This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.
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이 강좌에 대하여
귀하가 습득할 기술
- Multivariate Time Series Analysis
- Surrogate Model
- Multivariate Analysis
- