We present a simple, spreadsheet-based method to determine the statistical significance of the difference between any two arbitrary curves. This modified Chi-squared method addresses two scenarios: A single measurement at each point with known standard deviation, or multiple measurements at each point averaged to produce a mean and standard error. The method includes an essential correction for the deviation from normality in measurements with small sample size, which are typical in biomedical sciences. Statistical significance is determined without regard to the functionality of the curves, or the signs of the differences. Numerical simulations are used to validate the procedure. Example experimental data are used to demonstrate its application. An Excel spreadsheet is provided for performing the calculations for either scenario.

Standard deviation of Particulate Carbon average in smaller than 3µm size class measured via Elemental Analyzer in umol C L-1. Part of dataset Gradients1-KOK1606 On Station Particulate Phosphorus, Particulate Carbon, and Particulate Nitrogen

Graph and download economic data for Standard Error of Loan Rate, Small Domestic Banks (DISCONTINUED) (EEAEXSSNQ) from Q3 2012 to Q2 2017 about standard error, SBA, domestic, loans, banks, depository institutions, rate, and USA.

Standard deviation of Particulate Phosphorus average in smaller than 3µm size class measured via Elemental Analyzer in nmol P L-1. Part of dataset Gradients1-KOK1606 On Station Particulate Phosphorus, Particulate Carbon, and Particulate Nitrogen

The values in the table are the intermediate calculations in the Chi-squared test and the final result. In this case the sum of Chi-squared is 19.8, which at 8 degrees of freedom, is equivalent to a p-value of 0.011.

United States - Standard Error of Loan Rate, Small Domestic Banks (DISCONTINUED) was 0.12% in April of 2017, according to the United States Federal Reserve. Historically, United States - Standard Error of Loan Rate, Small Domestic Banks (DISCONTINUED) reached a record high of 0.33 in January of 2014 and a record low of 0.08 in July of 2013. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Standard Error of Loan Rate, Small Domestic Banks (DISCONTINUED) - last updated from the United States Federal Reserve on June of 2025.

Standard deviation of Particulate Nitrogen average in smaller than 3um size class measured via Elemental Analyzer in umol N L-1. Part of dataset Gradients1-KOK1606 On Station Particulate Phosphorus, Particulate Carbon, and Particulate Nitrogen

This data set contains 0.5 Degree ECMWF Ensemble Small Domain forecast imagery. The forecast products are available at 6 hourly intervals out to 36 hours and 12 hourly intervals from 36 to 144 hours. The products include a variety of ensemble mean, standard deviation, probabilities, and quartiles.

Mean relative activation data [5] are given here for the pair of curves shown in Fig 4B. At each ligand concentration, we measured relative activation in 3 independent experiments. The data in the table are the mean, SD, N and SE for each combination of mutant and ligand concentration.

Techical Information: All reported 143Nd/144Nd ratios have been normalised to the recommended JNdi value of Tanaka et al. (2000). Epsilon Nd values denote the deviation of measured 143Nd/144Nd values from the bulk Earth value (CHUR=0.512638) in parts per 10,000. The external reproducibility (2 SD) is reported based on repeat JNdi analyses of the day. For one sample (13.94-13.95 m), the ion beam was significantly smaller than for standards and hence a propagated error is reported to reflect this difference.

In the near future, the marine environment is likely to be subjected to simultaneous increases in temperature and decreased pH. The potential effects of these changes on intertidal, meiofaunal assemblages were investigated using a mesocosm experiment. Artificial Substrate Units containing meiofauna from the extreme low intertidal zone were exposed for 60 days to eight experimental treatments (four replicates for each treatment) comprising four pH levels: 8.0 (ambient control), 7.7 & 7.3 (predicted changes associated with ocean acidification), and 6.7 (CO2 point-source leakage from geological storage), crossed with two temperatures: 12 °C (ambient control) and 16 °C (predicted). Community structure, measured using major meiofauna taxa was significantly affected by pH and temperature. Copepods and copepodites showed the greatest decline in abundance in response to low pH and elevated temperature. Nematodes increased in abundance in response to low pH and temperature rise, possibly caused by decreased predation and competition for food owing to the declining macrofauna density. Nematode species composition changed significantly between the different treatments, and was affected by both seawater acidification and warming. Estimated nematode species diversity, species evenness, and the maturity index, were substantially lower at 16 °C, whereas trophic diversity was slightly higher at 16 °C except at pH 6.7. This study has demonstrated that the combination of elevated levels of CO2 and ocean warming may have substantial effects on structural and functional characteristics of meiofaunal and nematode communities, and that single stressor experiments are unlikely to encompass the complexity of abiotic and biotic interactions. At the same time, ecological interactions may lead to complex community responses to pH and temperature changes in the interstitial environment.

This dataset was created in order to document self-reported life evaluations among small-scale societies that exist on the fringes of mainstream industrialized socieities. The data were produced as part of the LICCI project, through fieldwork carried out by LICCI partners. The data include individual responses to a life satisfaction question, and household asset values. Data from Gallup World Poll and the World Values Survey are also included, as used for comparison. TABULAR DATA-SPECIFIC INFORMATION --------------------------------- 1. File name: LICCI_individual.csv Number of rows and columns: 2814,7 Variable list: Variable names: User, Site, village Description: identification of investigator and location Variable name: Well.being.general Description: numerical score for life satisfaction question Variable names: HH_Assets_US, HH_Assets_USD_capita Description: estimated value of representative assets in the household of respondent, total and per capita (accounting for number of household inhabitants) 2. File name: LICCI_bySite.csv Number of rows and columns: 19,8 Variable list: Variable names: Site, N Description: site name and number of respondents at the site Variable names: SWB_mean, SWB_SD Description: mean and standard deviation of life satisfaction score Variable names: HHAssets_USD_mean, HHAssets_USD_sd Description: Site mean and standard deviation of household asset value Variable names: PerCapAssets_USD_mean, PerCapAssets_USD_sd Description: Site mean and standard deviation of per capita asset value 3. File name: gallup_WVS_GDP_pk.csv Number of rows and columns: 146,8 Variable list: Variable name: Happiness Score, Whisker-high, Whisker-low Description: from Gallup World Poll as documented in World Happiness Report 2022. Variable name: GDP-PPP2017 Description: Gross Domestic Product per capita for year 2020 at PPP (constant 2017 international $). Accessed May 2022. Variable name: pk Description: Produced capital per capita for year 2018 (in 2018 US$) for available countries, as estimated by the World Bank (accessed February 2022). Variable names: WVS7_mean, WVS7_std Description: Results of Question 49 in the World Values Survey, Wave 7.

Seasonal patterns in the partitioning of phytoplankton carbon during receding sea ice conditions in the eastern Bering Sea water column are presented using rates of 14C net primary productivity (NPP), phototrophic plankton carbon content, and POC export fluxes from shelf and slope waters in the spring (March 30-May 6) and summer (July 3-30) of 2008. At ice-covered and marginal ice zone (MIZ) stations on the inner and middle shelf in spring, NPP averaged 76 ± 93 mmol C/m**2/d, and in ice-free waters on the outer shelf NPP averaged 102 ± 137 mmol C/m**2/d. In summer, rates of NPP were more uniform across the entire shelf and averaged 43 ± 23 mmol C/m**2/d over the entire shelf. A concomitant shift was observed in the phototrophic pico-, nano-, and microplankton community in the chlorophyll maximum, from a diatom dominated system (80 ± 12% autotrophic C) in ice covered and MIZ waters in spring, to a microflagellate dominated system (71 ± 31% autotrophic C) in summer. Sediment trap POC fluxes near the 1% PAR depth in ice-free slope waters increased by 70% from spring to summer, from 10 ± 7 mmol C/m**2/d to 17 ± 5 mmol C/m**2/d, respectively. Over the shelf, under-ice trap fluxes at 20 m were higher, averaging 43 ± 17 mmol C/m**2/d POC export over the shelf and slope estimated from 234Th deficits averaged 11 ± 5 mmol C/m**2/d in spring and 10 ± 2 mmol C/m**2/d in summer. Average e-ratios calculated on a station-by-station basis decreased by ~ 30% from spring to summer, from 0.46 ± 0.48 in ice-covered and MIZ waters, to 0.33 ± 0.26 in summer, though the high uncertainty prevents a statistical differentiation of these data.

