The Delta Neighborhood Physical Activity Study was an observational study designed to assess characteristics of neighborhood built environments associated with physical activity. It was an ancillary study to the Delta Healthy Sprouts Project and therefore included towns and neighborhoods in which Delta Healthy Sprouts participants resided. The 12 towns were located in the Lower Mississippi Delta region of Mississippi. Data were collected via electronic surveys between August 2016 and September 2017 using the Rural Active Living Assessment (RALA) tools and the Community Park Audit Tool (CPAT). Scale scores for the RALA Programs and Policies Assessment and the Town-Wide Assessment were computed using the scoring algorithms provided for these tools via SAS software programming. The Street Segment Assessment and CPAT do not have associated scoring algorithms and therefore no scores are provided for them. Because the towns were not randomly selected and the sample size is small, the data may not be generalizable to all rural towns in the Lower Mississippi Delta region of Mississippi. Dataset one contains data collected with the RALA Programs and Policies Assessment (PPA) tool. Dataset two contains data collected with the RALA Town-Wide Assessment (TWA) tool. Dataset three contains data collected with the RALA Street Segment Assessment (SSA) tool. Dataset four contains data collected with the Community Park Audit Tool (CPAT). [Note : title changed 9/4/2020 to reflect study name] Resources in this dataset:Resource Title: Dataset One RALA PPA Data Dictionary. File Name: RALA PPA Data Dictionary.csvResource Description: Data dictionary for dataset one collected using the RALA PPA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Two RALA TWA Data Dictionary. File Name: RALA TWA Data Dictionary.csvResource Description: Data dictionary for dataset two collected using the RALA TWA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Three RALA SSA Data Dictionary. File Name: RALA SSA Data Dictionary.csvResource Description: Data dictionary for dataset three collected using the RALA SSA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Four CPAT Data Dictionary. File Name: CPAT Data Dictionary.csvResource Description: Data dictionary for dataset four collected using the CPAT.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset One RALA PPA. File Name: RALA PPA Data.csvResource Description: Data collected using the RALA PPA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Two RALA TWA. File Name: RALA TWA Data.csvResource Description: Data collected using the RALA TWA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Three RALA SSA. File Name: RALA SSA Data.csvResource Description: Data collected using the RALA SSA tool.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Four CPAT. File Name: CPAT Data.csvResource Description: Data collected using the CPAT.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Data Dictionary. File Name: DataDictionary_RALA_PPA_SSA_TWA_CPAT.csvResource Description: This is a combined data dictionary from each of the 4 dataset files in this set.

Working with SPSS, SAS, Shazam, Excel and STATA users - why are there so many statistical packages and how do we keep our users happy while making our lives easier, outside of therapy?

This formatted dataset (AnalysisDatabaseGBD) originates from raw data files from the Institute of Health Metrics and Evaluation (IHME) Global Burden of Disease Study (GBD2017) affiliated with the University of Washington. We are volunteer collaborators with IHME and not employed by IHME or the University of Washington.

The population weighted GBD2017 data are on male and female cohorts ages 15-69 years including noncommunicable diseases (NCDs), body mass index (BMI), cardiovascular disease (CVD), and other health outcomes and associated dietary, metabolic, and other risk factors. The purpose of creating this population-weighted, formatted database is to explore the univariate and multiple regression correlations of health outcomes with risk factors. Our research hypothesis is that we can successfully model NCDs, BMI, CVD, and other health outcomes with their attributable risks.

These Global Burden of disease data relate to the preprint: The EAT-Lancet Commission Planetary Health Diet compared with Institute of Health Metrics and Evaluation Global Burden of Disease Ecological Data Analysis. The data include the following: 1. Analysis database of population weighted GBD2017 data that includes over 40 health risk factors, noncommunicable disease deaths/100k/year of male and female cohorts ages 15-69 years from 195 countries (the primary outcome variable that includes over 100 types of noncommunicable diseases) and over 20 individual noncommunicable diseases (e.g., ischemic heart disease, colon cancer, etc). 2. A text file to import the analysis database into SAS 3. The SAS code to format the analysis database to be used for analytics 4. SAS code for deriving Tables 1, 2, 3 and Supplementary Tables 5 and 6 5. SAS code for deriving the multiple regression formula in Table 4. 6. SAS code for deriving the multiple regression formula in Table 5 7. SAS code for deriving the multiple regression formula in Supplementary Table 7
8. SAS code for deriving the multiple regression formula in Supplementary Table 8 9. The Excel files that accompanied the above SAS code to produce the tables

For questions, please email davidkcundiff@gmail.com. Thanks.

