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.

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.

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.

In 2022, the highest amount of spending on surveys for market research in the United States was online/mobile quantitative research, with ** percent of respondents who stated this as their most financially committed endeavor. Social media monitoring accounted for only *** percent of the total of market research spending in the United States.

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...

Abstract

Abstract

Background: Adolescent girls in Kenya are disproportionately affected by early and unintended pregnancies, unsafe abortion and HIV infection. The In Their Hands (ITH) programme in Kenya aims to increase adolescents' use of high-quality sexual and reproductive health (SRH) services through targeted interventions. ITH Programme aims to promote use of contraception and testing for sexually transmitted infections (STIs) including HIV or pregnancy, for sexually active adolescent girls, 2) provide information, products and services on the adolescent girl's terms; and 3) promote communities support for girls and boys to access SRH services.

Objectives: The objectives of the evaluation are to assess: a) to what extent and how the new Adolescent Reproductive Health (ARH) partnership model and integrated system of delivery is working to meet its intended objectives and the needs of adolescents; b) adolescent user experiences across key quality dimensions and outcomes; c) how ITH programme has influenced adolescent voice, decision-making autonomy, power dynamics and provider accountability; d) how community support for adolescent reproductive and sexual health initiatives has changed as a result of this programme.

Methodology ITH programme is being implemented in two phases, a formative planning and experimentation in the first year from April 2017 to March 2018, and a national roll out and implementation from April 2018 to March 2020. This second phase is informed by an Annual Programme Review and thorough benchmarking and assessment which informed critical changes to performance and capacity so that ITH is fit for scale. It is expected that ITH will cover approximately 250,000 adolescent girls aged 15-19 in Kenya by April 2020. The programme is implemented by a consortium of Marie Stopes Kenya (MSK), Well Told Story, and Triggerise. ITH's key implementation strategies seek to increase adolescent motivation for service use, create a user-defined ecosystem and platform to provide girls with a network of accessible subsidized and discreet SRH services; and launch and sustain a national discourse campaign around adolescent sexuality and rights. The 3-year study will employ a mixed-methods approach with multiple data sources including secondary data, and qualitative and quantitative primary data with various stakeholders to explore their perceptions and attitudes towards adolescents SRH services. Quantitative data analysis will be done using STATA to provide descriptive statistics and statistical associations / correlations on key variables. All qualitative data will be analyzed using NVIVO software.

Study Duration: 36 months - between 2018 and 2020.

Geographic coverage

Homabay,Kakamega,Nakuru and Nairobi counties

Analysis unit

Private health facilities that provide T-safe services under the In Their Hands(ITH) Program.

Universe

1.Adolescent girls aged 15-19 who enrolled on the T-safe platform and received services and those who enrolled but did not receive services from the ITH facilities. 2.Service providers incharge of provision of T-safe services in the ITH facilities. 3.Mobilisers incharge of adolescent girls aged 15-19 recruitment into the T-safe program.

Sampling procedure

Qualitative Sampling

IDI participants were selected purposively from ITH intervention areas and facilities located in the four ITH intervention counties; Homa Bay, Nakuru, Kakamega and Nairobi respectively which were selected for the midline survey. Study participants were identified from selected intervention facilities. We interviewed one service provider of adolescent friendly ITH services per facility. Additionally, we conducted IDI's with adolescent girls' who were enrolled and using/had used the ITH platform to access reproductive health services or enrolled but may not have accessed the services for other reasons.

Sample coverage We successfully conducted a total of 122 In-depth Interviews with 54 adolescents enrolled on the T-Safe platform, including those who received services and those who were enrolled but did not receive services, 39 IDIS with service providers and 29 IDIs with mobilizers. The distribution per county included 51 IDI's in Nairobi City County (24 with adolescent girls, 17 with service providers and 10 with mobilisers), 15 IDI's in Nakuru County (2 with adolescent girls,8 with service providers and 5 with mobilisers), 34 IDI's in Homa Bay County (18 with adolescent girls,8 with service providers and 8 with mobilisers) and 22 IDI's in Kakamega County (10 with adolescent girls,6 with service providers and another 6 with mobilisers.)

