Certificate in Data Regression Analysis Basics
-- ViewingNowThe Certificate in Data Regression Analysis Basics is a comprehensive course designed to empower learners with essential skills in data analysis. This program focuses on regression analysis, a critical technique used to examine the relationship between variables, predict future trends, and make data-driven decisions.
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⢠Introduction to Data Regression Analysis: Defining regression analysis, understanding its importance, and getting familiar with the basic concepts.
⢠Types of Regression Analysis: Simple and multiple linear regression, polynomial regression, logistic regression, and Ridge and Lasso regression.
⢠Data Preparation for Regression Analysis: Data cleaning, missing value imputation, variable scaling, and creating dummy variables.
⢠Assessing Regression Models: Evaluating model assumptions, calculating residuals, and assessing model fit.
⢠Linear Regression Analysis: Creating and interpreting linear regression models, understanding the coefficients, and assessing model significance.
⢠Multiple Linear Regression Analysis: Building and interpreting multiple linear regression models, addressing multicollinearity, and performing variable selection.
⢠Polynomial Regression Analysis: Creating and interpreting polynomial regression models, understanding the role of degree and curvature, and building models with higher-order terms.
⢠Logistic Regression Analysis: Building and interpreting logistic regression models, understanding odds ratios, and distinguishing between binary and multinomial logistic regression.
⢠Regression Diagnostics: Identifying influential observations, outliers, and high-leverage points, and assessing their impact on model performance.
⢠Model Selection and Validation: Comparing models, selecting the best model, and validating its performance through cross-validation, bootstrapping, and hold-out methods.
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