This is the SAS 9.4 data set and the same data set as an excel file that is the basis and starting point for all analyses

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Credit report of Excel Plastic Piping Systems Sas contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

The Serial Attached SCSI (SAS) Solid State Drive (SSD) market is experiencing steady growth, driven by increasing demand for high-performance storage solutions in enterprise data centers and demanding applications. The market's robust performance is fueled by several factors, including the need for faster data access speeds, enhanced reliability, and improved data integrity compared to traditional hard disk drives (HDDs). The rising adoption of cloud computing and big data analytics further fuels this growth, as these technologies require massive storage capacity and rapid data processing capabilities, which SAS SSDs excel at delivering. While the overall storage market is witnessing a shift towards NVMe technology, SAS SSDs continue to hold a significant share, especially in applications requiring high-endurance and predictable performance, such as enterprise servers and storage arrays. This sustained relevance is expected to contribute to consistent market growth over the forecast period. Several key trends are shaping the SAS SSD market. The ongoing development of higher capacity drives with improved power efficiency is a major factor. Furthermore, the increasing integration of advanced features such as data encryption and self-monitoring capabilities is enhancing the security and reliability of these drives, making them more attractive to businesses with stringent data protection requirements. However, the market faces challenges, including the higher cost of SAS SSDs compared to other storage technologies like SATA SSDs and the competitive pressure from newer NVMe drives. Nevertheless, the continued demand from specific enterprise applications, along with ongoing technological advancements, is expected to ensure a positive outlook for the SAS SSD market in the coming years. We project a continued CAGR of approximately 6-8% through 2033, based on historical growth rates and current market trends.

three excel sheets contain exported SAS datasets that were analyzed for the paper. Each corresponds to the SAS code included in this Figshare project.

The Delta Produce Sources Study was an observational study designed to measure and compare food environments of farmers markets (n=3) and grocery stores (n=12) in 5 rural towns located in the Lower Mississippi Delta region of Mississippi. Data were collected via electronic surveys from June 2019 to March 2020 using a modified version of the Nutrition Environment Measures Survey (NEMS) Farmers Market Audit tool. The tool was modified to collect information pertaining to source of fresh produce and also for use with both farmers markets and grocery stores. Availability, source, quality, and price information were collected and compared between farmers markets and grocery stores for 13 fresh fruits and 32 fresh vegetables via SAS software programming. Because the towns were not randomly selected and the sample sizes are relatively small, the data may not be generalizable to all rural towns in the Lower Mississippi Delta region of Mississippi. Resources in this dataset:Resource Title: Delta Produce Sources Study dataset . File Name: DPS Data Public.csvResource Description: The dataset contains variables corresponding to availability, source (country, state and town if country is the United States), quality, and price (by weight or volume) of 13 fresh fruits and 32 fresh vegetables sold in farmers markets and grocery stores located in 5 Lower Mississippi Delta towns.Resource Software Recommended: Microsoft Excel,url: https://www.microsoft.com/en-us/microsoft-365/excel Resource Title: Delta Produce Sources Study data dictionary. File Name: DPS Data Dictionary Public.csvResource Description: This file is the data dictionary corresponding to the Delta Produce Sources Study dataset.Resource Software Recommended: Microsoft Excel,url: https://www.microsoft.com/en-us/microsoft-365/excel

Output from programming code written to summarize fates of immature monarch butterflies collected and raised in captivity following SOP 4 (ServCat reference 103368). Collection and raising was conducted by crews from Neal Smith (IA), Necedah (WI) NWRs and near the town of Lamoni, Iowa. Results are given in tabular format in the excel file labeled as 2017 Metrics. Additional output from the SAS analysis code is given in the mht file.

