Dataset

This dataset was created by Master Sniffer

Released under MIT

Contents

Question Paper Solutions of chapter Descriptive Statistics of Basic Data Science, 3rd Semester , Master of Computer Applications (2 Years)

This dataset was an inspiration to me to analytically find the best value Master's programs in data science given the statistics and rankings of each respective university. I acquired a majority of this data through Forbes. Though this data doesn't entirely go through every university from last year's ranking system, I went through each schools webpages through the top 250 universities to find the best value programs and if they offered a Data Science MS. I hope you use this data to make the best decision for yourself and make a respectable upgrade in your career as a Data Scientist.

NOTE: Some of the metrics are skewed for my usage i.e. I am a citizen in New York State and the cost of public universities in NY will be lesser than if you did not come from New York.

I also set a standard of 3.0 as a minimum GPA to be admitted to programs if a university did not provide a minimum GPA to be admitted.

Attribute Information:

1) School Name: Name of Given University 2) State: US State Abbreviation 3) City: US City University is located in 4) Ranking: 2021 Forbes ranking of University 5) Online: 0 -> in-person program, 1 -> online 6) Total_Tuition_Cost: Cost of Tuition in USD 7) Program_Years_Full_Time: Number of years to finish program 8) Min_Quant_GRE_Score: Quant GRE score needed to be accepted (blank if not found) 9) Min_Undergraduate_GPA: GPA needed to be accepted into program 10) Median_Salary_10yr: 10 year Median salary of former graduates (Not Exclusive to DS Majors) 11) Need_GRE: 0-> Do not need to take GRE, 1-> must take GRE 12) Institution Type: Either 'Private' or 'Public'

Main Source: (2022 Version)

https://www.forbes.com/top-colleges/

Question Paper Solutions of chapter Inferential Statistics of Basic Data Science, 3rd Semester , Master of Computer Applications (2 Years)

Graph and download economic data for All Employees: Professional, Scientific, and Technical Services in Mississippi (SMU28000006054000001A) from 1990 to 2024 about science, MS, professional, services, employment, and USA.

This dataset contains the results of the experiments that I ran for my master thesis. The full code (and more) can be found at https://github.com/dimitris93/msc-thesis

A combination of discrete and daily-aligned groundwater levels for the Mississippi River Valley alluvial aquifer clipped to the Mississippi Alluvial Plain, as defined by Painter and Westerman (2018), with corresponding metadata are based on processing of U.S. Geological Survey National Water Information System (NWIS) (U.S. Geological Survey, 2020) data. The processing was made after retrieval using aggregation and filtering through the infoGW2visGWDB software (Asquith and Seanor, 2019). The nomenclature GWmaster mimics that of the output from infoGW2visGWDB. Two separate data retrievals for NWIS were made. First, the discrete data were retrieved, and second, continuous records from recorder sites with daily-mean or other daily statistics codes were retrieved. Each dataset was separately passed through the infoGW2visGWDB software to create a "GWmaster discrete" and "GWmaster continuous" and these tables were combined and then sorted on the site identifier and date to form the data ...

Graph and download economic data for All Employees: Professional and Business Services: Professional, Scientific, and Technical Services in Jackson, MS (MSA) (SMU28271406054000001) from Jan 2001 to Aug 2025 about Jackson, science, MS, professional, services, employment, and USA.

In the rapidly moving proteomics field, a diverse patchwork of data analysis pipelines and algorithms for data normalization and differential expression analysis is used by the community. We generated a mass spectrometry downstream analysis pipeline (MS-DAP) that integrates both popular and recently developed algorithms for normalization and statistical analyses. Additional algorithms can be easily added in the future as plugins. MS-DAP is open-source and facilitates transparent and reproducible proteome science by generating extensive data visualizations and quality reporting, provided as standardized PDF reports. Second, we performed a systematic evaluation of methods for normalization and statistical analysis on a large variety of data sets, including additional data generated in this study, which revealed key differences. Commonly used approaches for differential testing based on moderated t-statistics were consistently outperformed by more recent statistical models, all integrated in MS-DAP. Third, we introduced a novel normalization algorithm that rescues deficiencies observed in commonly used normalization methods. Finally, we used the MS-DAP platform to reanalyze a recently published large-scale proteomics data set of CSF from AD patients. This revealed increased sensitivity, resulting in additional significant target proteins which improved overlap with results reported in related studies and includes a large set of new potential AD biomarkers in addition to previously reported.

