This excel file will do a statistical tests of whether two ROC curves are different from each other based on the Area Under the Curve. You'll need the coefficient from the presented table in the following article to enter the correct AUC value for the comparison: Hanley JA, McNeil BJ (1983) A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 148:839-843.

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.

In this project, I analysed the employees of an organization located in two distinct countries using Excel. This project covers:

1) How to approach a data analysis project 2) How to systematically clean data 3) Doing EDA with Excel formulas & tables 4) How to use Power Query to combine two datasets 5) Statistical Analysis of data 6) Using formulas like COUNTIFS, SUMIFS, XLOOKUP 7) Making an information finder with your data 8) Male vs. Female Analysis with Pivot tables 9) Calculating Bonuses based on business rules 10) Visual analytics of data with 4 topics 11) Analysing the salary spread (Histograms & Box plots) 12) Relationship between Salary & Rating 13) Staff growth over time - trend analysis 14) Regional Scorecard to compare NZ with India

Including various Excel features such as: 1) Using Tables 2) Working with Power Query 3) Formulas 4) Pivot Tables 5) Conditional formatting 6) Charts 7) Data Validation 8) Keyboard Shortcuts & tricks 9) Dashboard Design

About this dataset

Context

The dataset tabulates the Excel township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Excel township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Excel township was 300, a 0.99% decrease year-by-year from 2022. Previously, in 2022, Excel township population was 303, a decline of 0.98% compared to a population of 306 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Excel township increased by 17. In this period, the peak population was 308 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Excel township is shown in this column.
• Year on Year Change: This column displays the change in Excel township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Excel township Population by Year. You can refer the same here

Historical Dataset of Excel Academy Pcs is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2009-2023),Total Classroom Teachers Trends Over Years (2011-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2011-2023),Hispanic Student Percentage Comparison Over Years (2013-2023),Black Student Percentage Comparison Over Years (2009-2023),Two or More Races Student Percentage Comparison Over Years (2015-2023),Diversity Score Comparison Over Years (2009-2023),Free Lunch Eligibility Comparison Over Years (2011-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2009-2023),Reading and Language Arts Proficiency Comparison Over Years (2012-2018),Math Proficiency Comparison Over Years (2012-2018),Overall School Rank Trends Over Years (2012-2018)

Historical Dataset of Excel Academy - Englewood High School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2014-2020),Total Classroom Teachers Trends Over Years (2015-2023),Student-Teacher Ratio Comparison Over Years (2015-2018),Hispanic Student Percentage Comparison Over Years (2014-2020),Black Student Percentage Comparison Over Years (2014-2020),Two or More Races Student Percentage Comparison Over Years (2014-2015),Diversity Score Comparison Over Years (2014-2020),Free Lunch Eligibility Comparison Over Years (2014-2020),Reading and Language Arts Proficiency Comparison Over Years (2017-2021),Math Proficiency Comparison Over Years (2017-2021),Overall School Rank Trends Over Years (2017-2021),Graduation Rate Comparison Over Years (2017-2018)

Compare state-level estimates from the 2021-2022 National Surveys on Drug Use and Health (NSDUH) using p-values. The tables accompany the2021-2022 NSDUH State Estimates of Substance Use and Mental Disorders, and can be used to determine whether the difference in estimates between two geographic areas are statistically significant. Aguide to their useis also available.The tables are available in an Excel spreadsheet or a zip file containing CSV text files. Each tab or text file contains p-values for a particular measure and a particular age group.

Historical Dataset of Learn Charter Excel Campus is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2019-2023),Total Classroom Teachers Trends Over Years (2022-2023),Distribution of Students By Grade Trends,Hispanic Student Percentage Comparison Over Years (2019-2023),Black Student Percentage Comparison Over Years (2019-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Diversity Score Comparison Over Years (2019-2023),Free Lunch Eligibility Comparison Over Years (2019-2020),Reading and Language Arts Proficiency Comparison Over Years (2017-2022),Math Proficiency Comparison Over Years (2017-2023),Overall School Rank Trends Over Years (2017-2023)

The Excel file contains the model input-out data sets that where used to evaluate the two-layer soil moisture and flux dynamics model. The model is original and was developed by Dr. Hantush by integrating the well-known Richards equation over the root layer and the lower vadose zone. The input-output data are used for: 1) the numerical scheme verification by comparison against HYDRUS model as a benchmark; 2) model validation by comparison against real site data; and 3) for the estimation of model predictive uncertainty and sources of modeling errors. This dataset is associated with the following publication: He, J., M.M. Hantush, L. Kalin, and S. Isik. Two-Layer numerical model of soil moisture dynamics: Model assessment and Bayesian uncertainty estimation. JOURNAL OF HYDROLOGY. Elsevier Science Ltd, New York, NY, USA, 613 part A: 128327, (2022).

About this dataset

Context

The dataset tabulates the Excel population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Excel across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Excel was 539, a 1.46% decrease year-by-year from 2021. Previously, in 2021, Excel population was 547, a decline of 1.08% compared to a population of 553 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Excel decreased by 36. In this period, the peak population was 713 in the year 2010. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Excel is shown in this column.
• Year on Year Change: This column displays the change in Excel population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Excel Population by Year. You can refer the same here

Compare state-level estimates from the 2017-2018 National Surveys on Drug Use and Health (NSDUH) using p-values. The tables accompany the2017-2018 NSDUH State Estimates of Substance Use and Mental Disorders, and can be used to determine whether the difference in estimates between two geographic areas are statistically significant. A guide to their use is also included.The tables are available in an Excel spreadsheet or a zip file containing CSV text files. Each tab or text file contains p-values for a particular measure and a particular age group.

Age-depth models for Pb-210 datasets. The St Croix Watershed Research Station, of the Science Museum of Minnesota, kindly made available 210Pb datasets that have been measured in their lab over the past decades. The datasets come mostly from North American lakes. These datasets were used to produce both chronologies using the 'classical' CRS (Constant Rate of Supply) approach and also using a recently developed Bayesian alternative called 'Plum'. Both approaches were used in order to compare the two approaches. The 210Pb data will also be deposited in the neotomadb.org database. The dataset consists of 3 files; 1. Rcode_Pb210.R R code to process the data files, produce age-depth models and compare them. 2. StCroix_agemodel_output.zip Output of age-model runs of the St Croix datasets 3. StCroix_xlxs_files.zip Excel files of the St Croix Pb-210 datasets

In the beginning, the case was just data for a company that did not indicate any useful information that would help decision-makers. In this case, after collecting a number of revenues and expenses over the months. Needed to know the answers to a number of questions to make important decisions based on intuition-free data. The Questions:- About Rev. & Exp.
- What is the total sales and profit for the whole period? And What Total products sold? And What is Net profit? - In which month was the highest percentage of revenue achieved? And in the same month, what is the largest day have amount of revenue? - In which month was the highest percentage of expenses achieved? And in the same month, what is the largest day have amount of exp.? - What is the extent of the change in expenditures for each month? Percentage change in net profit over the months? About Distribution - What is the number of products sold each month in the largest state? -The top 3 largest states buying products during the two years? Comparison - Between Sales Method by Sales? - Between Men and Women’s Product by Sales? - Between Retailer by Profit?

What I did? - Understanding the data - preprocessing and clean the data - Solve The problems in the cleaning like missing data or false type data - querying the data and make some calculations like "COGS" with power query "Excel". - Modeling and make some measures on the data with power pivot "Excel" - After finishing processing and preparation, I made Some Pivot tables to answers the questions. - Last, I made a dashboard with Power BI to visualize The Results.

About this dataset

Context

The dataset tabulates the Excel township population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of Excel township.

Content

The dataset constitues the following two datasets across these two themes

• Excel Township, Minnesota Population Breakdown by Gender
• Excel Township, Minnesota Population Breakdown by Gender and Age

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/.

