This statistic shows the average price of cellular data per gigabyte in the United States from 2018 to 2023. In 2018, the average price of cellular data was estimated to amount to 4.64 U.S. dollars per GB.

One gigabyte for mobile internet in Nigeria cost on average ** U.S. cents as of August 2023. The country ranked **** in a list of *** countries worldwide, from the cheapest to the most expensive for mobile data. In the regional comparison, Nigeria was among the nations with lower costs for mobile data in Africa. Out of 55 plans analyzed in the country, the lowest price observed was **** U.S. dollars per *** for a ** days plan. In the most expensive plan, *** cost **** U.S. dollars.

One gigabyte of mobile internet in South Africa cost, on average, **** U.S. dollars in 2023. The country ranked *** in *** countries worldwide, from the cheapest to the most expensive for mobile data. Out of 46 plans measured in South Africa, the lowest price observed was *** U.S. dollars per *** for a ** days plan.

North America registered the highest mobile data consumption per connection in 2023, with the average connection consuming ** gigabytes per month. This figure is set to triple by 2030, driven by the adoption of data intensive activities such as 4K streaming.

An .json file that gives the table of contents for the health plan cost of services required under the No Surprise Act - Price Transparency Reporting.

The Cost of Risk metric shows how much the city spends on handling risks (like insurance, legal expenses, or accident payouts) compared to how much money it collects overall.The following historical data was corrected:2022 cost of risk percent was corrected from 1.49 to 1.842023 cost of risk percent was corrected from 1.36 to 1.342024 cost of risk percent was corrected from 1.47 to 1.30 The performance measure dashboard is available at 5.17 Total Cost of Risk. Additional Information Source: Peoplesoft and ACFRContact: Laura CalderContact E-Mail: laura.calder@tempe.govData Source Type: ExcelPreparation Method: The total expenses in Fund 2661 (The Risk Management cost center) is divided by the total revenue from Annual Comprehensive Financial Report to calculate the total cost of Risk.Publish Frequency: AnnualPublish Method: Manual Data Dictionary (pending update)

1. Conservation decision-makers face a trade-off between spending limited funds on direct management action, or gaining new information in an attempt to improve management performance in the future. Value-of-information analysis can help to resolve this trade-off by evaluating how much management performance could improve if new information was gained. Value-of-information analysis has been used extensively in other disciplines, but there are only a few examples where it has informed conservation planning, none of which have used it to evaluate the financial value of gaining new information. 2. We address this gap by applying value-of-information analysis to the management of a declining koala Phascolarctos cinereus population. Decision-makers responsible for managing this population face uncertainty about survival and fecundity rates, and how habitat cover affects mortality threats. The value of gaining new information about these uncertainties was calculated using a deterministic matrix model of the koala population to find the expected population growth rate if koala mortality threats were optimally managed under alternative model hypotheses, which represented the uncertainties faced by koala managers. 3. Gaining new information about survival and fecundity rates and the effect of habitat cover on mortality threats will do little to improve koala management. Across a range of management budgets, no more than 1·7% of the budget should be spent on resolving these uncertainties. 4. The value of information was low because optimal management decisions were not sensitive to the uncertainties we considered. Decisions were instead driven by a substantial difference in the cost efficiency of management actions. The value of information was up to forty times higher when the cost efficiencies of different koala management actions were similar. 5. Synthesis and applications. This study evaluates the ecological and financial benefits of gaining new information to inform a conservation problem. We also theoretically demonstrate that the value of reducing uncertainty is highest when it is not clear which management action is the most cost efficient. This study will help expand the use of value-of-information analyses in conservation by providing a cost efficiency metric by which to evaluate research or monitoring.

