The biostatistics software market is experiencing robust growth, driven by the increasing adoption of data-driven approaches in pharmaceutical research, clinical trials, and academic studies. The market, valued at approximately $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the rising volume of complex biological data necessitates sophisticated software solutions for analysis and interpretation. Secondly, advancements in machine learning and artificial intelligence are enhancing the capabilities of biostatistics software, enabling more accurate and efficient data processing. Thirdly, regulatory pressures demanding robust data analysis in the pharmaceutical and healthcare sectors are boosting demand for validated and compliant biostatistics tools. The market is segmented by software type (general-purpose versus specialized) and end-user (pharmaceutical companies, academic institutions, and others). Pharmaceutical companies represent a significant portion of the market due to their extensive reliance on clinical trial data analysis. However, the academic and research segments are also exhibiting strong growth due to increased research activities and funding. Geographically, North America and Europe currently dominate the market, but Asia-Pacific is expected to witness substantial growth in the coming years due to increasing healthcare spending and technological advancements in the region. The competitive landscape is characterized by a mix of established players offering comprehensive suites and specialized niche vendors. While leading players like IBM SPSS Statistics and Minitab enjoy significant market share based on their brand recognition and established user bases, smaller companies specializing in specific statistical methods or user interfaces are gaining traction by catering to niche demands. This competitive dynamic will likely drive innovation and further segmentation within the market, resulting in specialized software offerings tailored to particular research areas and user requirements. The challenges the market faces include the high cost of software licensing, the need for specialized training for effective utilization, and the potential integration complexities with existing data management systems. However, the overall growth trajectory remains positive, driven by the inherent need for sophisticated biostatistical analysis in various sectors.

Abstract

The harmonized data set on health, created and published by the ERF, is a subset of Iraq Household Socio Economic Survey (IHSES) 2012. It was derived from the household, individual and health modules, collected in the context of the above mentioned survey. The sample was then used to create a harmonized health survey, comparable with the Iraq Household Socio Economic Survey (IHSES) 2007 micro data set.

----> Overview of the Iraq Household Socio Economic Survey (IHSES) 2012:

Iraq is considered a leader in household expenditure and income surveys where the first was conducted in 1946 followed by surveys in 1954 and 1961. After the establishment of Central Statistical Organization, household expenditure and income surveys were carried out every 3-5 years in (1971/ 1972, 1976, 1979, 1984/ 1985, 1988, 1993, 2002 / 2007). Implementing the cooperation between CSO and WB, Central Statistical Organization (CSO) and Kurdistan Region Statistics Office (KRSO) launched fieldwork on IHSES on 1/1/2012. The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

The survey has six main objectives. These objectives are:

1. Provide data for poverty analysis and measurement and monitor, evaluate and update the implementation Poverty Reduction National Strategy issued in 2009.
2. Provide comprehensive data system to assess household social and economic conditions and prepare the indicators related to the human development.
3. Provide data that meet the needs and requirements of national accounts.
4. Provide detailed indicators on consumption expenditure that serve making decision related to production, consumption, export and import.
5. Provide detailed indicators on the sources of households and individuals income.
6. Provide data necessary for formulation of a new consumer price index number.

The raw survey data provided by the Statistical Office were then harmonized by the Economic Research Forum, to create a comparable version with the 2006/2007 Household Socio Economic Survey in Iraq. Harmonization at this stage only included unifying variables' names, labels and some definitions. See: Iraq 2007 & 2012- Variables Mapping & Availability Matrix.pdf provided in the external resources for further information on the mapping of the original variables on the harmonized ones, in addition to more indications on the variables' availability in both survey years and relevant comments.

Geographic coverage

National coverage: Covering a sample of urban, rural and metropolitan areas in all the governorates including those in Kurdistan Region.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

Kind of data

Sample survey data [ssd]

Sampling procedure

----> Design:

Sample size was (25488) household for the whole Iraq, 216 households for each district of 118 districts, 2832 clusters each of which includes 9 households distributed on districts and governorates for rural and urban.