Sampling deviation

N/A

Mode of data collection

Face-to-face [f2f]

Research instrument

The midline evaluation included qualitative in-depth interviews with adolescent T-Safe users, adolescents enrolled in the platform but did not use the services, providers and mobilizers to assess the adolescent user experience and quality of services as well as provider accountability under the T-Safe program. Generally,the aim of the qualitative study was to assess adolescents' T-Safe users experience across quality dimensions as well as provider's experiences and accountability. The dimensions assessed include adolescent's journey with the platforms, experience with the platform, perceptions of quality of services and how the ITH platforms changed provider behavior and accountability.

Adolescent in-depth interview included:Adolescent journey,Barriers to adolescents access to SRH services,Community attitudes towards adolescent use of contraceptives,Decision making,Factors influencing decision to visit a clinic,Motivating factors for girls to join ITH,Notable changes since the introduction of ITH,Parental support ,and Perceptions about T-Safe.

Service providers in-depth interview included;Personal and professional background,Provider's experience with ITH/T-safe platform,Notable changes/influences since the introduction of ITH/T-safe,Influence/Impact on the preference of adolescent service users and health care providers as a result of the program,Impact/influence of ITH on quality of care,Facilitators and barriers for adolescents to access SRH services,Mechanisms to address the barriers,Challenges related to the facility,Feedback about facility from adolescents,Types of support needed to improve SRH services provided to adolescents Scenarios of different clients accessing SRH services,and Free node.

Mobilisers in-depth interview included;Mobilizer responsibilities and designation,Job description,Motivation for joining ITH,Personal and professional background,Training,Mobilizer roles in ITH,Mobilization process ,Experience with ITH platform,Key messages shared with adolescent about ITH/ Tsafe during enrollment,Motivating factors for adolescents to join ITH/Tsafe,Community's attitude towards ITH/Tsafe,Challenges faced by mobilizers when mobilizing adolescents for Tsafe,Adolescents view regarding platform,Addressing the challenges ,andFree node

Cleaning operations

Qualitative interviews were audio-recorded and the audio recordings were transmitted to APHRC study team by uploading the audios to google drive which was only accessible to the team. Related interview notes, participant's description forms and Informed consent forms were transported to APHRC offices in Nairobi at the end of data collection where the data transcription and coding was conducted. Audio recordings from qualitative interviews were transcribed and saved in MS Word format. The transcripts were stored electronically in password protected computers and were only accessible to the evaluation team working on the project. A qualitative software analysis program (NVIVO) was used to assist in coding and analyzing the data. A “thematic analysis” approach was used to organize and analyze the data, and to assist in the development of a codebook and coding scheme. Data was analyzed by first reading the full IDI transcripts, becoming familiar with the data and noting the themes and concepts that emerged. A thematic framework was developed from the identified themes and sub-themes and this was then used to create codes and code the raw data.

Response rate

N/A

Sampling error estimates

N/A

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.

Abstract copyright UK Data Service and data collection copyright owner. This is one dataset arising from a project whose main aims are: 1. To contribute to knowledge by engaging in a study of the relationship between Australia, New Zealand and international capital markets 1850-1950 which would focus on three key themes: i. The history of Australia and New Zealand as borrowers and debtors. ii. The rise and consolidation of the British 'colonial' market in the London capital market from the mid-nineteenth century to the late 1920s. iii. The interaction between the market disciplines to which all borrowers were subject, and the opportunities and constraints created by membership of the British Empire. The study would also evaluate recent arguments (Cain and Hopkins, 1993) about the role of the City of London in the dynamics of British imperial expansion and control with respect to two British settler societies, Australia and New Zealand. 2. To extend and revise the statistics of Australasian public debt in the period 1850-1950. 3. To create a database of Australasian overseas public loans during that period. The projects specific objectives were to complete three stages of research: 1. The consultation of archival and printed official sources in the United Kingdom and Australia relating to Australasian borrowing activity and relations with overseas creditors during nineteenth century. These either had not been available to, or were not consulted by, earlier historians. 2. The collection of quantitative data for revised statistics of Australian and New Zealand public debt between 1850 and 1950. 3. The collection of data for a database of Australasian overseas public loans during that period. Main Topics: This dataset publishes new statistics of Australian colonial and state debt, and of capital raised by all Australian public borrowers (including corporation) in London, until 1914. Current historical statistics do not distinguish between stocks of debt held locally or abroad. Moreover, the time series of new capital subscribed or received in London prepared by Butlin, Simon, Hall, and others often aggregate all colonial public borrowing, have different terminal dates, and are inconsistent with each other. The new statistics remedy these deficiencies. Three types of table are presented. The first disaggregates, and where necessary corrects, the official annual statistics of stocks of outstanding debt of each Australian colony, distinguishing between the place of original sale, long and short-term securities, and gross new issues (i.e. the nominal value of all securities sold) and repayments. The second shows the stocks of long and short term debt held in Australia and the United Kingdom. These are taken principally from Statistical Registers, and include debt (e.g. stock issued by Savings Banks) omitted from the official statistics in the early years. The final type of table summarises the principal annual flows in London of capital created (including as a result of conversions and exchanges), subscribed, received, and amortized for each colonial government and for public corporations as a single group. It excludes flows arising from remittance of securities originally sold in the colonies, but includes transfers from London to colonial registers and purchases from sinking funds where they are known. The data is presented in 18 spreadsheets and are of seven separate borrowers: New South Wales (3 spreadsheets), Victoria (3), Queensland (3), South Australia (3), Tasmania (2), Western Australia (2), and public corporations (1). Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