The Pre-1990 HMDA Aggregation Data were prepared annually during this period by the FFIEC on behalf of institutions reporting HMDA data. The Aggregation Data consists of home purchase and home improvement loans that a depository institution originated or purchased during each calendar year. The collected HMDA data were individually aggregated up to the tract level by the reporting depository institution and submitted accordingly to the FFIEC. Individual records are the summary of loan activity for the specified respondent for the indicated census tract except when the census tract numbers were either 888888 or 999999. The 888888 tract records are the sum of all loan activity by the reporter outside of the MSA being reported, but not appearing in any other MSA report. The 999999 tract records are the consolidated county summary data for loans made in untracted counties or counties with 1980 total population less than 30,000. The 1988 and 1989 Aggregation Data files include aggregated data from nondepository institutions, specifically mortgage banking subsidiaries of bank holding companies.

In 2024, it was projected that people in the United States with a Master’s degree in Computer Science would have the highest average starting salary, at 85,403 U.S. dollars. People who held a Master’s degree in Engineering were projected to have the second-highest starting salary, at 83,628 U.S. dollars. An abundance of Masters As higher education in the United States has become more common, and even expected, the number of Master’s degrees awarded has increased. During the 1949-50 academic year, about 58,180 Master’s degrees were awarded to students, with the vast majority being earned by male students. In the 2018-19 academic year, this figure increased to about 833,710 Master’s degrees awarded, with the majority being earned by female students. The right career While Engineering might have the highest starting pay for Master’s degree holders, those with a Master’s degree as a Physician Assistant had the highest mid-career median pay in 2021. Engineering continues to be one of the most popular fields for those seeking their Master’s degree, and STEM fields continue to dominate the field in number of Master’s degrees awarded.

This data collection contains energy commodity production statistics for approximately 200 United Nations reporting countries for the years 1970-1979. In this file, each record refers to an individual reporting country and the quantity of its various transactions (e.g., production, imports, exports, bunkers, additions to stocks, and capacity) for a given energy commodity in a given year. Only annual data are included. The 70 types of commodities reported include solid fuels (e.g., coal, peat, and charcoal), liquid fuels (e.g., crude petroleum, gasoline, and kerosene), gases, uranium, and both industrial and public types of geothermal, hydro, and nuclear generated electricity. Information is also included on the population (in thousands) of the reporting country, the quantity of the commodity per transaction, and the date of the transaction. Supplementary data not contained in this data collection are in the introduction and footnotes of the individual tables published in the YEARBOOK OF WORLD ENERGY STATISTICS, 1979.

This information was complied from the Australian Bureau of Statistics in Partial fullfilment of Coursework for the Master of Data Science taught at UNSW

Household income and wealth Australia, Building Activity Australia, Affordable Housing Database, National and Regional House Price Indices, Population Projections, Lending Indicators

Household income and wealth Australia ->https://www.abs.gov.au/statistics/economy/finance/household-income-and-wealth-australia/latest-release, Affordable Housing Database ->http://www.oecd.org/social/affordable-housing-database.htm, National and Regional House Price Indices ->https://stats.oecd.org/Index.aspx?DataSetCode=RHPI_TARGET, Population Projections ->https://stats.oecd.org/Index.aspx?DataSetCode=POPPROJ, Lending Indicators ->https://www.abs.gov.au/statistics/economy/finance/lending-indicators/apr-2021

Employment income (in 2019 and 2020) by detailed major field of study and highest certificate, diploma or degree, including work activity (full time full year, part time full year, or part year).

Data collection summary statistics, LA-ICP-MS quality control data, and univariate statistics for element:calcium ratios from otolith samples.

Graph and download economic data for All Employees: Professional, Scientific, and Technical Services in Memphis, TN-MS-AR (MSA) (SMU47328206054000001A) from 1990 to 2024 about Memphis, science, MS, AR, professional, TN, services, employment, and USA.

Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions. Results: We present ASTRAL, a fast method for estimating species trees from multiple genes. ASTRAL is statistically consistent, can run on datasets with thousands of genes and has outstanding..., Availability and implementation: ASTRAL is available in open source form at https://github.com/smirarab/ASTRAL/. Datasets studied in this article are available at http://www.cs.utexas.edu/users/phylo/datasets/astral. Contact: Â warnow@illinois.edu Supplementary information: Â Supplementary data are available at Bioinformatics online., , # ASTRAL: genome-scale coalescent-based species tree estimation

This repository includes both simulated and biological dataset.

