100+ datasets found
  1. f

    SPSS Statistics Data file.

    • plos.figshare.com
    bin
    Updated May 31, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Filip Ventorp; Anna Gustafsson; Lil Träskman-Bendz; Åsa Westrin; Lennart Ljunggren (2023). SPSS Statistics Data file. [Dataset]. http://doi.org/10.1371/journal.pone.0140052.s001
    Explore at:
    binAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Filip Ventorp; Anna Gustafsson; Lil Träskman-Bendz; Åsa Westrin; Lennart Ljunggren
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    A SPSS file with data used in the statistical analysis. Covariates were excluded in the file due to restrictions of the ethical permission. However a complete file is provided for researchers after request at publication@ventorp.com. (SAV)

  2. m

    SPSS FILE

    • data.mendeley.com
    Updated Apr 9, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dr Khaula Noreen (2024). SPSS FILE [Dataset]. http://doi.org/10.17632/7jhrkt7ryk.1
    Explore at:
    Dataset updated
    Apr 9, 2024
    Authors
    Dr Khaula Noreen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

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

  3. spss data.sav

    • figshare.com
    bin
    Updated Mar 23, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    AHMED alradaideh; Alberto Ibáñez Fernández (2022). spss data.sav [Dataset]. http://doi.org/10.6084/m9.figshare.19403006.v1
    Explore at:
    binAvailable download formats
    Dataset updated
    Mar 23, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    AHMED alradaideh; Alberto Ibáñez Fernández
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data was collected from two different studies conducted for the undergraduate student E-learning fall semester 2020 experience at the University of Science and Technology Fujairah (USTF) in the United Arab Emirates. The two studies were conducted using an online questionnaire via Google Forms. Students were invited to participate voluntarily by email. They were asked to answer questions regarding their distance learning experience during their 2020 academic year.

  4. o

    SPSS Assignments for Introductory Statistics

    • osf.io
    Updated Aug 23, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Kimberly Barchard; Leiszle Lapping-Carr; Kristy Barraza; Matthew Helm; Sahara Gabales; victoria mcdowell; Eden Thiess (2021). SPSS Assignments for Introductory Statistics [Dataset]. https://osf.io/5qy2p
    Explore at:
    Dataset updated
    Aug 23, 2021
    Dataset provided by
    Center For Open Science
    Authors
    Kimberly Barchard; Leiszle Lapping-Carr; Kristy Barraza; Matthew Helm; Sahara Gabales; victoria mcdowell; Eden Thiess
    Description

    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.

  5. m

    SPSS Data sets

    • data.mendeley.com
    Updated Feb 11, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Heribert Wienkamp (2019). SPSS Data sets [Dataset]. http://doi.org/10.17632/6fybfs4zy4.1
    Explore at:
    Dataset updated
    Feb 11, 2019
    Authors
    Heribert Wienkamp
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    SPSS Data sets for study 1 to 3

  6. SPSS Data File

    • figshare.com
    tar
    Updated Oct 23, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Hamzeh Dodeen (2023). SPSS Data File [Dataset]. http://doi.org/10.6084/m9.figshare.24422323.v1
    Explore at:
    tarAvailable download formats
    Dataset updated
    Oct 23, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Hamzeh Dodeen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Statistic anxiety is the feeling of worrying and tension that students experience when taking statistics courses, especially in social sciences programs. Studying statistic anxiety and the related variables is crucial because this anxiety negatively and significantly affects students’ achievement and learning.

  7. l

    People in pain make poorer decisions: tasks, data files and SPSS analysis...

    • repository.lboro.ac.uk
    xlsx
    Updated Aug 21, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Nina Attridge; Jayne Pickering; Matthew Inglis; Edmund Keogh; Christopher Eccleston (2019). People in pain make poorer decisions: tasks, data files and SPSS analysis syntax [Dataset]. http://doi.org/10.17028/rd.lboro.7068413.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Aug 21, 2019
    Dataset provided by
    Loughborough University
    Authors
    Nina Attridge; Jayne Pickering; Matthew Inglis; Edmund Keogh; Christopher Eccleston
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

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

  8. d

    Download statistics GESIS Data Archive

    • da-ra.de
    Updated Apr 27, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GESIS - Data Archive for the Social Sciences (2018). Download statistics GESIS Data Archive [Dataset]. http://doi.org/10.4232/1.12979
    Explore at:
    Dataset updated
    Apr 27, 2018
    Dataset provided by
    GESIS Data Archive
    da|ra
    Authors
    GESIS - Data Archive for the Social Sciences
    Time period covered
    Jan 1, 2004 - Dec 31, 2017
    Description

    General information: The data sets contain information on how often materials of studies available through GESIS: Data Archive for the Social Sciences were downloaded and/or ordered through one of the archive´s plattforms/services between 2004 and 2017.

    Sources and plattforms: Study materials are accessible through various GESIS plattforms and services: Data Catalogue (DBK), histat, datorium, data service (and others).

    Years available: - Data Catalogue: 2012-2017 - data service: 2006-2017 - datorium: 2014-2017 - histat: 2004-2017

    Data sets: Data set ZA6899_Datasets_only_all_sources contains information on how often data files such as those with dta- (Stata) or sav- (SPSS) extension have been downloaded. Identification of data files is handled semi-automatically (depending on the plattform/serice). Multiple downloads of one file by the same user (identified through IP-address or username for registered users) on the same days are only counted as one download.

    Data set ZA6899_Doc_and_Data_all_sources contains information on how often study materials have been downloaded. Multiple downloads of any file of the same study by the same user (identified through IP-address or username for registered users) on the same days are only counted as one download.

    Both data sets are available in three formats: csv (quoted, semicolon-separated), dta (Stata v13, labeled) and sav (SPSS, labeled). All formats contain identical information.

    Variables: Variables/columns in both data sets are identical. za_nr ´Archive study number´ version ´GESIS Archiv Version´ doi ´Digital Object Identifier´ StudyNo ´Study number of respective study´ Title ´English study title´ Title_DE ´German study title´ Access ´Access category (0, A, B, C, D, E)´ PubYear ´Publication year of last version of the study´ inZACAT ´Study is currently also available via ZACAT´ inHISTAT ´Study is currently also available via HISTAT´ inDownloads ´There are currently data files available for download for this study in DBK or datorium´ Total ´All downloads combined´ downloads_2004 ´downloads/orders from all sources combined in 2004´ [up to ...] downloads_2017 ´downloads/orders from all sources combined in 2017´ d_2004_dbk ´downloads from source dbk in 2004´ [up to ...] d_2017_dbk ´downloads from source dbk in 2017´ d_2004_histat ´downloads from source histat in 2004´ [up to ...] d_2017_histat ´downloads from source histat in 2017´ d_2004_dataservice ´downloads/orders from source dataservice in 2004´ [up to ...] d_2017_dataservice ´downloads/orders from source dataservice in 2017´

    More information is available within the codebook.

  9. l

    SPSS processed data set of Procrastination survey data

    • repository.lboro.ac.uk
    bin
    Updated Sep 3, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ruth Welsh; George Torrens; Simon Downs; Jasmine Rose May Swalwell; Salman Asghar; Yi Wang (2024). SPSS processed data set of Procrastination survey data [Dataset]. http://doi.org/10.17028/rd.lboro.26871157.v1
    Explore at:
    binAvailable download formats
    Dataset updated
    Sep 3, 2024
    Dataset provided by
    Loughborough University
    Authors
    Ruth Welsh; George Torrens; Simon Downs; Jasmine Rose May Swalwell; Salman Asghar; Yi Wang
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    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.

  10. RAAAP-2 SPSS Data Cleansing syntax files

    • figshare.com
    txt
    Updated May 16, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Simon Kerridge (2023). RAAAP-2 SPSS Data Cleansing syntax files [Dataset]. http://doi.org/10.6084/m9.figshare.18972992.v2
    Explore at:
    txtAvailable download formats
    Dataset updated
    May 16, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Simon Kerridge
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    These two syntax files were used to convert the SPSS data output from the Qualtrics survey tool into the 17 cleansed and anonymised RAAAP-2 datasets form the 2019 international survey of research managers and administrators. The first creates and interim cleansed and anonymised datafile, the latter splits these into separate datasets to ensure anonymisation. Errata (16/6/23): v13 of the main Data Cleansing file has an error (two variables were missing value labels). This file has now been replaced with v14, and the Main Dataset has also been updated with the new data.

  11. r

    Online survey data for the 2017 Aesthetic value project (NESP 3.2.3,...

    • researchdata.edu.au
    bin
    Updated 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Becken, Susanne, Professor; Connolly, Rod, Professor; Stantic, Bela, Professor; Scott, Noel, Professor; Mandal, Ranju, Dr; Le, Dung (2019). Online survey data for the 2017 Aesthetic value project (NESP 3.2.3, Griffith Institute for Tourism Research) [Dataset]. https://researchdata.edu.au/online-survey-2017-tourism-research/1440092
    Explore at:
    binAvailable download formats
    Dataset updated
    2019
    Dataset provided by
    eAtlas
    Authors
    Becken, Susanne, Professor; Connolly, Rod, Professor; Stantic, Bela, Professor; Scott, Noel, Professor; Mandal, Ranju, Dr; Le, Dung
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Time period covered
    Jan 28, 2017 - Jan 28, 2018
    Description

    This dataset consists of three data folders including all related documents of the online survey conducted within the NESP 3.2.3 project (Tropical Water Quality Hub) and a survey format document representing how the survey was designed. Apart from participants’ demographic information, the survey consists of three sections: conjoint analysis, picture rating and open question. Correspondent outcome of these three sections are downloaded from Qualtrics website and used for three different data analysis processes.

    Related data to the first section “conjoint analysis” is saved in the Conjoint analysis folder which contains two sub-folders. The first one includes a plan file of SAV. Format representing the design suggestion by SPSS orthogonal analysis for testing beauty factors and 9 photoshoped pictures used in the survey. The second (i.e. Final results) contains 1 SAV. file named “data1” which is the imported results of conjoint analysis section in SPSS, 1 SPS. file named “Syntax1” representing the code used to run conjoint analysis, 2 SAV. files as the output of conjoint analysis by SPSS, and 1 SPV file named “Final output” showing results of further data analysis by SPSS on the basis of utility and importance data.

    Related data to the second section “Picture rating” is saved into Picture rating folder including two subfolders. One subfolder contains 2500 pictures of Great Barrier Reef used in the rating survey section. These pictures are organised by named and stored in two folders named as “Survey Part 1” and “Survey Part 2” which are correspondent with two parts of the rating survey sections. The other subfolder “Rating results” consist of one XLSX. file representing survey results downloaded from Qualtric website.

    Finally, related data to the open question is saved in “Open question” folder. It contains one csv. file and one PDF. file recording participants’ answers to the open question as well as one PNG. file representing a screenshot of Leximancer analysis outcome.

    Methods: This dataset resulted from the input and output of an online survey regarding how people assess the beauty of Great Barrier Reef. This survey was designed for multiple purposes including three main sections: (1) conjoint analysis (ranking 9 photoshopped pictures to determine the relative importance weights of beauty attributes), (2) picture rating (2500 pictures to be rated) and (3) open question on the factors that makes a picture of the Great Barrier Reef beautiful in participants’ opinion (determining beauty factors from tourist perspective). Pictures used in this survey were downloaded from public sources such as websites of the Tourism and Events Queensland and Tropical Tourism North Queensland as well as tourist sharing sources (i.e. Flickr). Flickr pictures were downloaded using the key words “Great Barrier Reef”. About 10,000 pictures were downloaded in August and September 2017. 2,500 pictures were then selected based on several research criteria: (1) underwater pictures of GBR, (2) without humans, (3) viewed from 1-2 metres from objects and (4) of high resolution.

    The survey was created on Qualtrics website and launched on 4th October 2017 using Qualtrics survey service. Each participant rated 50 pictures randomly selected from the pool of 2500 survey pictures. 772 survey completions were recorded and 705 questionnaires were eligible for data analysis after filtering unqualified questionnaires. Conjoint analysis data was imported to IBM SPSS using SAV. format and the output was saved using SPV. format. Automatic aesthetic rating of 2500 Great Barrier Reef pictures –all these pictures are rated (1 – 10 scale) by at least 10 participants and this dataset was saved in a XLSX. file which is used to train and test an Artificial Intelligence (AI)-based system recognising and assessing the beauty of natural scenes. Answers of the open-question were saved in a XLSX. file and a PDF. file to be employed for theme analysis by Leximancer software.

    Further information can be found in the following publication: Becken, S., Connolly R., Stantic B., Scott N., Mandal R., Le D., (2018), Monitoring aesthetic value of the Great Barrier Reef by using innovative technologies and artificial intelligence, Griffith Institute for Tourism Research Report No 15.

    Format: The Online survey dataset includes one PDF file representing the survey format with all sections and questions. It also contains three subfolders, each has multiple files. The subfolder of Conjoint analysis contains an image of the 9 JPG. Pictures, 1 SAV. format file for the Orthoplan subroutine outcome and 5 outcome documents (i.e. 3 SAV. files, 1 SPS. file, 1 SPV. file). The subfolder of Picture rating contains a capture of the 2500 pictures used in the survey, 1 excel file for rating results. The subfolder of Open question includes 1 CSV. file, 1 PDF. file representing participants’ answers and one PNG. file for the analysis outcome.

    Data Dictionary:

    Card 1: Picture design option number 1 suggested by SPSS orthogonal analysis. Importance value: The relative importance weight of each beauty attribute calculated by SPSS conjoint analysis. Utility: Score reflecting influential valence and degree of each beauty attribute on beauty score. Syntax: Code used to run conjoint analysis by SPSS Leximancer: Specialised software for qualitative data analysis. Concept map: A map showing the relationship between concepts identified Q1_1: Beauty score of the picture Q1_1 by the correspondent participant (i.e. survey part 1) Q2.1_1: Beauty score of the picture Q2.1_1 by the correspondent participant (i.e. survey part 2) Conjoint _1: Ranking of the picture 1 designed for conjoint analysis by the correspondent participant

    References: Becken, S., Connolly R., Stantic B., Scott N., Mandal R., Le D., (2018), Monitoring aesthetic value of the Great Barrier Reef by using innovative technologies and artificial intelligence, Griffith Institute for Tourism Research Report No 15.

    Data Location:

    This dataset is filed in the eAtlas enduring data repository at: data esp3\3.2.3_Aesthetic-value-GBR

  12. f

    Data_Sheet_1_Raw Data Visualization for Common Factorial Designs Using SPSS:...

    • frontiersin.figshare.com
    zip
    Updated Jun 2, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Florian Loffing (2023). Data_Sheet_1_Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial.ZIP [Dataset]. http://doi.org/10.3389/fpsyg.2022.808469.s001
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    Frontiers
    Authors
    Florian Loffing
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  13. m

    Questionnaire data on land use change of Industrial Heritage: Insights from...