Abstract

Kenya Investment Climate Survey was carried out in 2002-2003 by the World Bank's Regional Program on Enterprise Development (RPED) in collaboration with Kenya Institute of Public Policy Research and Analysis (KIPPRA). The survey covered 284 formal manufacturing firms.

The questionnaire contained a range of questions on such issues as the production process, cost of inputs, access to finance, types and cost of labor used, and costs incurred in preventing or treating HIV/AIDS.

The Investment Climate Surveys (ICS) were conducted by the World Bank and its partners across all geographic regions and covered firms of all sizes in many industries. The ICS collected a wide array of qualitative and quantitative information through face-to-face interviews with managers and owners regarding the investment climate in their country and the productivity of their firms. Topics covered in the ICS included the obstacles to doing business, infrastructure, finance, labor, corruption and regulation, contract enforcement, law and order, innovation and technology, and firm productivity. Taken together, the qualitative and quantitative data helped connect a country’s investment climate characteristics with firm productivity and performance.

Firm-level surveys have been administered since 1998 by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit (FPDEA). Enterprise Surveys, a replacement for Investment Climate Surveys, are now conducted by the Enterprise Analysis Unit.

Geographic coverage

National

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was drawn from a census conducted by the Kenya Central Bureau of Statistics (CBS) of nearly 2000 formal manufacturing firms employing more than 250000 full-time employees. In order to ensure representation of all types of firms, the sample was stratified across location, sub-sectors, and size in 148 clusters. The survey covered seven sub-sectors in five urban areas: Nairobi, Mombasa, Eldoret, Kisumu and Nakuru.

Nine manufacturing sub-sectors were: Agroindustry, Chemicals/Paints, Construction Materials, Furniture, Metals, Paper/Publishing/Printing, Plastics, Textile/Leather, and Wood. Four size classes were used: Small (11-49 employees), Medium (50-99 employees), Large (100-499 employees), and Very Large (500 and more employees). 368 firms were selected randomly from the clusters, representing roughly 20 percent of all formal firms. Several firms, often non-African and foreign ones, refused to be interviewed. Whenever possible, these firms were replaced with "new" firms having the same characteristics as the ones that refused. Due to the high rate of refusal, however, the replacement strategy was only partly successful and, in the end, 284 firms completed a survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Investment Climate Survey Questionnaire.