Herein, the spatial evolution characteristics of high-level Grade A tourist attractions in the Yangtze River Delta (YRD) urban agglomeration, from 2001 to 2021, are studied by comprehensively applying the nearest neighbor index, kernel density analysis, standard deviation ellipse, and spatial autocorrelation. High-level Grade A tourist attractions are investigated using the random forest model as the driving mechanism of the spatial pattern. Results show that 1) the spatial distribution of high-level Class A tourist attractions in the YRD city cluster has grown to be an agglomeration, and the high-density areas have evolved from “point-like dispersion to regiment-like combination,” gradually forming a B-shaped core density structure. 2) The spatial distribution comprises an overall “northwest–southeast” direction, a small counterclockwise rotation, the distribution of the center of gravity to the southwest migration, and the center of gravity from the territory of Suzhou City to the territory of Huzhou City. 3) The high-level Class A tourist attractions in the YRD city cluster as a whole show a strong positive spatial correlation, and the significantly clustered areas include three types: high-high (H-H), low-low (L-L), and low-high (L-H). 4) The spatial distribution of high, A-level tourist attractions in the YRD city cluster results from the combined action of the natural environment, resource endowment, socioeconomy, and policy background. Each element has a nonlinear and complex influence on the distribution of scenic spots.

Over the period 2007-2011, life expectancy at birth was 78.5 years for the total population in New Mexico, 75.8 years for males, and 81.3 years for females.For comparison, in 2011, life expectancy at birth was 78.7 years for the total U.S. population, 76.3 years for males, and 81.1 years for females. (http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6335a8.htm?s_cid=mm6335a8_e )PLEASE NOTE: The data in this map corrects, updates and replaces life expectancy data included in the 2012 Bernalillo County Place Matters 'Community Health Equity Report'. Compare life expectancy in Europe and the USA - Map ImageNOTE: Changes in life expectancy (Increase, Decrease, No Change) over the periods 1999-2003 to 2007-2011 are tested for statistical significance using a rule of one standard deviation.

Life Expectancy at Birth, Small Areas, by Sex, 1999-2003 and 2007-2011 - LEBSASEX

Summary: Life Expectancy at Birth, Small Areas, by Sex, 1999-2003 and 2007-2011

Prepared by: NEW MEXICO COMMUNITY DATA COLLABORATIVE, http://nmcdc.maps.arcgis.com/home/index.html ; T Scharmen, thomas.scharmen@state.nm.us, 505-897-5700 x126,

Data Sources: New Mexico Death Certificate Database, Office of Vital Records and Statistics, New Mexico Department of Health; Population Estimates: University of New Mexico, Geospatial and Population Studies (GPS) Program, http://bber.unm.edu/bber_research_demPop.html. Retrieved Mon, 21 June 2014 from New Mexico Department of Health, Indicator-Based Information System for Public Health Web site: http://ibis.health.state.nm.us

Shapefile: http://nmcdc.maps.arcgis.com/home/item.html?id=1e97d2715d8640ab9023fa35fc7b2634

Feature: http://nmcdc.maps.arcgis.com/home/item.html?id=3104749c2c094044914abf9ba6953eab

Master File:

NM DATA VARIABLE DEFINITION

999 SANO Small Area Number

NEW MEXICO SANAME Small Area Name

9250534 PB9903 Population at Risk, Both Sexes, 1999-2003

77.7 LEB9903 Life Expectancy at Birth, Both Sexes, 1999-2003

77.7 CILB9903 Lower Confidence Interval for Life Expectancy at Birth, Both Sexes, 1999-2003

77.7 CIUB9903 Upper Confidence Interval for Life Expectancy at Birth, Both Sexes, 1999-2003

10188104 PB0711 Population at Risk, Both Sexes, 2007-2011

78.5 LEB0711 Life Expectancy at Birth, Both Sexes, 2007-2011

78.5 CILB0711 Lower Confidence Interval for Life Expectancy at Birth, Both Sexes, 2007-2011

78.5 CIUB0711 Upper Confidence Interval for Life Expectancy at Birth, Both Sexes, 2007-2011

0.8 LEBDIFF Difference in Life Expectancy, Both Sexes, 2007-2011 MINUS 1999-2003

INCREASE LEBSIG Trend of the Difference in Life Expectancy, Both Sexes, (1 standard deviation = 68.2% confidence interval)

4683013 PF9903 Population at Risk, Females, 1999-2003

80.6 LEF9903 Life Expectancy at Birth, Females, 1999-2003

80.6 CILF9903 Lower Confidence Interval for Life Expectancy at Birth, Females, 1999-2003

80.6 CIUF9903 Upper Confidence Interval for Life Expectancy at Birth, Females, 1999-2003

5155192 PF0711 Population at Risk, Females, 2007-2011

81.3 LEF0711 Life Expectancy at Birth, Females, 2007-2011

81.3 CILF0711 Lower Confidence Interval for Life Expectancy at Birth, Females, 2007-2011

81.3 CIUF0711 Upper Confidence Interval for Life Expectancy at Birth, Females, 2007-2011

0.7 LEFDIFF Difference in Life Expectancy, Females, 2007-2011 MINUS 1999-2003

INCREASE LEFSIG Trend of the Difference in Life Expectancy, Females, (1 standard deviation = 68.2% confidence interval)

4567521 PM9903 Population at Risk, Males, 1999-2003

74.8 LEM9903 Life Expectancy at Birth, Males, 1999-2003

74.8 CILM9903 Lower Confidence Interval for Life Expectancy at Birth, Males, 1999-2003

74.8 CIUM9903 Upper Confidence Interval for Life Expectancy at Birth, Males, 1999-2003

5032911 PM0711 Population at Risk, Males, 2007-2011

75.8 LEM0711 Life Expectancy at Birth, Males, 2007-2011

75.7 CILM0711 Lower Confidence Interval for Life Expectancy at Birth, Males, 2007-2011

75.8 CIUM0711 Upper Confidence Interval for Life Expectancy at Birth, Males, 2007-2011

1 LEMDIFF Difference in Life Expectancy, Males, 2007-2011 MINUS 1999-2003

INCREASE LEMSIG Trend of the Difference in Life Expectancy, Males, (1 standard deviation = 68.2% confidence interval)

1.077540107 FMRT9903 Female to Male Ratio of Life Expectancy, 1999-2003

1.072559367 FMRT0711 Female to Male Ratio of Life Expectancy, 2007-2011

5.8 FMDT9903 Female Life Expectancy MINUS Male Life Expectancy, 1999-2003

5.5 FMDT0711 Female Life Expectancy MINUS Male Life Expectancy, 2007-2011

-0.3 FMDTDIFF Difference in Female Life Expectancy MINUS Male Life Expectancy, over both time periods, in Years

We present new Holocene century to millennial-scale proxies for the well-dated piston core MD99-2269 from Húnaflóadjúp on the North Iceland Shelf. The core is located in 365 mwd and lies close to the fluctuating boundary between Atlantic and Arctic/Polar waters. The proxies are: alkenone-based SST°C, and Mg/Ca SST°C estimates and stable d13C and d18O values on planktonic and benthic foraminifera. The data were converted to 60 yr equi-spaced time-series. Significant trends in the data were extracted using Singular Spectrum Analysis and these accounted for between 50% and 70% of the variance. A comparison between these data with previously published climate proxies from MD99-2269 was carried out on a data set which consisted of 14-variable data set covering the interval 400-9200 cal yr BP at 100 yr time steps. This analysis indicated that the 1st two PC axes accounted for 57% of the variability with high loadings clustering primarily into "nutrient" and "temperature" proxies. Clustering on the 100 yr time-series indicated major changes in environment at ~6350 and ~3450 cal yr BP, which define early, mid- and late Holocene climatic intervals. We argue that a pervasive freshwater cap during the early Holocene resulted in warm SST°s, a stratified water column, and a depleted nutrient supply. The loss of the freshwater layer in the mid-Holocene resulted in high carbonate production, and the late Holocene/neoglacial interval was marked by significantly more variable sea surface conditions.