    • data.mendeley.com
    Updated Jul 20, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Arsalan Karimi (2023). Questionnaire data on land use change of Industrial Heritage: Insights from Decision-Makers in Shiraz, Iran [Dataset]. http://doi.org/10.17632/gk3z8gp7cp.2
    Explore at:
    Dataset updated
    Jul 20, 2023
    Authors
    Arsalan Karimi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Iran, Shiraz
    Description

    The survey dataset for identifying Shiraz old silo’s new use which includes four components: 1. The survey instrument used to collect the data “SurveyInstrument_table.pdf”. The survey instrument contains 18 main closed-ended questions in a table format. Two of these, concern information on Silo’s decision-makers and proposed new use followed up after a short introduction of the questionnaire, and others 16 (each can identify 3 variables) are related to the level of appropriate opinions for ideal intervention in Façade, Openings, Materials and Floor heights of the building in four values: Feasibility, Reversibility, Compatibility and Social Benefits. 2. The raw survey data “SurveyData.rar”. This file contains an Excel.xlsx and a SPSS.sav file. The survey data file contains 50 variables (12 for each of the four values separated by colour) and data from each of the 632 respondents. Answering each question in the survey was mandatory, therefor there are no blanks or non-responses in the dataset. In the .sav file, all variables were assigned with numeric type and nominal measurement level. More details about each variable can be found in the Variable View tab of this file. Additional variables were created by grouping or consolidating categories within each survey question for simpler analysis. These variables are listed in the last columns of the .xlsx file. 3. The analysed survey data “AnalysedData.rar”. This file contains 6 “SPSS Statistics Output Documents” which demonstrate statistical tests and analysis such as mean, correlation, automatic linear regression, reliability, frequencies, and descriptives. 4. The codebook “Codebook.rar”. The detailed SPSS “Codebook.pdf” alongside the simplified codebook as “VariableInformation_table.pdf” provides a comprehensive guide to all 50 variables in the survey data, including numerical codes for survey questions and response options. They serve as valuable resources for understanding the dataset, presenting dictionary information, and providing descriptive statistics, such as counts and percentages for categorical variables.

  14. u

    SPSS file of data on handaxes from the sites of Tabun, Khall Amayshan 4, and...

    • rdr.ucl.ac.uk
    tar
    Updated Oct 26, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ceri Shipton (2023). SPSS file of data on handaxes from the sites of Tabun, Khall Amayshan 4, and Khabb Musayyib [Dataset]. http://doi.org/10.5522/04/22698625.v1
    Explore at:
    tarAvailable download formats
    Dataset updated
    Oct 26, 2023
    Dataset provided by
    University College London
    Authors
    Ceri Shipton
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    SPSS file containing variables recorded on handaxes from the later Acheulean sites of Tabun, Khall Amayshan, and Khabb Musayyib in southwest Asia. The variables include weight, surface area, material, blank type, and number of scars.

  15. d

    Data from: Technical Note on the Extraction of StatCan Data Files

    • dataone.org
    Updated Dec 28, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Rachad Antonius (2023). Technical Note on the Extraction of StatCan Data Files [Dataset]. http://doi.org/10.5683/SP3/QCFQ3X
    Explore at:
    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Rachad Antonius
    Description

    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".

  16. U

    Statistical Computing: SPSS

    • dataverse.unc.edu
    • dataverse-staging.rdmc.unc.edu
    • +1more
    pdf +3
    Updated Feb 26, 2014
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    UNC Dataverse (2014). Statistical Computing: SPSS [Dataset]. https://dataverse.unc.edu/dataset.xhtml;jsessionid=733b62bc52cc98c0fd30e07a5b3d?persistentId=hdl%3A1902.29%2F11631&version=&q=&fileAccess=Public&fileTag=&fileSortField=type&fileSortOrder=
    Explore at:
    xls(5632), text/plain; charset=us-ascii(145), tsv(3697), pdf(32311), pdf(30997), tsv(125503), tsv(20759), pdf(47997), tsv(12290), tsv(10257), tsv(17062)Available download formats
    Dataset updated
    Feb 26, 2014
    Dataset provided by
    UNC Dataverse
    Description

    Part 1 of the course will offer an introduction to SPSS and teach how to work with data saved in SPSS format. Part 2 will demonstrate how to work with SPSS syntax, how to create your own SPSS data files, and how to convert data in other formats to SPSS. Part 3 will teach how to append and merge SPSS files, demonstrate basic analytical procedures, and show how to work with SPSS graphics.

