distribution of the scaled values. Combining information sources In meteorology, weather datasets are acquired over many years of record and, as part of this, measurements at certain stations may cease occasionally while, at around the same time, measurements may start at nearby locations. There are then questions as to whether, if the records are combined to form a single longer set of records, those records can be considered homogeneous over time. An example of homogeneity testing of wind speed and direction data can be found in Romanić et al., 2015. Homogeneity within populations Simple populations surveys may start from the idea that responses will be homogeneous across the whole of a population. Assessing the homogeneity of the population would involve looking to see whether the responses of certain identifiable subpopulations differ from those of others. For example, car-owners may differ from non-car-owners, or there may be differences between different age-groups. Tests A test for homogeneity, in the sense of exact equivalence of statistical distributions, can be based on an E-statistic. A location test tests the simpler hypothesis that distributions have the same location parameter. See also Consistency (statistics) Reliability (statistics) References Further reading Hall, M.J. (2003) The interpretation of non-homogeneous hydrometeorological time series a case study. Meteorological Applications, 10, 61–67. Krus, D.J., & Blackman, H.S. (1988).Test reliability and homogeneity from perspective of the ordinal test theory. Applied Measurement in Education, 1, 79–88 (Request reprint). Loevinger, J. (1948). The technic of homogeneous tests compared with some aspects of scale analysis and factor analysis. Psychological Bulletin, 45, 507–529. Statistical analysis Meta-analysis