[ Derived from parent entry - See data hierarchy tab ]

This is the Baltic and North Sea Climatology (BNSC) for the Baltic Sea and the North Sea in the range 47 ° N to 66 ° N and 15 ° W to 30 ° E. It is the follow-up project to the KNSC climatology. The climatology was first made available to the public in March 2018 by ICDC and is published here in a slightly revised version 2. It contains the monthly averages of mean air pressure at sea level, and air temperature, and dew point temperature at 2 meter height. It is available on a 1 ° x 1 ° grid for the period from 1950 to 2015. For the calculation of the mean values, all available quality-controlled data of the DWD (German Meteorological Service) of ship observations and buoy measurements were taken into account during this period. Additional dew point values were calculated from relative humidity and air temperature if available. Climatologies were calculated for the WMO standard periods 1951-1980, 1961-1990, 1971-2000 and 1981-2010 (monthly mean values). As a prerequisite for the calculation of the 30-year-climatology, at least 25 out of 30 (five-sixths) valid monthly means had to be present in the respective grid box. For the long-term climatology from 1950 to 2015, at least four-fifths valid monthly means had to be available. Two methods were used (in combination) to calculate the monthly averages, to account for the small number of measurements per grid box and their uneven spatial and temporal distribution: 1. For parameters with a detectable annual cycle in the data (air temperature, dew point temperature), a 2nd order polynomial was fitted to the data to reduce the variation within a month and reduce the uncertainty of the calculated averages. In addition, for the mean value of air temperature, the daily temperature cycle was removed from the data. In the case of air pressure, which has no annual cycle, in version 2 per month and grid box no data gaps longer than 14 days were allowed for the calculation of a monthly mean and standard deviation. This method differs from KNSC and BNSC version 1, where mean and standard deviation were calculated from 6-day windows means. 2. If the number of observations fell below a certain threshold, which was 20 observations per grid box and month for the air temperature as well as for the dew point temperature, and 500 per box and month for the air pressure, data from the adjacent boxes was used for the calculation. The neighbouring boxes were used in two steps (the nearest 8 boxes, and if the number was still below the threshold, the next sourrounding 16 boxes) to calculate the mean value of the center box. Thus, the spatial resolution of the parameters is reduced at certain points and, instead of 1 ° x 1 °, if neighboring values are taken into account, data from an area of 5 ° x 5 ° can also be considered, which are then averaged into a grid box value. This was especially used for air pressure, where the 24 values of the neighboring boxes were included in the averaging for most grid boxes. The mean value, the number of measurements, the standard deviation and the number of grid boxes used to calculate the mean values are available as parameters in the products. The calculated monthly and annual means were allocated to the centers of the grid boxes: Latitudes: 47.5, 48.5, ... Longitudes: -14.5, -13.5, … In order to remove any existing values over land, a land-sea mask was used, which is also provided in 1 ° x 1 ° resolution. In this version 2 of the BNSC, a slightly different database was used, than for the KNSC, which resulted in small changes (less than 1 K) in the means and standard deviations of the 2-meter air temperature and dew point temperature. The changes in mean sea level pressure values and the associated standard deviations are in the range of a few hPa, compared to the KNSC. The parameter names and units have been adjusted to meet the CF 1.6 standard.

Nearest neighbor index of high-level Grade A tourist attractions in the Yangtze River Delta City Cluster.

ARL values of robust estimators based on CUSUM- charts in uncontaminated environment N(0,1) when ARLO = 500.

Standardized variance of robust estimators in different scenarios.