"Mastering Statistical Inference for Data-Driven Decisions"
Statistical InferenceStatistical inference is the process of drawing conclusions about a population based on a sample of data. It involves using statistical methods to analyze and interpret data, and making inferences about the population from which the sample was drawn. In the context of A/B testing on the web and in mobile, statistical inference is used to determine whether the differences observed between two groups (e.g. a control group and a treatment group) are statistically significant or simply due to chance. This is important because it allows us to make informed decisions about which version of a website or mobile app to use, based on data-driven evidence. Statistical inference involves several key concepts, including hypothesis testing, confidence intervals, and p-values. These concepts are used to determine the likelihood that the observed differences between two groups are real and not just due to random chance. Overall, statistical inference is a critical tool for making data-driven decisions in A/B testing on the web and in mobile. By using statistical methods to analyze and interpret data, we can make informed decisions about which version of a website or mobile app to use, based on evidence rather than intuition or guesswork. |