Soil generic group (SGG) is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Roper River Water Resource Assessment (ROWRA) through the digital soil mapping process (DSM). SGG data has been created to simplify the complex information of individual soils and soil attributes for extension, planning and management. This data simultaneously covers a number of purposes: to be descriptive so as to assist non-expert communication regarding soil and resources; to be relatable to agricultural potential; and to align, where practical, to the classes of the Australian Soil Classification system (ASC) (Isbell and National Committee on Soil and Terrain, 2016). This SGG raster data represents a modelled dataset of 13 classes derived from rules applied to measured site data and modelled with environmental covariates. Descriptions of the 13 SGG classes, their rules and the spatial data value descriptions are supplied with this data. SGG mapping was also used as a minor input into the land suitability framework but primarily as a communication tool. This raster data provides improved soil information used to underpin and identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO ROWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach. The DSM process is described in the CSIRO ROWRA published report ‘Soils and land suitability for the Roper catchment, Northern Territory’. A technical report from the CSIRO Roper River Water Resource Assessment to the Government of Australia. The Roper River Water Resource Assessment provides a comprehensive overview and integrated evaluation of the feasibility of aquaculture and agriculture development in the Roper catchment NT as well as the ecological, social and cultural (indigenous water values, rights and aspirations) impacts of development. Lineage: This soil generic group dataset has been generated from a range of inputs and processing steps. Following is an overview. For more information refer to the CSIRO ROWRA published reports and in particular ' Soils and land suitability for the Roper catchment, Northern Territory’. A technical report from the CSIRO Roper River Water Resource Assessment to the Government of Australia. 1. Collated existing data (relating to: soils, climate, topography, natural resources, remotely sensed, of various formats: reports, spatial vector, spatial raster etc). 2. Selection of additional soil and land attribute site data locations by a conditioned Latin hypercube statistical sampling method applied across the covariate data space. 3. Fieldwork was carried out to collect new attribute data, soil samples for analysis and build an understanding of geomorphology and landscape processes. 4. Database analysis was performed to extract the data to specific selection criteria required for the attribute to be modelled. 5. The R statistical programming environment was used for the attribute computing. Models were built from selected input data and covariate data using predictive learning from a Random Forest approach implemented in the ranger R package. 6. Create soil generic group Digital Soil Mapping (DSM) attribute raster dataset. DSM data is a geo-referenced dataset, generated from field observations and laboratory data, coupled with environmental covariate data through quantitative relationships. It applies pedometrics - the use of mathematical and statistical models that combine information from soil observations with information contained in correlated environmental variables, remote sensing images and some geophysical measurements. 7. Companion predicted reliability data was produced from the 500 individual Random Forest attribute models created. 8. QA Quality assessment of this DSM attribute data was conducted by three methods. Method 1: Statistical (quantitative) method of the model and input data. Testing the quality of the DSM models was carried out using data withheld from model computations and expressed as OOB and confusion matrix results, giving an estimate of the reliability of the model predictions. These results are supplied. Method 2: Statistical (quantitative) assessment of the spatial attribute output data presented as a raster of the attributes “reliability”. This used the 500 individual trees of the attributes RF models to generate 500 datasets of the attribute to estimate model reliability for each attribute. For categorical attributes the method for estimating reliability is the Confusion Index. This data is supplied. Method 3: Collecting independent external validation site data combined with on-ground expert (qualitative) examination of outputs during validation field trips. Across each of the study areas a two week validation field trip was conducted using a new validation site set which was produced by a random sampling design based on conditioned Latin Hypercube sampling using the reliability data of the attribute. The modelled DSM attribute value was assessed against the actual on-ground value. These results are published in the report cited in this metadata record.

Classification and types of school sports facilities (SSFs).

Abstract

The purpose of the Tajikistan LSS surveys has been to provide quantitative data at the individual, household and community level that will facilitate purposeful policy design on issues of welfare and living standards of the population of the Republic of Tajikistan. Since 2007, the studies have been done in collaboration with World Bank and UNICEF and implementation by Tajik National Committee for Statistics. The 2007 LSS survey is based on the 2003 LSS and 2005 MICS survey with additional questions and modules

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

A detailed description of the sampling methodology is available in appendix to the document "Basic Information Document".

The Tajikistan LSS sample was designed to allow reliable estimation of poverty and most variables for a variety of other living standard indicators at the various domains of interest based on a representative probability sample on the level of: • Tajikistan as a whole
• Total urban and total rural areas • The five main administrative regions (oblasts) of the country: Dushanbe, Rayons of Republican Subordination (RRS), Sogd, Khatlon, and Gorno-Badakhshan Autonomous Oblast (GBAO)

The last census was conducted in 2000 and covered all five main administrative regions (oblasts) of the country (Dushanbe, RRS, Sogd, Khatlon, and GBAO). Each oblast was further subdivided into smaller areas called census section, instructor's sector and enumeration sector (ES). Each ES is either totally urban or rural. The list of ESs has census information on the population of each ES, and the ES lists were grouped by oblast.