This is a front end to a database containing all service personnel recorded on JPA. The system contains snapshots of data from April 2006 to the present. It is used for producing statistics on the service manpower state. The main repository for the data is on the NEMESIS system. However throughout the agency there is a huge volume of files, SAS, Excel, Access, MySQL containing extracts from the production data. These are held on the various Asante fileservers as evidence for particular Parliamentary Questions (PQ) that have been answered from the data. These extracts probably run into the 1000s. They are retained indefinitely as DASA policy is that they need to be able to re-create any information used to answer a PQ.

The Delta Food Outlets Study was an observational study designed to assess the nutritional environments of 5 towns located in the Lower Mississippi Delta region of Mississippi. It was an ancillary study to the Delta Healthy Sprouts Project and therefore included towns in which Delta Healthy Sprouts participants resided and that contained at least one convenience (corner) store, grocery store, or gas station. Data were collected via electronic surveys between March 2016 and September 2018 using the Nutrition Environment Measures Survey (NEMS) tools. Survey scores for the NEMS Corner Store, NEMS Grocery Store, and NEMS Restaurant were computed using modified scoring algorithms provided for these tools via SAS software programming. Because the towns were not randomly selected and the sample sizes are relatively small, the data may not be generalizable to all rural towns in the Lower Mississippi Delta region of Mississippi. Dataset one (NEMS-C) contains data collected with the NEMS Corner (convenience) Store tool. Dataset two (NEMS-G) contains data collected with the NEMS Grocery Store tool. Dataset three (NEMS-R) contains data collected with the NEMS Restaurant tool. Resources in this dataset:Resource Title: Delta Food Outlets Data Dictionary. File Name: DFO_DataDictionary_Public.csvResource Description: This file contains the data dictionary for all 3 datasets that are part of the Delta Food Outlets Study.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset One NEMS-C. File Name: NEMS-C Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for convenience stores.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Two NEMS-G. File Name: NEMS-G Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for grocery stores.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Three NEMS-R. File Name: NEMS-R Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for restaurants.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel

Transects in backwaters of Navigation Pools 4 and 8 of the Upper Mississippi River (UMR) were established in 1997 to measure sedimentation rates. Annual surveys were conducted from 1997-2002 and then some transects surveyed again in 2017-18. Changes and patterns observed were reported on in 2003 for the 1997-2002 data, and a report summarizing changes and patterns from 1997-2017 will be reported on at this time. Several variables are recorded each survey year and placed into an Excel spreadsheet. The spreadsheets are read with a SAS program to generate a SAS dataset used in SAS programs to determine rates, depth loss, and associations between depth and change through regression.

The Washington SAC provides access to crime statistics through several methods; CrimeStats Online, the Uniform Crime Report (UCR), and the National Incident Based Reporting System (NIBRS). Queries are web-based interfaces that allow users to query Washington crime data online. For more detailed analyses, the UCR and NIBRS data are available in Excel spreadsheets and SAS datasets. County-level summaries from the Criminal Justice Data Book are available in Excel as well.

This is a front end to a flat file system containing historical Army, Navy and RAF manpower data from there systems prior to migration to JPA. The system also contains Civilian manpower data from HRMS which continues to be updated. However throughout the agency there is a huge volume of files, SAS, Excel, Access, MySQL containing extracts from the production data. These are held on the various Asante fileservers as evidence for particular Parliamentary Questions (PQ) that have been answered from the data. These extracts probably run into the 1000s. They are retained indefinitely as DASA policy is that they need to be able to re-create any information used to answer a PQ.

Documentation (Word file), SAS 9.4 program files and Excel spreadsheets used in generating the web-based database of Minnesota farmland assessor estimated market values by township for 2021. If you don't have SAS and would like to view the .sas program files, one approach is to make a copy of the file, rename it with a .txt extension, and open it in Notepad. The SAS database files can also be exported using R if you don't have SAS.