  17. d

    Data from: Complex Files: Pasting and Cutting with SPSS

    • search.dataone.org
    Updated Dec 28, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Wendy Watkins (2023). Complex Files: Pasting and Cutting with SPSS [Dataset]. http://doi.org/10.5683/SP3/BDSLOQ
    Explore at:
    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Wendy Watkins
    Description

    Some surveys contain multiple units of observation, while others come in many parts. This workshop will give participants hands-on experience using both types of files. The General Social Survey, Cycle 8 and the Canadian Travel Surveys will be used as examples. (Note: Data associated with this presentation is available on the DLI FTP site under folder 1873-216.)

  18. d

    Basics of writing SPSS syntax files

    • search.dataone.org
    Updated Nov 6, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Vince Gray (2023). Basics of writing SPSS syntax files [Dataset]. http://doi.org/10.5683/SP3/QK8OKC
    Explore at:
    Dataset updated
    Nov 6, 2023
    Dataset provided by
    Borealis
    Authors
    Vince Gray
    Description

    Vince Gray delivered an introduction to the basic parts of a SPSS syntax file to read in data, in addition to presenting tips and tricks for preparing syntax files, cleaning up blatant problems with the data, and held a short exercise in coding a SPSS syntax file.

  19. SPSS Data Set for Grief and Mental Health Outcomes Among College Students

    • figshare.com
    bin
    Updated Apr 4, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Chan Thai (2024). SPSS Data Set for Grief and Mental Health Outcomes Among College Students [Dataset]. http://doi.org/10.6084/m9.figshare.22557355.v1
    Explore at:
    binAvailable download formats
    Dataset updated
    Apr 4, 2024
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Chan Thai
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is a subset of data extracted from a larger data set on studnent wellness and wellbeing collected in November 2018 at a small liberal arts university in Northern California. The variables used in our manuscript submitted for publication are included in this file.

  20. A dataset from a survey investigating disciplinary differences in data...

    • zenodo.org
    • data.niaid.nih.gov
    bin, csv, pdf, txt
    Updated Jul 12, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Anton Boudreau Ninkov; Anton Boudreau Ninkov; Chantal Ripp; Chantal Ripp; Kathleen Gregory; Kathleen Gregory; Isabella Peters; Isabella Peters; Stefanie Haustein; Stefanie Haustein (2024). A dataset from a survey investigating disciplinary differences in data citation [Dataset]. http://doi.org/10.5281/zenodo.7853477
    Explore at:
    txt, pdf, bin, csvAvailable download formats
    Dataset updated
    Jul 12, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Anton Boudreau Ninkov; Anton Boudreau Ninkov; Chantal Ripp; Chantal Ripp; Kathleen Gregory; Kathleen Gregory; Isabella Peters; Isabella Peters; Stefanie Haustein; Stefanie Haustein
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Filip Ventorp; Anna Gustafsson; Lil Träskman-Bendz; Åsa Westrin; Lennart Ljunggren (2023). SPSS Statistics Data file. [Dataset]. http://doi.org/10.1371/journal.pone.0140052.s001

SPSS Statistics Data file.

Related Article
Explore at:
42 scholarly articles cite this dataset (View in Google Scholar)
binAvailable download formats
Dataset updated
May 31, 2023
Dataset provided by
PLOS ONE
Authors
Filip Ventorp; Anna Gustafsson; Lil Träskman-Bendz; Åsa Westrin; Lennart Ljunggren
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

A SPSS file with data used in the statistical analysis. Covariates were excluded in the file due to restrictions of the ethical permission. However a complete file is provided for researchers after request at publication@ventorp.com. (SAV)

Search
Clear search
Close search
Google apps
Main menu