In 2005, UNICEF implemented a Multiple Indicator Cluster Survey (MIC-05) in Tajikistan during which an electronic database of the ES information was created. Information in this database included: oblast, rayon, jamoat, settlement type, city/village, ES code, and population. Information from this database was used in the sample design of the TLSS07.

The total number of clusters for the Tajikistan LSS 2007 was established as 270 and total number of households per cluster was established as 18, resulting in a sample size of 4,860. The sample size was determined by considering: • The reliability of the survey estimates on both regional and national level • Quality of the data collected for the survey • Cost in time for the data collection • An oversample in 7 rayons in Khatlon

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data Entry and Cleaning

The data entry program was designed using CSPro, a data entry package developed by the US Census Bureau. This software allows programs to be developed to perform three types of data checks: (a) range checks; (b) intra-record checks to verify inconsistencies pertinent to the particular module of the questionnaire; and (c) inter-record checks to determine inconsistencies between the different modules of the questionnaire.

The data from the First Round were key entered at the Goskomstat headquarters in Dushanbe starting 4 October 2007 through 25 November 2007. The Second Round and Sughd data were key entered from 26 November 2007 through 12 December 2007. All of the data were double entered with both the First Round, Second Round and Sughd re-collection double entry being completed by 22 January 2008.

Data appraisal

The data cleaning process began in February 2008 and was completed at the end of May 2008.

How to Use the Data:

There are three separate data bases with the data from the TLSS07. The data from each data collection is maintained separately. The data sets have similar names in each of the three separate data collections. First Round data sets have names in the form of "r1mnp" where "n" is the number of the module, and "p" is the part of the module (if any). Data from the Subjective Poverty module would be stored as "r1m9" and data from the Migration module, Part C Family Members Living Away from the Household would be stored as "r1m2c". Second Round data set names have a similar form "r2mnp". Data sets from the Sughd collection replace the "m" of the First Round with "sm", such as sm12a1.

The variable names have a similar format. Each variable name includes the module in which the variable is found and the question number. For example, question 10 in Module 4 Health, Part B Utilization of Outpatient Health Care is "m4b_q10". The variable names in all three of the data collections have the same format.

In addition to the individual roster files for each data base, there is also one roster file for all three data bases, rosterall. This roster file contains the information on all of the households and household members who are included in the data. There is a variable (source) indicating if the household/member is: (a) in Round 1 only; (b) in Round 2 only; (c) in Round 1 and Round 2; or (d) in the Sughd data. It is important to pay attention to this variable as the recall periods for the Subjective Poverty and Food Security Module (9A) is the last 4 weeks in the First Round, but changed to the last 2 weeks in the Second Round and the Sughd collection. In addition, the order of the question in the Expenditure On Food In The Last 7 Days, Module 10, changed

Abstract

Within the scope of the efforts of the Palestinian Central Bureau of Statistics in the provision of official statistics on various aspects of Palestinian life of the Palestinian society, and given the importance of culture and its role in the human life and the resulting rights for the role of the impact on building society as a whole, the Central Bureau of Statistics implemented a survey on culture of households and individuals in Palestine, to provide the necessary quantitative data on this dimension in the process of composition of the Palestinian rights.

The Household Culture Survey aims to provide quantifiable indicators related to cultural activities and the role of modern methods of media in spreading the culture. Examples of such information include: - Availability of a home library, type of library collection and the culture of reading. - Tendency to listen to the radio or viewing television. - Popularity to visit cultural institutions and the practice of individuals to cultural activities. - Popularity of TV and broadcasting stations and the main sources of entertainment and recreation. - Proliferation of newspapers and magazines and how to obtain them, and the sections of the newspapers that have the largest number of readers. - The scope of household monitoring to the type of television programs being viewed by children, and the number of hours being spent watching television.

Geographic coverage

Palestine (West Bank and Gaza Strip) , type of locality (Urban, Rural, Refugee Camps) and governorate.

Analysis unit

• Household.
• Person 10 years and over .

