In 2022, online surveys were by far the most used traditional quantitative methodologies in the market research industry worldwide. During the survey, 85 percent of respondents stated that they regularly used online surveys as one of their three most used methods. Moreover, nine percent of respondents stated that they used online surveys only occasionally.

This data is associated with the publication of the manuscript "Nightlife as Counterspace: Potentials of Nightlife for Social Wellbeing" in Annals of Leisure Research. It contains a data set on the (german) standardized survey that is directly cited in the manuscript, the Cluster analysis, as well as the german original transcripted records of the cited group discussions.

Results of analysis on quantitative data, descriptive statistics, and group comparisons.

The interview data was gathered for a project that investigated the practices of instructors who use quantitative data to teach undergraduate courses within the Social Sciences. The study was undertaken by employees of the University of California, Santa Barbara (UCSB) Library, who participated in this research project with 19 other colleges and universities across the U.S. under the direction of Ithaka S+R. Ithaka S+R is a New York-based research organization, which, among other goals, seeks to develop strategies, services, and products to meet evolving academic trends to support faculty and students.

The field of Social Sciences has been notoriously known for valuing the contextual component of data and increasingly entertaining more quantitative and computational approaches to research in response to the prevalence of data literacy skills needed to navigate both personal and professional contexts. Thus, this study becomes particularly timely to identify current instructors’ practi..., The project followed a qualitative and exploratory approach to understand current practices of faculty teaching with data. The study was IRB approved and was exempt by the UCSB’s Office of Research in July 2020 (Protocol 1-20-0491).Â

The identification and recruitment of potential participants took into account the selection criteria pre-established by Ithaka S+R: a) instructors of courses within the Social Sciences, considering the field as broadly defined, and making the best judgment in cases the discipline intersects with other fields; b) instructors who teach undergraduate courses or courses where most of the students are at the undergraduate level; c) instructors of any rank, including adjuncts and graduate students; as long as they were listed as instructors of record of the selected courses; d) instructors who teach courses were students engage with quantitative/computational data.Â

The sampling process followed a combination of strategies to more easily identify instructo..., The data folder contains 10Â pdf files with de-identified transcriptions of the interviews and the pdf files with the recruitment email and the interview guide.Â

This data set contains the replication data and supplements for the article "Knowing, Doing, and Feeling: A three-year, mixed-methods study of undergraduates’ information literacy development." The survey data is from two samples: - cross-sectional sample (different students at the same point in time) - longitudinal sample (the same students and different points in time)Surveys were distributed via Qualtrics during the students' first and sixth semesters. Quantitative and qualitative data were collected and used to describe students' IL development over 3 years. Statistics from the quantitative data were analyzed in SPSS. The qualitative data was coded and analyzed thematically in NVivo. The qualitative, textual data is from semi-structured interviews with sixth-semester students in psychology at UiT, both focus groups and individual interviews. All data were collected as part of the contact author's PhD research on information literacy (IL) at UiT. The following files are included in this data set: 1. A README file which explains the quantitative data files. (2 file formats: .txt, .pdf)2. The consent form for participants (in Norwegian). (2 file formats: .txt, .pdf)3. Six data files with survey results from UiT psychology undergraduate students for the cross-sectional (n=209) and longitudinal (n=56) samples, in 3 formats (.dat, .csv, .sav). The data was collected in Qualtrics from fall 2019 to fall 2022. 4. Interview guide for 3 focus group interviews. File format: .txt5. Interview guides for 7 individual interviews - first round (n=4) and second round (n=3). File format: .txt 6. The 21-item IL test (Tromsø Information Literacy Test = TILT), in English and Norwegian. TILT is used for assessing students' knowledge of three aspects of IL: evaluating sources, using sources, and seeking information. The test is multiple choice, with four alternative answers for each item. This test is a "KNOW-measure," intended to measure what students know about information literacy. (2 file formats: .txt, .pdf)7. Survey questions related to interest - specifically students' interest in being or becoming information literate - in 3 parts (all in English and Norwegian): a) information and questions about the 4 phases of interest; b) interest questionnaire with 26 items in 7 subscales (Tromsø Interest Questionnaire - TRIQ); c) Survey questions about IL and interest, need, and intent. (2 file formats: .txt, .pdf)8. Information about the assignment-based measures used to measure what students do in practice when evaluating and using sources. Students were evaluated with these measures in their first and sixth semesters. (2 file formats: .txt, .pdf)9. The Norwegain Centre for Research Data's (NSD) 2019 assessment of the notification form for personal data for the PhD research project. In Norwegian. (Format: .pdf)