----> Sample frame:

Listing and numbering results of 2009-2010 Population and Housing Survey were adopted in all the governorates including Kurdistan Region as a frame to select households, the sample was selected in two stages: Stage 1: Primary sampling unit (blocks) within each stratum (district) for urban and rural were systematically selected with probability proportional to size to reach 2832 units (cluster). Stage two: 9 households from each primary sampling unit were selected to create a cluster, thus the sample size of total survey clusters was 25488 households distributed on the governorates, 216 households in each district.

----> Sampling Stages:

In each district, the sample was selected in two stages: Stage 1: based on 2010 listing and numbering frame 24 sample points were selected within each stratum through systematic sampling with probability proportional to size, in addition to the implicit breakdown urban and rural and geographic breakdown (sub-district, quarter, street, county, village and block). Stage 2: Using households as secondary sampling units, 9 households were selected from each sample point using systematic equal probability sampling. Sampling frames of each stages can be developed based on 2010 building listing and numbering without updating household lists. In some small districts, random selection processes of primary sampling may lead to select less than 24 units therefore a sampling unit is selected more than once , the selection may reach two cluster or more from the same enumeration unit when it is necessary.

Mode of data collection

Face-to-face [f2f]

Research instrument

----> Preparation:

The questionnaire of 2006 survey was adopted in designing the questionnaire of 2012 survey on which many revisions were made. Two rounds of pre-test were carried out. Revision were made based on the feedback of field work team, World Bank consultants and others, other revisions were made before final version was implemented in a pilot survey in September 2011. After the pilot survey implemented, other revisions were made in based on the challenges and feedbacks emerged during the implementation to implement the final version in the actual survey.

----> Questionnaire Parts:

The questionnaire consists of four parts each with several sections: Part 1: Socio – Economic Data: - Section 1: Household Roster - Section 2: Emigration - Section 3: Food Rations - Section 4: housing - Section 5: education - Section 6: health - Section 7: Physical measurements - Section 8: job seeking and previous job

Part 2: Monthly, Quarterly and Annual Expenditures: - Section 9: Expenditures on Non – Food Commodities and Services (past 30 days). - Section 10 : Expenditures on Non – Food Commodities and Services (past 90 days). - Section 11: Expenditures on Non – Food Commodities and Services (past 12 months). - Section 12: Expenditures on Non-food Frequent Food Stuff and Commodities (7 days). - Section 12, Table 1: Meals Had Within the Residential Unit. - Section 12, table 2: Number of Persons Participate in the Meals within Household Expenditure Other Than its Members.

Part 3: Income and Other Data: - Section 13: Job - Section 14: paid jobs - Section 15: Agriculture, forestry and fishing - Section 16: Household non – agricultural projects - Section 17: Income from ownership and transfers - Section 18: Durable goods - Section 19: Loans, advances and subsidies - Section 20: Shocks and strategy of dealing in the households - Section 21: Time use - Section 22: Justice - Section 23: Satisfaction in life - Section 24: Food consumption during past 7 days

Part 4: Diary of Daily Expenditures: Diary of expenditure is an essential component of this survey. It is left at the household to record all the daily purchases such as expenditures on food and frequent non-food items such as gasoline, newspapers…etc. during 7 days. Two pages were allocated for recording the expenditures of each day, thus the roster will be consists of 14 pages.

Cleaning operations

----> Raw Data:

Data Editing and Processing: To ensure accuracy and consistency, the data were edited at the following stages: 1. Interviewer: Checks all answers on the household questionnaire, confirming that they are clear and correct. 2. Local Supervisor: Checks to make sure that questions has been correctly completed. 3. Statistical analysis: After exporting data files from excel to SPSS, the Statistical Analysis Unit uses program commands to identify irregular or non-logical values in addition to auditing some variables. 4. World Bank consultants in coordination with the CSO data management team: the World Bank technical consultants use additional programs in SPSS and STAT to examine and correct remaining inconsistencies within the data files. The software detects errors by analyzing questionnaire items according to the expected parameter for each variable.