Universe

All Palestinian households and individuals whose usual place of residence is in Palestine with focus on persons aged 10 years and over in the year 2014.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample frame The sampling frame consists of list of enumeration areas adopted in the Population, Housing and Establishment Census 2007. Each enumeration area has an average size of about 124 households. These were used in the first phase as Preliminary Sampling Units in the process of selecting the survey sample.

Sample size The total sample size of the survey was 7,268 households of which 6,000 completed the interview.

Sample Design The sample is stratified clustered systematic random sample. The design is comprised of three phases:

Phase I: Random sample of 240 enumeration areas. Phase II: Selection of (25) household from each enumeration area, selected in phase one, using systematic random manner. Phase III: Selection of a person (aged 10 years or more) in the field from the selected households; and KISH TABLES are used in the process of persons selection to ensure indiscriminate selection.

Sample Strata Distribution of the sample was stratified by: 1. Governorate (16 governorates, J1). 2. Type of locality (urban, rural and camps).

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was developed based on the requirements identified and after discussion with stakeholders. A workshop was conducted at the Palestinian Central Bureau of Statistics as part of the user producer dialogue to discuss the indicators of the survey.

The survey comprises identification data of the questionnaire, quality controls, and three main sections: Section I: Data about household members that include identification fields and the characteristics of household members (demographic and social) such as the relationship of individuals to head of household, sex, birth date, and age.

Section II: Household data include information on the availability of a library and its contents, access to newspapers, listening to radio stations, and ownership of a TV set and DVD. This section also includes information on topics related to time spent watching TV, preferred TV programs and household monitoring of children (5-17 years old) while watching television.

Section III: Data on persons (aged 10 years or over) include information about reading newspapers, magazines and periodic publications, the habit of reading books and the type of books read. Data also include watching television, listening to the radio, and listening to the Voice of Palestine, plus engagement in cultural activities by individuals in their free time and the locations frequented.

Cleaning operations

Preparation of Data Entry Program: This stage included preparation of the data entry programs using an ACCESS package and defining data entry control rules to avoid errors, plus validation inquiries to examine the data after it had been captured electronically.

Data Entry: The data entry process started on 8 May 2014 and ended on 23 June 2014. The data entry took place at the main PCBS office and in field offices using 28 data clerks.

Editing and Cleaning procedures: Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

Response rate

The survey sample consists of (7,268) households, of which (6,000) households completed the interview: (3,925) households from the West Bank and (2,075) households in Gaza Strip. Weights were modified to account for the non-response rate. Response rate = 85.6%

Sampling error estimates

There are many aspects of the concept of data quality; this includes the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are three components to the quality of statistics: accuracy, comparability, and quality control procedures.

Checks on data accuracy cover many aspects of the survey and include statistical errors due to the use of a sample, non-statistical errors resulting from field workers or survey tools, and response rates and their effect on estimations. This section includes:

Statistical Errors Data of this survey may be affected by statistical errors due to the use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators.

Variance calculations revealed that there is no problem in disseminating results nationally or regionally (the West Bank, Gaza Strip), but some indicators show high variance by governorate, as noted in the tables of the main report.

Non-Statistical Errors Non-statistical errors are possible at all stages of the project, during data collection or processing. These are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous efforts were made to train the field workers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, and practical and theoretical training took place during the training course. Training manuals were provided for each section of the questionnaire, along with practical exercises in class and instructions on how to approach respondents to reduce refused cases. Data entry staff were trained on the data entry program, which was tested before starting the data entry process.

Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

The sources of non-statistical errors can be summarized as: 1. Some of the households were not at home and could not be interviewed, and some households refused to be interviewed. 2. In unique cases, errors occurred due to the way the questions were asked by interviewers and respondents misunderstood some of the questions.

