Descriptive statistics, mean ± SD, range, median and interquartile range (IQR).

DH represents 100% for the relative measure. Differences between medians and distributions were significant between all disciplines if indicated with * and were significantly different between GS and SG when marked with 1, significantly different between GS and DH if marked with 2 and significantly different between SG and DH if marked with 3. If no parameter was significantly different the column is empty. Columns marked with—indicate that the measure was not calculated.Median, interquartile range (IQR) and significance level of the difference between discipline medians and distributions for all parameters, and percentage of DH for GS and SG.

The Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Network-Climate Data Record (PERSIANN-CDR) is a satellite-based precipitation dataset for hydrological and climate studies, spanning from 1983 to present. It is the longest satellite-based precipitation record available, with daily data at 0.25° resolution for the 60°S–60°N latitude band.PERSIANN rain rate estimates are generated at 0.25° resolution and calibrated to a monthly merged in-situ and satellite product from the Global Precipitation Climatology Project (GPCP). The model uses Gridded Satellite (GridSat-B1) infrared data at 3-hourly time steps, with the raw output (PERSIANN-B1) bias-corrected and accumulated to produce the daily PERSIANN-CDR.The maps show 31 years (1984–2014) of annual and seasonal median and interquartile range (IQR) data. The median represents the 50th percentile of precipitation, and the IQR reflects the range between the 75th and 25th percentiles, showing data variability. Median and IQR are preferred over mean and standard deviation as they are less influenced by extreme values and better represent non-normally distributed data, such as precipitation, which is skewed and zero-limited.Data and Metadata: NCEIThis is a component of the Gulf Data Atlas (V1.0) for the Physical topic area.

The Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Network-Climate Data Record (PERSIANN-CDR) is a satellite-based precipitation dataset for hydrological and climate studies, spanning from 1983 to present. It is the longest satellite-based precipitation record available, with daily data at 0.25° resolution for the 60°S–60°N latitude band.PERSIANN rain rate estimates are generated at 0.25° resolution and calibrated to a monthly merged in-situ and satellite product from the Global Precipitation Climatology Project (GPCP). The model uses Gridded Satellite (GridSat-B1) infrared data at 3-hourly time steps, with the raw output (PERSIANN-B1) bias-corrected and accumulated to produce the daily PERSIANN-CDR.The maps show 31 years (1984–2014) of annual and seasonal median and interquartile range (IQR) data. The median represents the 50th percentile of precipitation, and the IQR reflects the range between the 75th and 25th percentiles, showing data variability. Median and IQR are preferred over mean and standard deviation as they are less influenced by extreme values and better represent non-normally distributed data, such as precipitation, which is skewed and zero-limited.Data and Metadata: NCEIThis is a component of the Gulf Data Atlas (V1.0) for the Physical topic area.

*Those loading most heavily (component load ≥|0.5|) in principal component analyses are identified in bold.

IQR is proposed for the image-text retrieval task. We use 200,000 queries and the corresponding images as the annotated image-query pairs.

Geoscience Australias GEOMACS model was utilised to produce hindcast hourly time series of continental shelf (~20 to 300 m depth) bed shear stress (unit of measure: Pascal, Pa) on a 0.1 degree grid covering the period March 1997 to February 2008 (inclusive). The hindcast data represents the combined contribution to the bed shear stress by waves, tides, wind and density-driven circulation. Included in the parameters that will be calculated to represent the magnitude of the bulk of the data are the quartiles of the distribution; Q25, Q50 and Q75 (i.e. the values for which 25, 50 and 75 percent of the observations fall below). The interquartile range, , of the GEOMACS output takes the observations from between Q25 and Q75 to provide an accurate representation of the spread of observations. The interquartile range was shown to provide a more robust representation of the observations than the standard deviation, which produced highly skewed observations (Hughes and Harris 2008). This dataset is a contribution to the CERF Marine Biodiversity Hub and is hosted temporarily by CMAR on behalf of Geoscience Australia.

The Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Network-Climate Data Record (PERSIANN-CDR) is a new, retrospective satellite-based precipitation dataset, constructed as a climate data record for hydrological and climate studies. The PERSIANN-CDR is available from 1983-present making the dataset the longest satellite based precipitation data record available. The precipitation maps are available at daily temporal resolution for the latitude band 60°S–60°N at 0.25 degrees. The maps shown here represent 30-year annual and seasonal median and interquartile range (IQR) of the PERSIANN-CDR dataset from 1984 – 2014. In the median precipitation maps, the mid-point value (or 50th percentile) for each pixel in is computed and plotted for the study area. The range of the data about the median is represented by the interquartile range (IQR), and shows the variability of the dataset. For these maps, winter = December – February, spring = March – May, summer = June – August, fall = September – November

United States CSI: Savings: Stock Mkt Invts Current Val Inc: Interquartile Range data was reported at 375,509.000 USD in May 2018. This records an increase from the previous number of 365,952.000 USD for Apr 2018. United States CSI: Savings: Stock Mkt Invts Current Val Inc: Interquartile Range data is updated monthly, averaging 178,711.500 USD from Jan 1990 (Median) to May 2018, with 246 observations. The data reached an all-time high of 467,630.000 USD in Feb 2018 and a record low of 31,384.000 USD in Jan 1990. United States CSI: Savings: Stock Mkt Invts Current Val Inc: Interquartile Range data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H026: Consumer Sentiment Index: Savings & Retirement. Suppose that tomorrow someone were to invest one thousand dollars in a type What do you think is the percent chance that this one thousand dollar investment will increase in value in the year ahead, so that it is worth more than one thousand dollars one year from now?

