Vendor Master Data Cleaning – a Project for Accounting Class

2021 ◽  
Author(s):  
Sonia Gantman ◽  
Lorrie Metzger
Keyword(s):  
United States ◽  
Problem Solving ◽  
Data Analytics ◽  
Data Cleaning ◽  
The United States ◽  
Public University ◽  
Data Set ◽  
Initial Analysis ◽  
Master Data

We present a data cleaning project that utilizes real vendor master data of a large public university in the United States. Our main objective when developing this case was to identify the areas where students need guidance in order to apply a problem solving approach to the project. This includes initial analysis of the data and the task at hand, planning for cleaning and testing activities, executing this plan, and communicating the results in a written report. We provide a data set with 29K records of vendor master data, and a subset of the same data with 800 records. The assignment has two parts - the planning and the actual cleaning, each with its own deliverable. It can be used in many different courses and completed with almost any data analytics software. We provide suggested solutions and detailed solution notes for Excel and for Alteryx Designer.

scholarly journals Altitude and risk of sudden unexpected infant death in the United States

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Richard Johnston ◽  
Xiaohan Yan ◽  
Tatiana M. Anderson ◽  
Edwin A. Mitchell
Keyword(s):  
United States ◽  
Logistic Regression ◽  
Infant Death ◽  
The United States ◽  
Sudden Infant ◽  
Data Set ◽  
Live Births ◽  
Sudden Unexpected Infant Death ◽  
Increased Risk ◽  
Unexpected Infant Death

AbstractThe effect of altitude on the risk of sudden infant death syndrome (SIDS) has been reported previously, but with conflicting findings. We aimed to examine whether the risk of sudden unexpected infant death (SUID) varies with altitude in the United States. Data from the Centers for Disease Control and Prevention (CDC)’s Cohort Linked Birth/Infant Death Data Set for births between 2005 and 2010 were examined. County of birth was used to estimate altitude. Logistic regression and Generalized Additive Model (GAM) were used, adjusting for year, mother’s race, Hispanic origin, marital status, age, education and smoking, father’s age and race, number of prenatal visits, plurality, live birth order, and infant’s sex, birthweight and gestation. There were 25,305,778 live births over the 6-year study period. The total number of deaths from SUID in this period were 23,673 (rate = 0.94/1000 live births). In the logistic regression model there was a small, but statistically significant, increased risk of SUID associated with birth at > 8000 feet compared with < 6000 feet (aOR = 1.93; 95% CI 1.00–3.71). The GAM showed a similar increased risk over 8000 feet, but this was not statistically significant. Only 9245 (0.037%) of mothers gave birth at > 8000 feet during the study period and 10 deaths (0.042%) were attributed to SUID. The number of SUID deaths at this altitude in the United States is very small (10 deaths in 6 years).

scholarly journals Development of a semi-parametric PAR (Photosynthetically Active Radiation) partitioning model for the United States, version 1.0

2014 ◽  
Vol 7 (5) ◽  
pp. 2477-2484 ◽  
Author(s):  
J. C. Kathilankal ◽  
T. L. O'Halloran ◽  
A. Schmidt ◽  
C. V. Hanson ◽  
B. E. Law
Keyword(s):  
United States ◽  
Elevation Angle ◽  
Model Performance ◽  
Diffuse Radiation ◽  
The United States ◽  
Polynomial Model ◽  
Coefficient Of Determination ◽  
Data Set ◽  
Cubic Polynomial ◽  
Solar Elevation Angle

Abstract. A semi-parametric PAR diffuse radiation model was developed using commonly measured climatic variables from 108 site-years of data from 17 AmeriFlux sites. The model has a logistic form and improves upon previous efforts using a larger data set and physically viable climate variables as predictors, including relative humidity, clearness index, surface albedo and solar elevation angle. Model performance was evaluated by comparison with a simple cubic polynomial model developed for the PAR spectral range. The logistic model outperformed the polynomial model with an improved coefficient of determination and slope relative to measured data (logistic: R2 = 0.76; slope = 0.76; cubic: R2 = 0.73; slope = 0.72), making this the most robust PAR-partitioning model for the United States currently available.

Racial Sentiment and Public Support for Arming Teachers with Guns in the United States

2021 ◽  
pp. 215336872110389
Author(s):  
Andrew J. Baranauskas
Keyword(s):  
United States ◽  
African Americans ◽  
Minority Groups ◽  
Public Support ◽  
The United States ◽  
Data Set ◽  
Racial Issue ◽  
Racial Resentment ◽  
Nationally Representative ◽  
Negative Feelings

In the effort to prevent school shootings in the United States, policies that aim to arm teachers with guns have received considerable attention. Recent research on public support for these policies finds that African Americans are substantially less likely to support them, indicating that support for arming teachers is a racial issue. Given the racialized nature of support for punitive crime policies in the United States, it is possible that racial sentiment shapes support for arming teachers as well. This study aims to determine the association between two types of racial sentiment—explicit negative feelings toward racial/ethnic minority groups and racial resentment—and support for arming teachers using a nationally representative data set. While explicit negative feelings toward African Americans and Hispanics are not associated with support for arming teachers, those with racial resentments are significantly more likely to support arming teachers. Racial resentment also weakens the effect of other variables found to be associated with support for arming teachers, including conservative ideology and economic pessimism. Implications for policy and research are discussed.