The Detection of Crime, Resource Deployment, and Predictors of Success: A Multi-Level Analysis of Closed-Circuit Television (CCTV) in Newark, NJ collection represents the findings of a multi-level analysis of the Newark, New Jersey Police Department's video surveillance system. This collection contains multiple quantitative data files (Datasets 1-14) as well as spatial data files (Dataset 15 and Dataset 16). The overall project was separated into three components:

• Component 1 (Dataset 1, Individual CCTV Detections and Calls-For-Service Data and Dataset 2, Weekly CCTV Detections in Newark Data) evaluates CCTV's ability to increase the "certainty of punishment" in target areas;
• Component 2 (Dataset 3, Overall Crime Incidents Data; Dataset 4, Auto Theft Incidents Data; Dataset 5, Property Crime Incidents Data; Dataset 6, Robbery Incidents Data; Dataset 7, Theft From Auto Incidents Data; Dataset 8, Violent Crime Incidents Data; Dataset 9, Attributes of CCTV Catchment Zones Data; Dataset 10, Attributes of CCTV Camera Viewsheds Data; and Dataset 15, Impact of Micro-Level Features Spatial Data) analyzes the context under which CCTV cameras best deter crime. Micro-level factors were grouped into five categories: environmental features, line-of-sight, camera design and enforcement activity (including both crime and arrests); and
• Component 3 (Dataset 11, Calls-for-service Occurring Within CCTV Scheme Catchment Zones During the Experimental Period Data; Dataset 12, Calls-for-service Occurring Within CCTV Schemes During the Experimental Period Data; Dataset 13, Targeted Surveillances Conducted by the Experimental Operators Data; Dataset 14, Weekly Surveillance Activity Data; and Dataset 16, Randomized Controlled Trial Spatial Data) was a randomized, controlled trial measuring the effects of coupling proactive CCTV monitoring with directed patrol units.

Over 40 separate four-hour tours of duty, an additional camera operator was funded to monitor specific CCTV cameras in Newark. Two patrol units were dedicated solely to the operators and were tasked with exclusively responding to incidents of concern detected on the experimental cameras. Variables included throughout the datasets include police report and incident dates, crime type, disposition code, number of each type of incident that occurred in a viewshed precinct, number of CCTV detections that resulted in any police enforcement, and number of schools, retail stores, bars and public transit within the catchment zone.

Abstract

Uganda Investment Climate Survey was carried out between November 2002 and April 2003 by the World Bank's Regional Program on Enterprise Development (RPED) in collaboration with the Uganda Manufacturers Association Consultancy and Information Services (UMACIS). The survey covered 392 firms across four sectors (commercial agriculture, construction, manufacturing, and tourism) and three regions (central, northeast, and southwest). The dataset described in this study includes only manufacturing establishments (300 observations).

The questionnaire contained a range of questions on such issues as the production process, cost of inputs, access to finance, types and cost of labor used, and costs incurred in preventing or treating HIV/AIDS.

The Investment Climate Surveys (ICS) were conducted by the World Bank and its partners across all geographic regions and covered firms of all sizes in many industries. The ICS collected a wide array of qualitative and quantitative information through face-to-face interviews with managers and owners regarding the investment climate in their country and the productivity of their firms. Topics covered in the ICS included the obstacles to doing business, infrastructure, finance, labor, corruption and regulation, contract enforcement, law and order, innovation and technology, and firm productivity. Taken together, the qualitative and quantitative data helped connect a country’s investment climate characteristics with firm productivity and performance.

Firm-level surveys have been administered since 1998 by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit (FPDEA). Enterprise Surveys, a replacement for Investment Climate Surveys, are now conducted by the Enterprise Analysis Unit.

Geographic coverage

National

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of Ugandan firms was designed as a stratified random sample on the basis of census data from the Uganda Bureau of Statistics.

The sample frame was obtained from the Uganda Bureau of Statistics, which compiled the list during a nationwide census in 2001-2002. The sample frame was stratified by location, manufacturing subsector, and size. To adequately reflect the geographic distribution of firms, three regions were defined on the basis of existing districts: the central region, which includes the Kampala district; the northeast region; and the southwest region. Similarly, to obtain the correct distribution of activity in manufacturing, nine broad subsectors were defined using the ISIC: agro-industry; chemicals and paints; construction materials; furniture; metals; paper, printing, and publishing; plastics; textiles and leather products; and wood. Finally, to allow comparisons with datasets compiled for other African countries by the Regional Program on Enterprise Development (RPED), three standard size classes were used: small (10-49 employees), medium-size (50-99), and large (100 or more). Clusters were then defined on the basis of the location, size, and sector of firms.