----> Harmonized Data:

• The SPSS package is used to harmonize the Iraq Household Socio Economic Survey (IHSES) 2007 with Iraq Household Socio Economic Survey (IHSES) 2012.
• The harmonization process starts with raw data files received from the Statistical Office.
• A program is generated for each dataset to create harmonized variables.
• Data is saved on the household and individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

Iraq Household Socio Economic Survey (IHSES) reached a total of 25488 households. Number of households refused to response was 305, response rate was 98.6%. The highest interview rates were in Ninevah and Muthanna (100%) while the lowest rates were in Sulaimaniya (92%).

The database for the SPSS statistical program is used as support for the data analysis carried out for the evaluation of the pilot study.

With the rapid development of AIGC (Artificial Intelligence Generated Content) and its expanding role and scope in education and teaching. This study conducted a survey among 394 pre-service STEM teachers enrolled at a university located in Zhejiang Province. Data were collected and a structural model was constructed to examine interplay among psychological stress, anxiety self-efficacy, and learning burnout resulting from the utilization of AIGC. The findings indicate that pre-service STEM teachers may experience psychological stress when applying AIGC, which could exacerbate their anxiety towards artificial intelligence and potentially lead to academic burnout. In order to effectively integrate AIGC in the field of education and enhance the professional development of pre-service teachers, the key lies in the dissemination of artificial intelligence knowledge, enhancing pre-service teachers' understanding of artificial intelligence, and encouraging them to appropriately utilize AIGC as a learning auxiliary tool. Methods This study uses the internationally recognized five-point Likert scale as the main tool to quantitatively assess STEM teachers' psychological pressure, fear of artificial intelligence, self-efficacy and learning fatigue caused by the use of AIGC. The questionnaire design is based on proven and valid scales in published academic literature at home and abroad to ensure the reliability and validity of data collection. After collecting data using the questionnaire method, invalid data were eliminated and SPSS 29.0 was used for statistical analysis.

IntroductionCervical cancer is a significant public health problem for women worldwide. It is the fourth most frequent cancer in women globally. While early detection of cancerous lesions through screening tests leads to a better prognosis and a better chance of being cured, the number of people who go for screening is still low, especially for groups that are marginalized, like immigrant women.ObjectiveThe purpose of this study was to identify cervical cancer screening practices and factors influencing screening status among Yemeni immigrant women living in the Klang Valley, Malaysia.MethodA cross-sectional study among 355 randomly selected respondents between the ages of 20 and 65 was conducted through an online survey. A questionnaire was sent directly to the participants via WhatsApp. The analysis was conducted using SPSS 25 with a significance level of 0.05. It included descriptive analysis, chi-square and multiple logistic regression.ResultsThe response rate was 59%, with the majority of the respondents being married and between the ages of 35 and 49. Screening was reported at 23.1% in the previous three years. The final model revealed that age group 50–65 years (AOR = 5.39, 95% CI: 1.53–18.93), insurance status (AOR 2.22, 95% CI = 1.15–4.3), knowledge (AOR = 6.67, 95% CI = 3.45–12.9), access to health care facilities (AOR = 4.64, 95% CI = 1.29–16.65), and perceived barriers (AOR = 2.5, 95% CI = 1.3–4.83) were significant predictors of cervical screening uptake among Yemeni immigrant women in Malaysia (p<0.05).ConclusionAccording to the results, cervical cancer screening was found to be low among Yemeni immigrant women. The predictors were age group 50–65 years, insurance status, knowledge, access to health care facilities and perceived barriers. Efforts to enhance immigrant women’s participation in cervical cancer screening must tackle barriers to access to healthcare services as well as expand cervical cancer screening education programs.