Datas of article Shabanov T How much is Russian Food Calorie - preprint 10.13140/RG.2.2.31426.53444

Fossil-based estimates of diversity and evolutionary dynamics mainly rely on the study of morphological variation. Unfortunately, organism remains are often altered by post-mortem taphonomic processes such as weathering or distortion. Such a loss of information often prevents quantitative multivariate description and statistically controlled comparisons of extinct species based on morphometric data. A common way to deal with missing data involves imputation methods that directly fill the missing cases with model estimates. Over the last several years, several empirically determined thresholds for the maximum acceptable proportion of missing values have been proposed in the literature, whereas other studies showed that this limit actually depends on several properties of the study dataset and of the selected imputation method, and is by no way generalizable. We evaluate the relative performances of seven multiple imputation techniques through a simulation-based analysis under three distinct patterns of missing data distribution. Overall, Fully Conditional Specification and Expectation-Maximization algorithms provide the best compromises between imputation accuracy and coverage probability. Multiple imputation (MI) techniques appear remarkably robust to the violation of basic assumptions such as the occurrence of taxonomically or anatomically biased patterns of missing data distribution, making differences in simulation results between the three patterns of missing data distribution much smaller than differences between the individual MI techniques. Based on these results, rather than proposing a new (set of) threshold value(s), we develop an approach combining the use of multiple imputations with procrustean superimposition of principal component analysis results, in order to directly visualize the effect of individual missing data imputation on an ordinated space. We provide an R function for users to implement the proposed procedure.

The Manufacturing Cost Guide is a tool that estimates the costs that US manufacturers face and can be used to help gauge the potential returns on manufacturing industry research projects through cost reductions. These costs are grouped into various standardized categories such as the North American Industry Classification System (NAICS) and the Standard Occupational Classification (SOC) system along with other non-standardized costs. The tool can be used to answer questions such as: -An organization is conducting research to reduce redundant engineering labor. How much do manufacturers spend on engineering? -A researcher is proposing a project to reduce the use of steel by advancing material standards, thereby, reducing scrap caused from material deficiencies. How much do manufacturers spend on steel? -A research organization is proposing to reduce energy consumption from machinery. How much is spent on energy for machine operation? -An organization wants to promote energy efficient lighting in manufacturing facilities. How much do manufacturers spend on lighting?

This paper investigates the relationship between housing prices and the quality of public schools in the Australian Capital Territory. To disentangle the effects of schools and other neighbourhood characteristics on the value of residential properties, we compare sale prices of homes on either side of high school attendance boundaries. We find that a 5 percent increase in test scores (approximately one standard deviation) is associated with a 3.5 percent increase in house prices. Our result is in line with private school tuition costs, and accords with prior research from Britain and the United States. Estimating the effect of school quality on house prices provides a possible measure of the extent to which parents value better educational outcomes.

Comprehensive freight pricing data including LTL rates, FTL costs, regional variations, and industry benchmarks for commercial shipping

Survey of 250 businesses on how much they spend on SEO and their SEO costs

Under the No Surprise Act - Price Transparency Reporting we are providing an .xml file that when downloaded contains the allowed amounts paid to providers outside of the VHP network.

Do people care about future generations? Moral philosophers say we should, but it is unclear whether laypeople agree. In particular, humanity’s inadequate efforts to mitigate climate change could be due to public indifference or heavy discounting of future generations’ well-being. Using surveys and survey experiments in four countries—Sweden, Spain, South Korea, and China—we found that most people say they care about future generations, and would be willing to reduce their standard of living so that people can enjoy better lives in the future. However, not everyone who says they care supports two public actions that could be taken for the benefit of future generations: policies to reduce either global warming or national debt. We find evidence that much of people’s apparent lack of concern for future generations is actually due to distrust of major social institutions, and associated doubts about the effectiveness of future-oriented policies.

The replication file includes the raw data extracted from the NCES NPSAS PowerStats batch processor, CPI inflation data from the Bureau of Labor Statistics, Nominal Personal Consumption Expenditures on Postsecondary Education from the Bureau of Economic Analysis, a Stata do file (replication.do) which uses these datasets to produce the figures in the text, and an archive of those visuals.

Survey of 250 businesses on how much they spend on ecommerce PPC and their ecommerce PPC costs

Comprehensive statistical analysis of Amazon seller monthly revenue, profit margins, and business performance metrics based on survey data from nearly 2,000 sellers across 100+ countries

Survey of 620 businesses on social media advertising pricing

Comprehensive dataset of e-commerce SEO pricing ranges, ROI statistics, traffic growth data, conversion rates, and industry benchmarks compiled from multiple authoritative sources including Google, Semrush, Ahrefs, Moz, WebFX, BrightEdge, and Clutch.