Septic shock and systemic inflammatory response syndrome patients' CD15+ granulocytes were subjected to global transcriptional profiling (SIRS)

2021 ◽  
Author(s):  
Marni Mack ◽  
Argo Easston
Keyword(s):  
Gene Expression ◽  
United States ◽  
Septic Shock ◽  
Immune Cells ◽  
Transcriptional Profiling ◽  
The United States ◽  
Transcriptional Level ◽  
Data Set ◽  
Transcriptional Alterations ◽  
Level I

In the United States, sepsis, the body's response to infection in a typically sterile circulation, is a leading causeof death (1). To assess the primary transcriptional alterations associated with each illness state, I utilized amicroarray data set from a cohort of thirtyone individuals with septic shock or systemic inflammatory responsesyndrome (2). At the transcriptional level, I discovered that the granulocytes of patients with SIRS weresimilar to those of patients with septic shock. SIRS showed a “intermediate” gene expression state betweenthat of control patients and that of septic shock patients for numerous genes expressed in the granulocyte. Thediscovery of the most differentially expressed genes in the granulocytic immune cells of patients with septicshock might aid the development of new therapies or diagnostics for an illness with a 14.7 percent to 29.9% inhospitaldeath rate despite decades of study (1).

scholarly journals Reliability and validity of an instrument that measures the willingness to emigrate

Psychologia ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 41-46
Author(s):  
Celia Yaneth Quiroz Campas ◽  
Eyder Bolivar Mojica ◽  
Margarita Juárez Nájera ◽  
Jorge Hernández Valdés ◽  
Cruz García Lirios
Keyword(s):  
United States ◽  
Construct Validity ◽  
United States Of America ◽  
Vocational Training ◽  
Strategic Alliance ◽  
Reliability And Validity ◽  
The United States ◽  
Public University ◽  
Selection Of

Provisions for migration underlie asymmetric relations between sending and receiving countries, such as the cases of Mexico and the United States of America, although studies focus on stigma. The objective of this study was to establish the reliability and construct validity of an instrument that measures the phenomenon. A transversal and exploratory work was carried out with a selection of 300 students, considering their affiliation to a public university in a strategic alliance with multinationals for vocational training. A structure of four factors related to risk, utility, hyperopia and identity was observed, although the design of the research limited the results to the research scenario, suggesting the extension of the work towards negative dispositions such as exclusion, discrimination and the stigma. Keywords: Migration, Identity, Hyperopia, Helplessness, Reliability.

Profiles in workplace giving: a cluster analysis of ‘types’ of givers within a public university

2022 ◽  
Author(s):  
Jorge Ruiz-Menjivar ◽  
Tracy Johns ◽  
Tara Counts ◽  
Yong Liu ◽  
Jennifer Amanda Jones
Keyword(s):  
United States ◽  
Cluster Analysis ◽  
The United States ◽  
Ordinary Least Squares ◽  
Public University ◽  
Strategic Marketing ◽  
Public Employees ◽  
Least Squares Regression ◽  
Job Classification ◽  
Employment Duration

This study examines public employees’ donations to a workplace giving campaign at a large public university in the south-east of the United States. First, we employed logistic regression to predict the likelihood of donating through workplace giving programmes using a sample of employees at a large public university (N = 11,726). Second, we estimated an ordinary least squares regression to identify the significant predictors of donation value with a subsample of employee donors (n=1,832). Third, we developed donor profiles (for example, clusters) of employee benefactors using K-medoids clustering. Factors such as sex, age, education and salary were significant predictors of both being a donor and the donation amount. Additionally, employment duration was significantly related to being a donor and the donation amount, while job classification only predicted being a donor. Employee donors fell into five distinct clusters. These findings contribute to our knowledge of workplace giving campaigns and can be used to develop strategic marketing campaigns.

Legislative Accomplishment and Policy Issue Substance

2013 ◽  
Author(s):  
John S. Lapinski
Keyword(s):  
United States ◽  
Substance P ◽  
Political Behavior ◽  
Policy Issue ◽  
The United States ◽  
Legislative Behavior ◽  
Aggregate Level ◽  
Data Set ◽  
Proper Understanding ◽  
Specific Policy

This chapter introduces a new measure of legislative accomplishment. To understand lawmaking requires that one move beyond studying political behavior in Congress alone and beyond a complete empirical reliance on roll call votes. Moreover, legislative behavior and legislative outputs must be studied in tandem to gain a proper understanding of the lawmaking process in the United States. Although the idea of studying important lawmaking across time is not controversial, constructing an appropriate measure is not a trivial exercise. The chapter constructs a comprehensive lawmaking data set that provides measures of legislative accomplishment at the aggregate level as well as by specific policy issue areas for a 118-year period. It also explains the construction of Congress-by-Congress measures of legislative accomplishment, including measures broken down by the policy-coding schema.

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