The slope b1 tells us how a change in the input causes changes in the output. The term b0 is the intercept, b1 is the slope of the regression line, x is the input variable, e is the error term, and y is the predicted value of the response variable. In simple terms, linear regression helps to find the relation between two variables and is a type of supervised algorithm.Ī linear regression line has an equation of the form: Predicting a response using one or more input features, that is given a set of input data points (X) and responses (Y), simple linear regression tries to fit a line that passes through the maximum number of points while minimizing the squared distance of the points to the fitted line values. to present supply chain to managers visually. A children's apparel manufacturer used descriptive analytics: a. Linear regression can be used to create a predictive model on apparently random data, showing trends in the dataset, such as in cancer diagnoses or in stock prices. Answer: B Feedback: Linear regression, time series analysis, some data-mining techniques, and simulation, often referred to as risk analysis, all fall under the banner of predictive analytics. Linear regression looks at various data points and aims at fitting a trend line. Linear regression is a kind of statistical analysis that attempts to model the relationship between a scalar response and one or more explanatory variables.
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