ObjectiveThe national fitness initiative in China is a strategic priority, public satisfaction is a key metric for evaluating the effectiveness of public services. The American Customer Satisfaction Index (ACSI) model has proven a robust tool for evaluating satisfaction with public services. The objective of study was to construct a satisfaction model for national fitness public services in China based on the ACSI framework and to explore the complex relationships among its components.MethodsEvaluation dimensions and an item pool were carefully developed by referencing the ACSI model and relevant academic literature. After a panel of experts assessed the initial items pool, the study formed the questionnaire to distribute the residents in Guangzhou, a total of 1,133 valid responses were collected. Data analysis was conducted using SPSS 22.0 and AMOS 16.0 software to evaluate the reliability and validity of the measurement model, the goodness-of-fit of the structural model, and analyze the statistical significance of each path coefficient.ResultsPublic expectation does not directly influence satisfaction (path coefficient 0.039, p = 0.103), it exerts a significant and direct influence on perceived quality (path coefficient 0.445, p = 0.003), which in turn demonstrably shapes public satisfaction (path coefficient 0.403, p = 0.005). Perceived quality also directly influences perceived value (path coefficient 0.735, p = 0.006), which in turn significantly impacts public satisfaction (path coefficient 0.554, p = 0.003). Public satisfaction directly and significantly influences both public complaints (path coefficient 0.395, p = 0.003) and public trust (path coefficient 0.699, p = 0.003).ConclusionPerceived quality is the most critical factor influencing public satisfaction, which subsequently affects public complaints and trust. Fitness service providers should consistently improve service quality, aligning actual service delivery with public expectations, and enhancing the perceived value for the public. These efforts will bolster the public’s satisfaction level.

Raw data file in SPSS, collected for Effects of online retailers’ after delivery services on repurchase intention: An empirical analysis based on customers’ past experience and future confidence with the retailer

Data is based on two provinces: KwaZulu Natal and Gauteng provinces. It gives an indication of support given to farmers who benefited from the Comprehensive Agricultural Support Programme (CASP) with emphasis on extension services and business development. The data also provides information on food security of CASP beneficiaries.The study used secondary data from the CASP evaluation study that was conducted in 2015 by the University of Pretoria in conjunction with the DPME. The secondary data that was received from the University of Pretoria and Department of Agriculture, Land Reform and Rural Development (DALRRD) was analyzed with the use of Statistical Package for the Social Sciences (SPSS). The analysis only focused on 167 key informants’ data (80 in KZN and 87 in GP). Secondary data was analysed using SPSS focusing on the following indicators to respond to the objectives of the study.Secondary data was use for the study. From the acquired master data, a separate dataset with information only on KZN and Gauteng was isolated; an overall final dataset was prepared and cleaned on Statistical Package for the Social Sciences (SPSS). The secondary data was captured on Excel when it was received. The data was then cleaned and transferred to SPSS for analysis. When the secondary data was cleaned, the cleaned database was aligned to better respond to objectives of the study. This database was subjected to descriptive quantitative analysis, including basic statistics, crosstabs, pivot tables, etc. Data from key informant interviews was analysed using qualitative methods.Data processing and analysis were done using both qualitative and quantitative methodologies. Utilizing the SPSS, descriptive quantitative analysis was used to analyse the project manager data SPSS. Visuals such as graphs and tables were used to present the data. The database was subjected to extensive descriptive quantitative analysis, including basic statistics such as cross tabs, frequencies and pivot tables. These results were used to draw conclusions as well as recommendations.

This study aims to determine "the effect of conflict on employee performance at Giant Pekanbaru". In this study, a sample of 90 people was used. Data collection was carried out through questionnaires and data analysis techniques used with a significance level of 0.05 were validity test, reliability test with crobanchalpha, simple linear regression and t test analysis and analysis of determination R Square (R2). The results of the analysis and data of this study using the help of SPSS Version 16.0, the results of the simple linear regression equation are Y = 45.561 + 0.256X. Based on the results of the research on the t-test showed results, Tcount> Ttable or 2,250> 1,987. So it can be concluded that there is a significant influence between conflict on performance. Based on the data obtained from the variable Y (performance), obtained R Square (R2) of 0.597 or 59.7%. R Square is used to determine the percentage of the influence of the Independent variable (conflict) on the Dependent variable (performance) is 59.7% while the remaining 40.3% is influenced by other variables not examined.

Statistical analysis data using SPSS V16.0

SPSS syntax files, ready-for-analysis data, Stata do files and transcripts from interviews and FGDs used in the analysis published in the Final Report to 3ie on the project, "Impact evaluation of youth-friendly family planning services in Uganda" (UPW06.IE.SEDC). This project was funded as part of the Uganda Policy Window round.