The Market Research and Statistical Services industry has performed poorly because of mixed demand across years for market research and related services. Industry revenue is anticipated to shrink at an annualised 1.3% over the five years through 2024-25, totalling $3.6 billion, with revenue falling by 1.5% in the current year. The overall revenue decrease can be attributed to mixed growth in prior years because of uncertainty and demand changes in response to the COVID-19 pandemic and ABS funding volatility. Industry revenue displays significant volatility from year to year, mainly because of fluctuations in ABS funding by the Federal Government. As the next census is set to occur in 2026, ABS revenue over the past two years has been constrained. Some companies that previously used industry businesses have been increasingly performing market research and statistical analysis in-house. Many external companies have improved their technology and data collection capabilities, which has made it more cost-effective to perform these activities internally. While the introduction of artificial intelligence has provided cost-cutting opportunities for market research businesses, it has also encouraged clients to bring industry services in-house, reducing demand. Profitability has also waned because of heightened price competition and wage costs increasing as a share of revenue. Ongoing growth in online media and big data presents both challenges and opportunities for market research businesses. Mounting demand for research and statistics relating to new media audience numbers and advertising effectiveness represents a potential opportunity. Even so, market research businesses will face challenges in developing effective measurement systems, and competition from information technology specialists that are developing similar systems will intensify. Despite these challenges, industry revenue is forecast to increase at an annualised 2.0% through 2029-30 to reach $3.9 billion.

Objectives: In quantitative research, understanding basic parameters of the study population is key for interpretation of the results. As a result, it is typical for the first table ("Table 1") of a research paper to include summary statistics for the study data. Our objectives are 2-fold. First, we seek to provide a simple, reproducible method for providing summary statistics for research papers in the Python programming language. Second, we seek to use the package to improve the quality of summary statistics reported in research papers.

Materials and Methods: The tableone package is developed following good practice guidelines for scientific computing and all code is made available under a permissive MIT License. A testing framework runs on a continuous integration server, helping to maintain code stability. Issues are tracked openly and public contributions are encouraged.

Results: The tableone software package automatically compiles summary statistics into publishable formats such as CSV, HTML, and LaTeX. An executable Jupyter Notebook demonstrates application of the package to a subset of data from the MIMIC-III database. Tests such as Tukey's rule for outlier detection and Hartigan's Dip Test for modality are computed to highlight potential issues in summarizing the data.

Discussion and Conclusion: We present open source software for researchers to facilitate carrying out reproducible studies in Python, an increasingly popular language in scientific research. The toolkit is intended to mature over time with community feedback and input. Development of a common tool for summarizing data may help to promote good practice when used as a supplement to existing guidelines and recommendations. We encourage use of tableone alongside other methods of descriptive statistics and, in particular, visualization to ensure appropriate data handling. We also suggest seeking guidance from a statistician when using tableone for a research study, especially prior to submitting the study for publication.