Following the stratification of the sample frame, firms were selected randomly in each cluster. A total sample of 410 firms was drawn, with an overall sampling rate of 28.5 percent. The surveyed sample differs slightly from the drawn sample because of some replacement sampling, but it retains the key characteristics: the importance of firms with 100 or more employees and the prominence of the central region. The surveyed sample includes 392 firms (a sampling rate of 27.2 percent). Firms with 100 or more workers account for about 86 percent of the employment in the sample, and the central region accounts for 66 percent of the enterprises and about 66.5 percent of the employment.

The difference between the theoretical and the surveyed sample is explained by several factors: some firms refused to be interviewed, several firms changed size class (the survey was undertaken about a year after the completion of the census), and some firms either did not exist or had changed their activity. Some of these "missing" firms were replaced with firms with similar or identical characteristics. These replacements replacements from the sample frame were required to be similar in size and to operate in the same sector and the same region.

The manufacturing subsample is the largest component of the overall sample. It includes 300 firms, or about 40 percent of the existing manufacturing firms in the sample frame, and accounts for about 75 percent of the manufacturing employment. This subsample reflects the dominance of the central region and large firms. But it differs slightly from the sample frame in its structure. In the subsample 68 percent of firms are in the central region (compared with 72 percent in the frame) and 19.7 percent of firms have 100 or more employees (compared with 10.6 percent in the frame).

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instrument is available: - Investment Climate Survey Questionnaire.

Snapshot img

The drug-eluting stent market size will grow up to USD 1.57 billion at a CAGR of 4.67% during 2021-2025.

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'North America will generate growth across all the years of the forecast period between 2020 and 2025. The year-on-year growth during this period will vary between 3.78% and 4.89%.'

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Key drivers such as the high prevalence of atherosclerosis are notably supporting the drug-eluting stent market growth. However, one of the foremost factors impeding market growth is the decline in the price of drug-eluting stents. Get detailed insights on the trends and challenges to stay prepared for the obstacles in the future, which will help companies analyze and develop growth strategies.

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Market Overview

The parent, global healthcare supplies market, covers products and companies engaged in R&D of a variety of product categories spanned across medical consumables that are used for the diagnosis and treatment of various diseases. Technavio calculates the global healthcare supplies market size based on the combined revenue generated by manufacturers of medical supplies such as syringes, drapes, gloves, and gowns. Growth in the global healthcare supplies market will be driven by the following factors: Increasing life expectancy.

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The drug-eluting stent market size, share, & trends analysis report offers an up-to-date study of the geographical composition of the market. 32% of the market’s growth will originate from North America during the forecast period. The US is the key market for drug-eluting stents in North America.

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The drug-eluting stent market share growth by the polymer free coating segment has been sign

1The totals in this column equal the number of articles using a particular type of data, minus instances of duplicate classification by type of company within category of type of data. These instances were: Other types of data were used by articles classified as both tobacco and transportation, both mining and manufacturing, and both tobacco and alcohol, and quantitative data from internal company studies were used by the article classified as both mining and manufacturing. The overall column total is not shown, as it is greater than the total number of included articles (n = 361) because several articles used multiple types of internal documents.2The totals in this row equal the total number of articles for each type of company, minus instances where articles used multiple types of data, of which there are too many to list. The totals for the columns are therefore not equal to the sum of the classifications within the columns. The overall row total is not shown, as it is greater than the total number of included articles (N = 361) because three articles were classified with two types of companies.

The global market size of Laser Painted Pictures is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Laser Painted Pictures Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Laser Painted Pictures industry. The key insights of the report:
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3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Laser Painted Pictures industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
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There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Laser Painted Pictures as well as some small players.
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For product type segment, this report listed main product type of Laser Painted Pictures market
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* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
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For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
* Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and non-economic aspects
* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.

The global market size of Clinical Data Management is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global Clinical Data Management Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global Clinical Data Management industry. The key insights of the report:
1.The report provides key statistics on the market status of the Clinical Data Management manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of Clinical Data Management industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of Clinical Data Management Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of Clinical Data Management as well as some small players.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of Clinical Data Management market
* Product Type I
* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Application I
* Application II
* Application III

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
* Market dynamics scenario, along with growth opportunities of the market in the years to come
* Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and non-economic aspects
* Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
* Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
* 1-year analyst support, along with the data support in excel format.
We also can offer customized report to fulfill special requirements of our clients. Regional and Countries report can be provided as well.