Abstract: The aim of this study was to describe and evaluate access to oral health services among adolescents enrolled in public schools of Campina Grande, Paraíba, Brazil, a large-size municipality in the Northeast of Brazil. An observational, descriptive, analytical, quantitative, and cross-sectional study was carried out through a school survey, in which four validated questionnaires were applied to 438 adolescents aged 12 to 19 years. Data were processed using the SPSS statistical software version 20.0, with bivariate analysis and multivariate analysis through Poisson regression. About 90.9% of adolescents reported having visited the dentist at least once; however, when considering the last 6 months, this percentage fell to 48.4%. Adolescents used private services (50.2%) or the public service (49.8%). About 70.6% of interviewees reported dental treatment (61.1%) as the main reason for seeking the service. Through multivariate analysis, it was observed that the demand for the service was higher among female adolescents (60.5%, p <0.001); the other variables did not present statistically significant differences. In conclusion, the access to oral healthcare services reported by adolescents was good, but there is still a considerable part of this population with no access. Variables that presented significant associated with dental services were gender and toothache history, but only gender remained significant in the multivariate model.

This study investigated the current situation of social media adoption in the energy and resources sector, the preferred social media platforms in the energy and resources sector, and the reasons for the differences between these preferred platforms. In this study, quantitative analysis method was adopted, and we used Excel and SPSS for data collection and data analysis. Through the investigation of 262 companies, all companies maintained a strong online presence through corporate websites, email contacts, and various social media platforms. However, the adoption and use of social media platforms differed among countries. Linear regression analysis revealed that companies should constantly update their relevant information on social media platforms to increase their followers, improve their influence and popularity, and achieve better interaction with stakeholders. Through quantitative analysis, it was found that companies in the energy and resources sector should maintain a strong online presence. These companies should choose specific social media platforms according to their target audience. Because some platforms are more suitable for specific purposes, companies should pay attention to the different designs and functions of each social media platform. Future research should focus on the use of social media in B2B marketing by companies operating in the energy and resources sector.

Online survey software developers have seen robust revenue growth over the past five years, driven by heightened demand for real-time feedback amid economic turbulence. Companies across retail, healthcare and the public sector turned to online survey platforms to gauge shifting customer sentiment and employee satisfaction, resulting in a 17.9% surge in revenue in 2022. Research and development (R&D) spending soared as businesses sought product differentiation, while public agencies, like the US Department of Veterans Affairs, adopted survey tools for large-scale feedback. Despite controlling a collective four-fifths of the market, major companies Qualtrics and Momentive Global have remained unprofitable, with heavy R&D expenses and stock-based compensation driving persistent losses. These losses attracted private equity interest, culminating in major acquisitions by Silver Lake and STG in 2023. Revenue has surged at a CAGR of 7.6% to an estimated $2.4 billion over the five years through 2025. Innovation has become central to the online survey software industry, reshaping user experience and competition. Artificial intelligence now allows users to automate question generation, reduce bias and analyze respondents' sentiments. Features like Typeform's jumps and interactive formats have boosted completion rates. As clients expect more from their chosen platform, developers have doubled down on expensive AI enhancements and analytics tools to stay competitive. However, these advancements are costly to develop and maintain. While innovation drives revenue and market relevance, it has also stifled profitability by inflating operational costs and intensifying the need for continuous upgrades. The next five years will likely bring slower revenue growth for online survey software developers as corporate profit slumps and businesses scrutinize discretionary spending. Still, economic uncertainty will maintain demand for survey insights, especially in areas like workforce management and product development. Companies will expand their plan options, offering affordable versions for cost-conscious buyers and premium packages featuring personalized, AI-driven analytics for larger enterprises. Stricter data privacy laws will force platforms to bolster security and transparency. Revenue is set to climb at a CAGR of 2.6% to an estimated $2.7 billion through the end of 2030.