The Best Management Practices Statistical Estimator (BMPSE) version 1.2.0 was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to provide planning-level information about the performance of structural best management practices for decision makers, planners, and highway engineers to assess and mitigate possible adverse effects of highway and urban runoff on the Nation's receiving waters (Granato 2013, 2014; Granato and others, 2021). The BMPSE was assembled by using a Microsoft Access® database application to facilitate calculation of BMP performance statistics. Granato (2014) developed quantitative methods to estimate values of the trapezoidal-distribution statistics, correlation coefficients, and the minimum irreducible concentration (MIC) from available data. Granato (2014) developed the BMPSE to hold and process data from the International Stormwater Best Management Practices Database (BMPDB, www.bmpdatabase.org). Version 1.0 of the BMPSE contained a subset of the data from the 2012 version of the BMPDB; the current version of the BMPSE (1.2.0) contains a subset of the data from the December 2019 version of the BMPDB. Selected data from the BMPDB were screened for import into the BMPSE in consultation with Jane Clary, the data manager for the BMPDB. Modifications included identifying water quality constituents, making measurement units consistent, identifying paired inflow and outflow values, and converting BMPDB water quality values set as half the detection limit back to the detection limit. Total polycyclic aromatic hydrocarbons (PAH) values were added to the BMPSE from BMPDB data; they were calculated from individual PAH measurements at sites with enough data to calculate totals. The BMPSE tool can sort and rank the data, calculate plotting positions, calculate initial estimates, and calculate potential correlations to facilitate the distribution-fitting process (Granato, 2014). For water-quality ratio analysis the BMPSE generates the input files and the list of filenames for each constituent within the Graphical User Interface (GUI). The BMPSE calculates the Spearman’s rho (ρ) and Kendall’s tau (τ) correlation coefficients with their respective 95-percent confidence limits and the probability that each correlation coefficient value is not significantly different from zero by using standard methods (Granato, 2014). If the 95-percent confidence limit values are of the same sign, then the correlation coefficient is statistically different from zero. For hydrograph extension, the BMPSE calculates ρ and τ between the inflow volume and the hydrograph-extension values (Granato, 2014). For volume reduction, the BMPSE calculates ρ and τ between the inflow volume and the ratio of outflow to inflow volumes (Granato, 2014). For water-quality treatment, the BMPSE calculates ρ and τ between the inflow concentrations and the ratio of outflow to inflow concentrations (Granato, 2014; 2020). The BMPSE also calculates ρ between the inflow and the outflow concentrations when a water-quality treatment analysis is done. The current version (1.2.0) of the BMPSE also has the option to calculate urban-runoff quality statistics from inflows to BMPs by using computer code developed for the Highway Runoff Database (Granato and Cazenas, 2009;Granato, 2019). Granato, G.E., 2013, Stochastic empirical loading and dilution model (SELDM) version 1.0.0: U.S. Geological Survey Techniques and Methods, book 4, chap. C3, 112 p., CD-ROM https://pubs.usgs.gov/tm/04/c03 Granato, G.E., 2014, Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater runoff best management practices (BMPs): U.S. Geological Survey Scientific Investigations Report 2014–5037, 37 p., http://dx.doi.org/10.3133/sir20145037. Granato, G.E., 2019, Highway-Runoff Database (HRDB) Version 1.1.0: U.S. Geological Survey data release, https://doi.org/10.5066/P94VL32J. Granato, G.E., and Cazenas, P.A., 2009, Highway-Runoff Database (HRDB Version 1.0)--A data warehouse and preprocessor for the stochastic empirical loading and dilution model: Washington, D.C., U.S. Department of Transportation, Federal Highway Administration, FHWA-HEP-09-004, 57 p. https://pubs.usgs.gov/sir/2009/5269/disc_content_100a_web/FHWA-HEP-09-004.pdf Granato, G.E., Spaetzel, A.B., and Medalie, L., 2021, Statistical methods for simulating structural stormwater runoff best management practices (BMPs) with the stochastic empirical loading and dilution model (SELDM): U.S. Geological Survey Scientific Investigations Report 2020–5136, 41 p., https://doi.org/10.3133/sir20205136

Statistics on the number of requests for quantitative information that Scottish Government put to local government and other public bodies in 2005/06 and 2008/09.

Source agency: Scottish Government

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: Review of quantitative data requirements of Local Government and Public Bodies

Key Metrics: awareness, consideration, preference, purchase intent, willingness to pay, NPS/CSAT, conversion rate, lift, elasticity, share of preference

Abstract The aim of this research was to investigate the validity evidence for the Attitude scale towards Statistics, EAEst. This instrument measures the attitude towards Statistics using a three-dimensional model, which considers the knowledge about Statistics (cognitive), feelings (affective) and behaviors (behavioral) towards Statistics. To this purpose, the EAEst, Likert of 5 points and with 24 items was used. A total of 277 higher education students of both genders, aged 18 to 54 years old (M = 24.1 and SD = 5.8), participated in the study. In order to verify the internal consistency of the instrument, Confirmatory Factor Analysis was used, which suggested an observable model similar to the theoretical model of attitudes. Reliability was verified using Cronbach's alpha (α = 0.908). The results show satisfactory psychometric properties. It is suggested that further studies use other types of validity evidence, such as criterion and meta-analyses.