Description of the data and file structure

The following datasets are used in the ASTRAL paper shown above. All these archive files include README files that describe their content.

biological.zip:

This file includes: 1. our estimated gene trees on alignments provided to us by authors of Song et al, 2012, PNAS, 2. our estimated species trees on the same dataset.

We have re-analyses of two biological datasets in our paper.

Song et al dataset

We obtained gene alignments from the Song et al and re-estimated gene trees and species trees.

The following files are included in mammals.zip

• mammals-alignments.zip contains all the alignments that we obtained from Song et al.

• mammals-genetreess.zip contains gene trees that we estimated. For each gene, we include 3 files

  • RAxML_bipartitions.final.f200 is the bestML tree with support...

Please note: This is a Synthetic data file, also known as a Dummy file - it is not real data. This synthetic file should not be used for purposes other than to develop an test computer programs that are to be submitted by remote access. Each record in the synthetic file matches the format and content parameters of the real Statistics Canada Master File with which it is associated, but the data themselves have been 'made up'. They do NOT represent responses from real individuals and should NOT be used for actual analysis. These data are provided solely for the purpose of testing statistical package 'code' (e.g. SPSS syntax, SAS programs, etc.) in preperation for analysis using the associated Master File in a Research Data Centre, by Remote Job Submission, or by some other means of secure access. If statistical analysis 'code' works with the synthetic data, researchers can have some confidence that the same code will run successfully against the Master File data in the Resource Data Centres. In the fall of 1991, the National Health Information Council recommended that an ongoing national survey of population health be conducted. This recommendation was based on consideration of the economic and fiscal pressures on the health care systems and the requirement for information with which to improve the health status of the population in Canada. Commencing in April 1992, Statistics Canada received funding for development of a National Population Health Survey (NPHS). The NPHS collects information related to the health of the Canadian population and related socio-demographic information to: aid in the development of public policy by providing measures of the level, trend and distribution of the health status of the population, provide data for analytic studies that will assist in understanding the determinants of health, and collect data on the economic, social, demographic, occupational and environmental correlates of health. In addition the NPHS seeks to increase the understanding of the relationship between health status and health care utilization, including alternative as well as traditional services, and also to allow the possibility of linking survey data to routinely collected administrative data such as vital statistics, environmental measures, community variables, and health services utilization. The NPHS collects information related to the health of the Canadian population and related socio-demographic information. It is composed of three components: the Households, the Health Institutions, and the North components. The Household component started in 1994/1995 and is conducted every two years. The first cycle of the NPHS is both longitudinal and cross-sectional. The NPHS longitudinal sample includes 17,276 persons from all ages in 1994/1995 and these same persons will be interviewed every two years. Health Canada, Public Health Agency of Canada and provincial ministries of health use NPHS longitudinal data to plan, implement and evaluate programs and health policies to improve health and the efficiency of health services. Non-profit health organizations and researchers in the academic fields use the information to move research ahead and to improve health.

Version 3.3 is the current version. Older versions have been superseded by Version 3.3.

Product latency/update: The products are currently paused at September 2024 because the IR input dataset from NCEI requires a new calibration scheme to extend past that point. Once NCEI irons out the calibration, we expect to return to quarterly updates.

The Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set of (mainly) satellite-based global products dealing with the Earth's water and energy cycles, under the auspices of the Global Water and Energy Exchange (GEWEX) Data and Assessment Panel (GDAP) of the World Climate Research Program. As the follow on to the GPCP Version 1.3 One Degree Daily product, GPCP Version 3 (GPCP V3.3) seeks to continue the long, homogeneous precipitation record using modern merging techniques and input data sets. The GPCPV3 suite currently consists of the 0.5-degree Monthly and 0.5-degree Daily. Additional products may be added, which consist of (1) 0.5-degree pentad and (2) 0.1-degree 3-hourly. All GPCPV3 products will be internally consistent. Inputs consist of GPM IMERG in the span 55°N-S, and TOVS/AIRS estimates, adjusted climatologically to IMERG, outside 55°N-S. The Daily estimates are scaled to approximately sum to the Monthly value at each 0.5° grid box. In addition to the final precipitation field, probability of liquid phase estimates are provided globally.

This map shows locations that provide ADN (associate degree nursing), AE-MSN (alternate entry master of science in nursing), Diploma, BSN (bachelor of science in nursing), DE-MSN (direct entry master of science in nursing), and LVN (licensed vocation nursing) certifications. The data includes information on pass rates from 2020 through 2024.This map was created with data from Texas Center for Nursing Workforce Studies and last updated in May 2025.