This statistic depicts the distribution of tools used to compile data and present analytics and/or reports to management, according to a marketing survey of C-level executives, conducted in December 2015 by Black Ink. As of December 2015, 9 percent of respondents used statistical modeling tools, such as IBM's SPSS or the SAS Institute's Statistical Analysis System package, to compile and present their reports.

The Sales Presentation Tool market has evolved into a crucial component of the sales process, enabling businesses to convey their value propositions effectively and engage potential customers. These tools facilitate seamless presentations by providing dynamic features such as slides, templates, and interactive eleme

Most studies in the life sciences and other disciplines involve generating and analyzing numerical data of some type as the foundation for scientific findings. Working with numerical data involves multiple challenges. These include reproducible data acquisition, appropriate data storage, computationally correct data analysis, appropriate reporting and presentation of the results, and suitable data interpretation.Finding and correcting mistakes when analyzing and interpreting data can be frustrating and time-consuming. Presenting or publishing incorrect results is embarrassing but not uncommon. Particular sources of errors are inappropriate use of statistical methods and incorrect interpretation of data by software. To detect mistakes as early as possible, one should frequently check intermediate and final results for plausibility. Clearly documenting how quantities and results were obtained facilitates correcting mistakes. Properly understanding data is indispensable for reaching well-founded conclusions from experimental results. Units are needed to make sense of numbers, and uncertainty should be estimated to know how meaningful results are. Descriptive statistics and significance testing are useful tools for interpreting numerical results if applied correctly. However, blindly trusting in computed numbers can also be misleading, so it is worth thinking about how data should be summarized quantitatively to properly answer the question at hand. Finally, a suitable form of presentation is needed so that the data can properly support the interpretation and findings. By additionally sharing the relevant data, others can access, understand, and ultimately make use of the results.These quick tips are intended to provide guidelines for correctly interpreting, efficiently analyzing, and presenting numerical data in a useful way.

This guidance note sets out the recommended standard presentation of statistics for health areas within the countries and regions of the UK. (File Size 125 KB)

Social Scientists rarely take full advantage of the information available in their statistical results. As a consequence, they miss opportunities to present quantities that are of greatest substantive interest for their research and express the appropriate degree of certainty about these quantities. In this article, we offer an approach, built on the technique of statistical simulation, to extract the currently overlooked information from any statistical method and to interpret and present it in a reader-friendly manner. Using this technique requires some expertise, which we try to provide herein, but its application should make the results of quantitative articles more informative and transparent. To illustrate our recommendations, we replicate the results of several published works, showing in each case how the authors' own concl usions can be expressed more sharply and informatively, and, without changing any data or statistical assumptions, how our approach reveals important new information about the research questions at hand. We also offer very easy-to-use Clarify software that implements our suggestions. See also: Unifying Statistical Analysis

This statistic presents the preferred types of product presentation according to online shoppers in the United States as of April 2017. During the survey period, 70.3 percent of respondents found customer ratings an appealing way of presenting a product to them.

This statistic shows the average number of physical and digital informational presentations to groups at academic libraries in the United States in 2015, by type of degree granted by institution. In 2015, academic libraries at post-secondary education institutions in the U.S. that granted doctoral degrees made 401 physical informational presentations on average.

Scientific investigation is of value only insofar as relevant results are obtained and communicated, a task that requires organizing, evaluating, analysing and unambiguously communicating the significance of data. In this context, working with ecological data, reflecting the complexities and interactions of the natural world, can be a challenge. Recent innovations for statistical analysis of multifaceted interrelated data make obtaining more accurate and meaningful results possible, but key decisions of the analyses to use, and which components to present in a scientific paper or report, may be overwhelming. We offer a 10-step protocol to streamline analysis of data that will enhance understanding of the data, the statistical models and the results, and optimize communication with the reader with respect to both the procedure and the outcomes. The protocol takes the investigator from study design and organization of data (formulating relevant questions, visualizing data collection, data...

This statistic presents information on the truthfulness of online adult dating users in the United States when they present themselves on their adult dating profile. During an April 2017 survey, it was found that 50 percent of responding adult dating website or app users always presented themselves truthfully.

Financial overview and grant giving statistics of Presentation Learning Center

The overall goal of the project was to establish an innovative information system, which can automatically detect and extract content related to side effect of drugs from user reviews, determine whether they are talking about effectiveness or adverse drug events, extract keywords or phrases related to effectiveness or adverse drug events, and visualize the resulting information to doctors and patients. Our group was provided with crawled Twitter reviews and social network forum reviews on drugs that are used to treat diabetes. The raw data were manually labeled in four different label for named entity recognition in order to create training, testing, and validation sets. Using the training data set, a side effect dictionary was created using PamTAT. Side effect dictionary was then refined by removing neutral words to increase accuracy. To validate the accuracy of the generated side effect dictionary, the results of side effect analysis based on the generated dictionary and two other general negative word dictionaries were compared. The generated side effect dictionary performed better in recognizing side effect entities. After validation, the generated dictionary was further tested with a set of user reviews on a drug that is used to treat stroke. Using generated dictionary, the project accomplished to accurately determine if any reviews relates to the mention of side effect of specific drugs. The project successfully delivered to accurately detect mention of side effect from the reviews in > 90% accuracy. Resulting algorithm can be used to create innovative information system to detect and extract content related to side effect of drugs for any other drugs with creation of problem specific dictionary. The project should be further developed to incorporate automatic extraction of user reviews, analysis of data, and visualization of results. DrugEventsSocialMediaReport.docx - Presentation file in docx format DrugEventsSocialMediaReport.pdf - Presentation file in pdf format DrugEventsSocialMediaPresentation.pptx - Presentation file in pptx format DrugEventsSocialMediaPresentation.pdf - Presentation file in pdf format PamTaT4VTWorks - CSV and XML files to use PamTAT

A paper outlining how the gender pay gap will be presented in future ONS Statistical Bulletins

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: Presentation of the Gender Pay Gap: ONS Position Paper

This guidance note sets out the recommended standard presentation of statistics for travel to work areas in the UK. (File Size - 343 KB)

Financial overview and grant giving statistics of Sisters Of The Presentation Of Mary Inc

This document sets out the recommended standard presentation of statistics for administrative areas at regional and sub-regional levels in the UK. This version of the guidance is now available in accessible format. (File Size - 142 KB)

About this dataset

Context

The dataset tabulates the population of Rutherford College by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Rutherford College across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.26% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Rutherford College is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Rutherford College total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rutherford College Population by Race & Ethnicity. You can refer the same here

This presentation describes what aggregate data are. This is followed by a computing exercise that demonstrates how to aggregate data with SPSS. (Note: Data associated with this presentation is available on the DLI FTP site under folder 1873-217.)

Financial overview and grant giving statistics of Presentation Parish Conference Society Of St Vincent De Paul

This guidance note sets out the recommended standard presentation of statistics for electoral areas at regional level in the UK. (File Size - 338 KB)

Original excel files of tabular data that have been used to generate the visual presentation using graphs and charts of the techniques for the current research trends within 6 years (from years 2013 to 2018).