Gene expression assays that are based on quantitative real-time PCR (qRT-PCR) method are still very popular, therefore, we developed qDATA, an open-source R-based bioinformatics application that offers a quick and intuitive analysis of raw cycle threshold (Ct) values. The application relies on a straightforward data input consisting in Ct values and on other mandatory fields specifying the experimental and control groups. qDATA automatically performs descriptive statistics, normality and statistical testing on 2–ΔCt (or ΔCt) and 2–ΔΔCt terms calculated with Livak’s method. We also propose a qRT-PCR data analysis framework that depends on performing exhaustive ΔCt calculations within discrete biological replicates (BRs) and subsequently using the Livak formula for the complete sets of available data. These prerequisites arguably lead to an improved data analysis and statistical relevance. The efficiency of our computing approach was tested using input Ct values corresponding to immune related gene expression evaluated in experimental infection of Drosophila melanogaster and Apis mellifera workers. The presented results reveal that our working strategy is reliable and highlight the efficacy and performance of qDATA application. We developed qDATA, an open-source R based application designed for automated analysis of gene expression of data derived from qRT-PCR experiments. This tool provides a streamlined workflow with a modern and user-friendly graphical interface, enabling users to perform descriptive statistics, assess data normality and conduct statistical testing on 2–ΔCt (or ΔCt) and 2–ΔΔCt terms calculated with the Livak’s method. qDATA implements a strategy of calculating all possible differences between cycle threshold values within a biological replicate. In this article we showcase the functionality of qDATA and demonstrate its efficiency on two previously published qRT-PCR datasets, highlighting its practical application and effectiveness in gene expression studies. IntroductionCurrently, qRT-PCR is the method of choice for targeted gene expression experiments and the Livak formula is the most popular implementation for calculating fold change values. Currently, qRT-PCR is the method of choice for targeted gene expression experiments and the Livak formula is the most popular implementation for calculating fold change values. Materials and methodsWe developed qDATA, an open-source R based application designed for automated analysis of qRT-PCR data that is freely available to download from GitHub at https://github.com/DL-UB/dScaff. We developed qDATA, an open-source R based application designed for automated analysis of qRT-PCR data that is freely available to download from GitHub at https://github.com/DL-UB/dScaff. ImplementationSupports the use of extended calculations for ΔCt values by implementing all possible differences between technical replicates within a biological replicate.Argues the efficiency of statistical testing and of calculating the fold change values when using this framework in comparison to the other implementation based on mean Ct values.Presents qDATA, an original bioinformatics tool that makes use of the proposed framework in an intuitive, fast and customizable GUI.Advocates for statistical testing on linear forms of ΔCt (2-ΔCt) for consistent and reliable results.Provides a streamlined interface with intuitive data input and advanced parameter adjustments that enable comprehensive summary statistics, statistical testing, fold change analysis and various export features. Supports the use of extended calculations for ΔCt values by implementing all possible differences between technical replicates within a biological replicate. Argues the efficiency of statistical testing and of calculating the fold change values when using this framework in comparison to the other implementation based on mean Ct values. Presents qDATA, an original bioinformatics tool that makes use of the proposed framework in an intuitive, fast and customizable GUI. Advocates for statistical testing on linear forms of ΔCt (2-ΔCt) for consistent and reliable results. Provides a streamlined interface with intuitive data input and advanced parameter adjustments that enable comprehensive summary statistics, statistical testing, fold change analysis and various export features. Results and DiscussionUsing actual qRT-PCR data, we put to test our application and made a detail comparison of the results obtained with two different analysis approaches (Case 1 and Case 2).We compare qDATA to existing tools of qRT-PCR data analysis.We intend to further develop qDATA in order to accommodate a wider range of research scenarios and to be more user friendly. Using actual qRT-PCR data, we put to test our application and made a detail comparison of the results obtained with two different analysis approaches (Case 1 and Case 2). We compare qDATA to existing tools of qRT-PCR data analysis. We intend to further develop qDATA in order to accommodate a wider range of research scenarios and to be more user friendly. Conclusion:qDATA offers fast, efficient and reliable automatic qRT-PCR data analysis, with no required programming experience. qDATA offers fast, efficient and reliable automatic qRT-PCR data analysis, with no required programming experience.