CSI: Home Values: Next Yr: Interquartile Range data was reported at 5.100 % in May 2018. This records an increase from the previous number of 4.900 % for Apr 2018. CSI: Home Values: Next Yr: Interquartile Range data is updated monthly, averaging 3.500 % from Jan 2007 (Median) to May 2018, with 137 observations. The data reached an all-time high of 5.600 % in Feb 2007 and a record low of 0.700 % in Jan 2012. CSI: Home Values: Next Yr: Interquartile Range data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H036: Consumer Sentiment Index: Home Buying and Selling Conditions. The question was: What do you think will happen to the prices of homes like yours in your community over the next 12 months? Will they increase at a rapid rate, increase at a moderate rate, remain about the same, decrease ata moderate rate, or decrease at a rapid rate? By about what percent do you expect prices of homes like yours in your community to go (up/down), on average, over the next 12 months?

eGFR: estimated glomerular filtration rate, IQR: interquartile range.

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Fluorescence t 1/2 values of FRAP on Swi6‐EGFP heterochromatic loci. The box bounds the interquartile range (IQR) divided by the median, and whiskers extend to a maximum of 1.5 × IQR beyond the box.. List of tagged entities: swi6 (uniprot:P40381), , FRAP

Normalized fluorescence recovery values of FRAP on Swi6‐EGFP heterochromatic loci. The box bounds the interquartile range (IQR) divided by the median, and whiskers extend to a maximum of 1.5 × IQR beyond the box.. List of tagged entities: swi6 (uniprot:P40381), , FRAP

United States CSI: Expected Inflation: Next 5 Yrs: Interquartile Range data was reported at 2.100 % in May 2018. This records a decrease from the previous number of 2.300 % for Apr 2018. United States CSI: Expected Inflation: Next 5 Yrs: Interquartile Range data is updated monthly, averaging 3.100 % from Feb 1979 (Median) to May 2018, with 380 observations. The data reached an all-time high of 8.700 % in Mar 1982 and a record low of 2.000 % in Jan 2018. United States CSI: Expected Inflation: Next 5 Yrs: Interquartile Range data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The questions were: 'What about the outlook for prices over the next 5 to 10 years? Do you think prices will be higher, to go up, on the average, during the next 12 months?' and 'By about what percent per year do you expect prices to go up or down, on the average, during the next 5 to 10 years?'

United States CSI: Expected Inflation: Next Yr: Interquartile Range data was reported at 3.200 % in May 2018. This records a decrease from the previous number of 3.500 % for Apr 2018. United States CSI: Expected Inflation: Next Yr: Interquartile Range data is updated monthly, averaging 3.900 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 10.000 % in Apr 1980 and a record low of 3.000 % in Oct 2017. United States CSI: Expected Inflation: Next Yr: Interquartile Range data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The questions were: 'During the next 12 months, do you think that prices in general will go up, or go down, or stay where they are now?' and 'By what percent do you expect prices to go up, on the average, during the next 12 months?'

*n = 1041 (35 missing data).BMI = body mass index (kg/m2); SD = standard deviation; IQR = interquartile range; EI energy intake (MJ/d); BMR = basal metabolic rate (MJ/d).

C Boxplots showing average gene expression (log10(FPKMs +1) for genes up or down-regulated (adjusted P-value < 0.001, |FC|>2) in R6/1 (N=9) versus WT (N=9) mice (left). The bottom and top of the boxes are the first and third quartiles, and the line within represents the median. The whiskers denote the interval within 1.5 times the interquartile range (IQR) from the median. Heatmap showing expression profile (log10 (FPKMs +1)) of genes up- or down-regulated (adjusted P-value<0.001, |FC|>2, N=9) in R6/1 mice (mid). Genes are ranked by the degree of expression. Numbers in colour scale show the correspondence between gene expression values and colours. Boxplots showing average TSS chromatin accessibility (log10(ATAC reads +1), N=3) for genes up or down-regulated (adjusted P-value < 0.001, |FC|>2, N=9) in R6/1 versus WT mice hippocampus (right). Exact P values are reported in Appendix Table S3. The bottom and top of the boxes are the first and third quartiles, and the line within represents the median. The whiskers denote the interval within 1.5 times the interquartile range (IQR) from the median. D Average gene expression (closed or open regions FPKMs/ unchanged regions FPKMs) for genes associated with differential accessible regions in R6/1 (N=9) versus WT (N=9) mice (adjusted P-value < 0.05, N=3). Each point corresponds to the value from an individual sample. Data is shown as the mean ± S.E.M. *P < 0.05 as compared with WT mice (two-tailed unpaired Student's t test). Exact P values are reported in Appendix Table S3. . List of tagged entities: multiple components, chromatin (go:GO:0000785), , assay for transposase-accessible chromatin using sequencing (obi:OBI_0002039),gene expression assay (bao:BAO_0002785), Huntington's disease (doid:DOID:12858)

Categorical output of IPAQ.

Displays the descriptive statistics, including the minimum, maximum, median and interquartile range (IQR) values, for the variables analyzed.