Sabotaging milkweed by monarch caterpillars (Danaus plexippus) is a famous textbook example of disarming plant defence. By severing leaf veins, monarchs are thought to prevent the flow of toxic latex to their feeding site. Here, we show that sabotaging by monarch caterpillars is not only an avoidance strategy. While young caterpillars appear to avoid latex, late-instar caterpillars actively ingest exuding latex, presumably to increase sequestration of cardenolides used for defence against predators. Comparisons with caterpillars of the related but non-sequestering common crow butterfly (Euploea core) revealed three lines of evidence supporting our hypothesis. First, monarch caterpillars sabotage inconsistently and therefore the behaviour is not obligatory to feed on milkweed, whereas sabotaging precedes each feeding event in Euploea caterpillars. Second, monarch caterpillars shift their behaviour from latex avoidance in younger to eager drinking in later stages, whereas Euploea caterpil..., , , Readme for the statistical documentation for the publication: Monarchs sabotage milkweed to acquire toxins, not to disarm plant defense Authors: Anja Betz, Robert Bischoff, Georg Petschenka

For the statistical documentation, we provide the following files: This readme gives a brief outline of the different files and data provided in the statistical documentation Subfolders for each experiment containing

• Excel files with just the data, SAS code files for analysis of each dataset with comments SAS dataset files (sas7bdat) a data dictionary.txt that defines all variables of all datasets

Disclaimer: Excel automatically formats numbers. We do not take any responsibility for automatic formatting of the numbers by Excel. This might lead to different results, if the Excel files are used for analysis. The sas7bdat files, or data at the start of the individual sas-analysis files should be resistant to automatic formatting, so we suggest using them for analysis.

The datasets co...

description: The Washington State Criminal Justice Data Book combines state data from multiple agency sources that can be queried through CrimeStats Online. The Washington Statistical Analysis Center is a clearinghouse for state data on crime and justice topics, brought together from many different agencies and reporting systems. Use our Web-based query tools to target your crime and justice questions and search the databases for answers. Full data sets from each database are downloadable in Excel or SAS for more detailed analysis.; abstract: The Washington State Criminal Justice Data Book combines state data from multiple agency sources that can be queried through CrimeStats Online. The Washington Statistical Analysis Center is a clearinghouse for state data on crime and justice topics, brought together from many different agencies and reporting systems. Use our Web-based query tools to target your crime and justice questions and search the databases for answers. Full data sets from each database are downloadable in Excel or SAS for more detailed analysis.

Nigeria adopted dolutegravir (DTG) as part of first line (1L) antiretroviral therapy (ART) in 2017. However, there is limited documented experience using DTG in sub-Saharan Africa. Our study assessed DTG acceptability from the patient’s perspective as well as treatment outcomes at 3 high-volume facilities in Nigeria. This is a mixed method prospective cohort study with 12 months of follow-up between July 2017 and January 2019. Patients who had intolerance or contraindications to non-nucleoside reverse-transcriptase inhibitors were included. Patient acceptability was assessed through one-on-one interviews at 2, 6, and 12 months following DTG initiation. ART-experienced participants were asked about side effects and regimen preference compared to their previous regimen. Viral load (VL) and CD4+ cell count tests were assessed according to the national schedule. Data were analysed in MS Excel and SAS 9.4. A total of 271 participants were enrolled on the study, the median age of participants was 45 years, 62% were female. 229 (206 ART-experienced, 23 ART-naive) of enrolled participants were interviewed at 12 months. 99.5% of ART-experienced study participants preferred DTG to their previous regimen. 32% of particpants reported at least one side effect. “Increase in appetite” was most frequently reported (15%), followed by insomnia (10%) and bad dreams (10%). Average adherence as measured by drug pick-up was 99% and 3% reported a missed dose in the 3 days preceding their interview. Among participants with VL results (n = 199), 99% were virally suppressed (

Residential greenness, biomarkers of stress and allostatic load, demographic and health characteristics from 300 subjets. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: See above. Format: Data are stored in SAS and MS Excel. This dataset is associated with the following publication: Egorov, A., S. Griffin, R. Converse, J. Styles, E. Sams, A. Wilson, L. Jackson, and T. Wade. Vegetated land cover near residence is associated with reduced allostatic load and improved biomarkers of neuroendocrine, metabolic and immune functions. ENVIRONMENTAL RESEARCH. Academic Press Incorporated, Orlando, FL, USA, 158: 508-21, (2017).