By the end of this course, learners will be able to apply linear regression techniques, interpret statistical outputs, and implement predictive models using SPSS and Excel. Through a blend of foundational theory and real-world applications, students will gain hands-on experience in analyzing datasets across engineering, energy, and finance.
您将学到什么
Apply linear regression and interpret statistical outputs.
Build predictive models in SPSS and Excel with real datasets.
Use regression in engineering, energy, and financial analysis.
您将获得的技能
要了解的详细信息

添加到您的领英档案
September 2025
10 项作业
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该课程共有3个模块
This module introduces the fundamentals of linear regression modeling using SPSS. Learners will explore the conceptual foundations of regression, understand the importance of statistical significance, and practice visualizing data relationships. By the end of this module, students will be able to construct regression equations, interpret coefficients, and evaluate the strength of predictive models.
涵盖的内容
9个视频4个作业1个插件
This module demonstrates the practical application of regression modeling across engineering and energy datasets. Learners will examine case studies such as copper expansion and energy consumption, applying regression to interpret real-world phenomena. The focus is on extending regression analysis to scientific and applied contexts while validating model consistency with new data.
涵盖的内容
6个视频3个作业
This module focuses on financial applications of regression, particularly in assessing debt, credit risk, and forecasting. Learners will build regression models to evaluate debt-to-income ratios, credit card liabilities, and predictive outcomes using Excel and SPSS. By mastering these skills, students will enhance their ability to make data-driven financial decisions.
涵盖的内容
6个视频3个作业
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