GroupSize: 6-8 participants OverRecruitment: 20-30%

Building strong quantitative skills prepares undergraduate biology students for successful careers in science and medicine. While math and statistics anxiety can negatively impact student learning within biology classrooms, instructors may reduce this anxiety by steadily building student competency in quantitative reasoning through instructional scaffolding, application-based approaches, and simple computer program interfaces. However, few statistical programs exist that meet all needs of an inclusive, inquiry-based laboratory course. These needs include an open-source program, a simple interface, little required background knowledge in statistics for student users, and customizability to minimize cognitive load, align with course learning outcomes, and create desirable difficulty. To address these needs, we used the Shiny package in R to develop a custom statistical analysis application. Our “BioStats” app provides students with scaffolded learning experiences in applied statistics that promotes student agency and is customizable by the instructor. It introduces students to the strengths of the R interface, while eliminating the need for complex coding in the R programming language. It also prioritizes practical implementation of statistical analyses over learning statistical theory. To our knowledge, this is the first statistics teaching tool where students are presented basic statistics initially, more complex analyses as they advance, and includes an option to learn R statistical coding. The BioStats app interface yields a simplified introduction to applied statistics that is adaptable to many biology laboratory courses.

Primary Image: Singing Junco. A sketch of a junco singing on a pine tree branch, created by the lead author of this paper.

Oblique orientation of vocal cord demands strict compliance, by technicians and clinicians, to the recommended parallel plane CT scan of larynx. Repercussions of non-compliance has never been investigated before. We aimed to observe influence of non-parallel vocal cord plane CT scan on qualitative and quantitative glottic parameters, keeping parallel plane CT as a standard for comparison. Simultaneous identification of potential suboptimal imaging sequelae as a result of unformatted CT plane was also identified. In this study we included 95 normal adult glottides and retrospectively analyzed their anatomy in two axial planes, non-parallel plane ① and parallel to vocal cord plane ②. Qualitative (shape, structures at glottic level) and quantitative (anterior commissure ACom, vocal cord width VCw, anteroposterior AP, transverse Tr, cross-sectional area CSA) glottic variables were recorded. Multivariate statistical analysis was used to predict pattern and their impact on glottic anatomy. Plane ① displayed supraglottic features in glottis; adipose (90.5%) and split thyroid laminae (70.6%). Other categorical variables: atypical shape, submental structures and multilevel vertebral crossing were also in majority. All glottic dimensions varied significantly between two planes with most in ACom (-5.8mm) and CSA (-15.0 mm2). In contrast, plane ② manifested higher VCw (>73%), Tr (66.3%), CSA (64.2%) and AP (44.2%) measurements. On correlation analysis, variation in ACom, CSA, Tr was positively associated with VC or plane obliquity (p<0.05). This variability was more in obese and short necked subjects. Change in one parameter also modified other significantly i.e., ACom versus AP and CSA versus Tr. Results indicated statistically significant change in subjective and objective anatomical parameters of glottis on non-application of appropriate CT larynx protocol for image analysis hence highlighting importance of image reformation.