The average American’s diet does not align with the Dietary Guidelines for Americans (DGA) provided by the U.S. Department of Agriculture and the U.S. Department of Health and Human Services (2020). The present study aimed to compare fruit and vegetable consumption among those who had and had not heard of the DGA, identify characteristics of DGA users, and identify barriers to DGA use. A nationwide survey of 943 Americans revealed that those who had heard of the DGA ate more fruits and vegetables than those who had not. Men, African Americans, and those who have more education had greater odds of using the DGA as a guide when preparing meals relative to their respective counterparts. Disinterest, effort, and time were among the most cited reasons for not using the DGA. Future research should examine how to increase DGA adherence among those unaware of or who do not use the DGA. Comparative analyses of fruit and vegetable consumption among those who were aware/unaware and use/do not use the DGA were completed using independent samples t tests. Fruit and vegetable consumption variables were log-transformed for analysis. Binary logistic regression was used to examine whether demographic features (race, gender, and age) predict DGA awareness and usage. Data were analyzed using SPSS version 28.1 and SAS/STAT® version 9.4 TS1M7 (2023 SAS Institute Inc).

This folders contains three types of files. The first one is in excel format. The excel files consist of the raw data, descriptive data that describes the background of the participants, correlation and confirmatory Factor analysis outputs, and survey questionnaire in Malay and English. The second file type contains raw data in SPSS and the output in SPSS. The third file type contains the survey questionnaire; the items are bilingual.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study was designed to understand the economic and social structure of the market for stolen data on-line. This data provides information on the costs of various forms of personal information and cybercrime services, the payment systems used, social organization and structure of the market, and interactions between buyers, sellers, and forum operators. The PIs used this data to assess the economy of stolen data markets, the social organization of participants, and the payment methods and services used. The study utilized a sample of approximately 1,900 threads generated from 13 web forums, 10 of which used Russian as their primary language and three which used English. These forums were hosted around the world, and acted as online advertising spaces for individuals to sell and buy a range of products. The content of these forums were downloaded and translated from Russian to English to create a purposive, yet convenient sample of threads from each forum. The collection contains 1 SPSS data file (ICPSR Submission Economic File SPSS.sav) with 39 variables and 13,735 cases and 1 Access data file (Social Network Analysis File Revised 04-11-14.mdb) with a total of 16 data tables and 199 variables. Qualitative data used to examine the associations and working relationships present between participants at the micro and macro-level are not available at this time.

This was a cross-sectional nationwide survey of adults in the US conducted between April 24 and May 13, 2020. The survey targeted a representative sample of approximately 5,000 respondents. The rate of COVID-19 cases and testing, most frequently reported symptoms, symptom severity, treatment received, impact of COVID-19 on mental and physical health, and factors predictive of testing positive were assessed.

Methods Data was collected through an on-line cross-sectional survey of adults (18 years or older) in the US. The survey was conducted in accordance with Acumen Health Research Institute's (AHRI) established SOPs. A random stratified sampling framework ensured a community-based sample with a demographic composition representative of the US adult population by region, gender, age, and race, according to the US Census (US Census American Community Survey 5-year estimate, 2011-2015). To participate in the study, respondents were required to be 18 years old or older, reside in the United States, and confirm their voluntarily agreement to participate (participants were informed they could leave the survey at any time). The survey was open to the general population and not restricted to patients hospitalized with COVID-19. Participants were recruited through AHRI’s online research panels. Analysis was carried out with SPSS v27.0.1.0.

Survey responses exported from Qualtrics XM platform used for data analysis. The objectives of the study were to evaluate the user experience of current Wisdom Panel customers and evaluate their motivations to pursue canine genetic services, their perceptions of the services and test(s) used, and their response to the canine genetic test results. The file format provided is for Excel. Data analysis was completed using SPSS version 28. Please contact the author directly with any questions about the data.

This dataset presents primary data on the the effect of social capital on business performance in the Nigerian informal economy. Primary data collection was carried out through a cross-sectional survey of 600 informal business owners within Ikeja Local Government Area (LGA), Lagos State, Nigeria. A simple sampling technique was further adopted in selecting the sample size of the study, and a close-ended questionnaire was adopted for the data collection process. Descriptive statistical analysis was performed using the Statistical Package for Social Sciences (SPSS) version 23. This data has the potential to be reused for full empirical research relating to social capital and business performance in emerging economies.