Almazan, E. P. (Speaker). (2017). An introduction to secondary data analysis [Streaming video]. Retrieved from SAGE Research Methods. https:
"Data are commonly understood to be the raw material produced by abstracting the world into categories, measures and other representational forms – numbers, characters, symbols, images, sounds, electromagnetic waves, bits – that constitute the building blocks from which information and knowledge are created. Data are usually representative in nature (e.g., measurements of a phenomena, such as a person's age, height, weight, colour, blood pressure, opinion, habits, location, etc.), but can also be implied (e.g., through an absence rather than presence) or derived (e.g., data that are produced from other data, such as percentage change over time calculated by comparing data from two time periods), and can be either recorded and stored in analogue form or encoded in digital form as bits (binary digits)."
Conceptualising data. (2014). In Kitchin, R. The data revolution: Big data, open data, data infrastructures & their consequences (pp. 1-26). London: SAGE Publications Ltd doi: 10.4135/9781473909472
"A statistic is simply a numerical summary of the sample data. For example, data analysts often use familiar sample statistics such as sample means, sample variances and standard deviation, sample percentiles and medians, and so on to summarize the samples of quantitative data. For samples of categorical data, sample proportions, percentages, and ratios are typical sample statistics that can be utilized to summarize the data. In short, a statistic is simply a summary quantity that is calculated from a sample of data."
Lewis-Beck, M. S., Bryman, A., & Futing Liao, T. (2004). The SAGE encyclopedia of social science research methods Thousand Oaks, CA: Sage Publications, Inc. doi: 10.4135/9781412950589