (16 questions in total). The population of interest for this survey consists of researchers from all disciplines and countries, sampled from the corresponding authors of papers indexed in the Web of Science (WoS) between 2016 and 2020.

Received 3,632 responses, 2,509 of which were completed, representing a completion rate of 68.6%. Incomplete responses were excluded from the dataset. The final total contains 2,492 complete responses and an uncorrected response rate of 1.57%. Controlling for invalid emails, bounced emails and opt-outs (n=5,201) produced a response rate of 1.62%, similar to surveys using comparable recruitment methods (Gregory et al., 2020).

Methods for processing the data:

Results were downloaded from SurveyMonkey in CSV format and were prepared for analysis using Excel and SPSS by recoding ordinal and multiple choice questions and by removing missing values.

Instrument- or software-specific information needed to interpret the data:

The dataset is provided in SPSS format, which requires IBM SPSS Statistics. The dataset is also available in a coded format in CSV. The Codebook is required to interpret to values.

DATA-SPECIFIC INFORMATION FOR: MDCDataCitationReuse2021surveydata

Number of variables: 95

Number of cases/rows: 2,492

Missing data codes: 999 Not asked

Refer to MDCDatacitationReuse2021Codebook.pdf for detailed variable information.

Data from study investigating the preferences of the adult Danish population for five specific protective features of AI systems and implementation across a range of eight different use cases in the public and commercial sectors ranging from medical diagnostics to the issuance of parking tickets.

TABLES AND FIGURES DYSMENORHEA

Research database of Russian female stock market investors who started their activities from 2006 to 2019. The main characteristics of modern women investors in the Russian stock market are given: age, education, marital status, place of residence, profession, monthly income per family member, attitude to the Russian privatization of the 90s, investment strategies of women investors.

Tasks, data files, and SPSS analysis scripts for the paper "People in pain make poorer decisions".

Data is based on factor analysis of newly developed tool for professionalism assessment

This is a translation of a workshop that describes the procedures for manipulating microdata files using SPSS software. It also points out a few things to keep in mind when opening a file or data extraction created by Statistics Canada. Translation of: "Un pas de plus avec SPSS".

This presentation describes what aggregate data are. This is followed by a computing exercise that demonstrates how to aggregate data with SPSS. (Note: Data associated with this presentation is available on the DLI FTP site under folder 1873-217.)