The importance of data science skills for modern scientific research cannot be understated. Although policy documents increasingly recommend what skills should be included in undergraduate statistics and data science curricula, little is known about how students actually develop and apply these skills. This paper addresses this gap through an in-depth case study tracing one student’s learning progressions throughout her master’s program. Using a qualitative method to analyze student code, which has seen little use in statistics education research, I examined how Alicia transferred the data science skills from her applied statistics course into authentic research settings. The analysis shows that, while Alicia successfully navigated new challenges, she encountered persistent hurdles when extending bivariate techniques into multivariate contexts, particularly with visualizations and summary statistics. These findings highlight the obs..., R Script files submitted by Alicia (pseudonym) over the course of the study. The files are named according to when they were submitted:

December 2018

R Script #1

April 2019

R Script #1 (revised) R Script #2

September 2019

R Script #1 (revised) R Script #2 (revised)

Qualitative Data Analysis Files (Rich text files)

December 2018 Script #1 April 2019 Script #1 April 2019 Script #2 September 2019 Script #1 September 2019 Script #2

Quantitative Data Analysis Files

r-code-themes.csv

Comma separated values file with separate sheets for each R script Each sheet contains the qualitative code assigned to each line of code and whether the code contained errors.

, , # Code from: Beyond the classroom: Alicia’s multivariate journey

https://doi.org/10.5061/dryad.c59zw3rg6

This repository contains the R script files submitted by Alicia (pseudonym) throughout this study, files associated with the qualitative analysis of the code, and files associated with visualizations of the qualitative themes included in Alicia's code.

Description of the data and file structure

As this is a qualitative analysis, the usage of these "data" files differs from a typical quantitative analysis.

• The .R Files contain the scripts generated by Alicia at each time point (December 2018, April 2019, September 2019)
• The -codes.rftÂ Files contain the (qualitative) process codes for each R script
• The r-code-themes.xlsxÂ The file contains information on every script and the qualitative code assigned to each line of code.

Code/Software

While the "data" for this analysis are R scripts, these scripts cannot be execu...,

In 2023, the methodology that contributed most to the revenue of market research companies was online/mobile quantitative research with ** percent of the market share. Second in the list was automated digital/electronic, with *** percent.

It has as its general objective, describe how is the logic of dynamic from base basketball games. Specifically, it sought to understand which are the statistical indicators meaningful to claim victory in the game and competition in general and in balanced, normal and unbalanced games; which is the influence of the indicator "efficiency" individual and collective for the end result of game and competition; and which is the relationships between the momentum of the game with the same results. The methodology used the descriptive quantitative research, with a statistical analysis spreadsheet built specifically for research as an instrument. The data processing was through descriptive and inferential statistics. Results: 2 points attempts, 2 points converted, 2 points percentage, total points made, overall hit percentage, defensive rebounds, total rebounds and assists were considered significant for obtaining victory in the game. The same indicators, plus "free throws attempted" were coincident in balanced, normal and unbalanced games. 2 points attempts, 2 points converted, 2 points percentage, overall hit percentage and offensive rebounds were significant for achievement of victory in the competition. Teams that won the game and competition presented collective efficiency superior to others. An average of 4 players per team presented individual efficiency higher than the average of individual efficiency of the team and competition. The second and last quarters were even more relevant for obtaining the victory in the game and the competition. In conclusion, it is understood that the statistical analysis is a relevant source of information on a basketball game, and can provide relevant insights for researches and technical committees.

Analyze statistics: The données have registered on one of the Excel donné bases. The results have been extracted from the center (effect) of the qualitative variables and many of the quantitative variables. They are included in the table (III-1 to III-7) In the file below

Code and associated data for the following preprint:

AP Browning, JA Sharp, RJ Murphy, G Gunasingh, B Lawson, K Burrage, NK Haass, MJ Simpson. 2021 Quantitative analysis of tumour spheroid structure. eLife http://dx.doi.org/https://doi.org/10.7554/eLife.73020

Data comprises measurements relating to the size and inner structure of spheroids grown from WM793b and WM983b melanoma cells over up to 24 days.

Code, data, and interactive figures are available as a Julia module on GitHub:

Browning AP (2021) Github ID v.0.6.2. Quantitative analysis of tumour spheroid structure. https://github.com/ap-browning/Spheroids

(copy archived here)

Code used to process the experimental images is available on Zenodo:

Browning AP, Murphy RJ (2021) Zenodo Image processing algorithm to identify structure of tumour spheroids with cell cycle labelling. https://doi.org/10.5281/zenodo.5121093