Statistical Inference
Statistical Inference is the process of drawing conclusions about a population based on a sample of data from that population. It involves using probability theory and statistical methods to make inferences about the characteristics of a population, such as its mean, variance, or distribution. Statistical inference can be used to test hypotheses, estimate parameters, and make predictions. There are two main types of statistical inference: estimation and hypothesis testing. Estimation involves using sample data to estimate the value of an unknown population parameter, such as the mean or variance. Hypothesis testing involves using sample data to test a hypothesis about a population parameter, such as whether the mean is equal to a specific value. Statistical inference is a fundamental concept in data science and is used in a wide range of applications, including business, healthcare, and social sciences.
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