Viited

Cairo, A. (2016). The truthful art: data, charts, and maps for communication. New Riders.
Çetinkaya-Rundel, M., & Ellison, V. (2021). A Fresh Look at Introductory Data Science. Journal of Statistics and Data Science Education, 29(sup1), S16–S26. https://doi.org/10.1080/10691898.2020.1804497
Crameri, F., Shephard, G. E., & Heron, P. J. (2020). The misuse of colour in science communication. Nature Communications, 11(1), 5444. https://doi.org/10.1038/s41467-020-19160-7
Kelleher, J. D., & Tierney, B. (2018). Data science. The MIT Press.
Kitchin, R., & McArdle, G. (2016). What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets. Big Data & Society, 3(1), 205395171663113. https://doi.org/10.1177/2053951716631130
Peng, R., & Matsui, E. (2016). The Art of Data Science. Leanpub.
Pinheiro, C., Patetta, M., & Safari, an O. M. C. (2021). Introduction to Statistical and Machine Learning Methods for Data Science. SAS Institute Inc.
Saltz, J. S., & Stanton, J. M. (2017). An introduction to data science. SAGE Publications, Inc.
Sauga, A. (2020). Statistika õpik majanduseriala üliõpilastele (2nd ed.). TTÜ kirjastus.
Spiegelhalter, D. J. (2019). The art of statistics: learning from data. Pelican Books.
Stevens, S. S. (1946). On the Theory of Scales of Measurement. Science, 103(2684), 677–680. https://doi.org/10.1126/science.103.2684.677
Taddy, M. (2019). Business data science: combining machine learning and economics to optimize, automate, and accelerate business decisions (First edition). McGraw-Hill Education.
Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 059(i10). https://ideas.repec.org/a/jss/jstsof/v059i10.html
Wild, C. (2006). The concept of distribution. Statistics Education Research Journal, 5(2), 10–26.
Wu, J. (1997). Statistics = data science? http://www2. isye. gatech. edu/~ jeffwu/presentations/datascience.pdf