Data from www.census.gov.in was downloaded and processed available in this link,

Used the table code :PC11_B07 which contains data regarding working population classified by industrial category, educational level and gender. From these 35 excel tables, data was extracted and transformed into required format using Excel and Power Query detailed here. Transformed it into two datasets of Urban and Rural.

There are two .csv files used here. One is Rural education data district wise and second one is Urban education data district wise.

The open repository consists of two folders; Dataset and Picture. The dataset folder consists file “AWS Dataset Pangandaraan.xlsx”. There are 10 columns with three first columns as time attributes and the other six as atmosphere datasets. Each parameter has 8085 data, and Each parameter has a parameter index at the bottom of the column we added, including mMinimum, mMaximum, and Average values.

For further use, the user can choose one or more parameters for calculating or analyzing. For example, wind data (speed and direction) can be utilized to calculate Waves using the Hindcast method. Furthermore, the user can filter data by using the feature in Excel to extract the exact time range for analyzing various phenomena considered correlated to atmosphere data around Pangandaran, Indonesia.

The second folder, named “Picture,” contains three figures, including the monthly distribution of datasets, temporal data, and wind rose. Furthermore, the user can filter data by using the feature in Excel sheet to extract the exact time range for analyzing various phenomena considered correlated to atmosphere data around Pangandaran, Indonesia

We have uploaded two datasets in excel format. Information Flow: identifies the information flow for each of the papers analyzed on the literature review. Complexity Analysis: Uses the information flows to determine the scaling simulation in terms of computation costs and connectivitiy.

Historical Dataset of Chicago Excel Academy High School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2013-2023),Total Classroom Teachers Trends Over Years (2015-2018),Distribution of Students By Grade Trends,Hispanic Student Percentage Comparison Over Years (2013-2023),Black Student Percentage Comparison Over Years (2013-2023),Two or More Races Student Percentage Comparison Over Years (2019-2023),Diversity Score Comparison Over Years (2013-2023),Free Lunch Eligibility Comparison Over Years (2013-2023),Reading and Language Arts Proficiency Comparison Over Years (2013-2022),Math Proficiency Comparison Over Years (2013-2023),Overall School Rank Trends Over Years (2013-2023),Graduation Rate Comparison Over Years (2013-2023)

Abstract

The dataset was derived by the Bioregional Assessment Programme from HUN_GW_Model_v01l. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

The dataset includes text and excel version of two datafiles pertaining to the groundwater monitoring bores and the surface water gauging stations where the model predicts water levels and baseflow estimates respectively. Also included is an excel file which lists the extraction rates used in the modellling for production bores.

probe_points_plus_extras.xyz GW model output points

no_repeats_with_elevation.txt - points where the groundwater model provides baseflow estimates that are then fed into the river model.

Purpose

Used to generate shapefiles for the two datasets

Dataset History

The dataset was created by exporting text files from the groundwater model after calibration and simulation were complete. Text files were converted to excel spreadsheets.

Dataset Citation

Bioregional Assessment Programme (2016) HUN GW model output points v01. Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/63573849-6e91-45b4-a97c-ad59e48eeb9f.

Dataset Ancestors

• Derived From HUN GW Model Mines raw data v01

• Derived From HUN GW Model v01

• Derived From HUN GW Model code v01

Historical Dataset of Excel Public Charter School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2016-2023),Total Classroom Teachers Trends Over Years (2017-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2017-2023),American Indian Student Percentage Comparison Over Years (2019-2023),Asian Student Percentage Comparison Over Years (2016-2023),Hispanic Student Percentage Comparison Over Years (2016-2023),Black Student Percentage Comparison Over Years (2016-2023),White Student Percentage Comparison Over Years (2016-2023),Native Hawaiian or Pacific Islander Student Percentage Comparison Over Years (2016-2023),Two or More Races Student Percentage Comparison Over Years (2016-2023),Diversity Score Comparison Over Years (2016-2023),Free Lunch Eligibility Comparison Over Years (2017-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2019-2023),Reading and Language Arts Proficiency Comparison Over Years (2017-2019),Math Proficiency Comparison Over Years (2017-2019),Overall School Rank Trends Over Years (2017-2021)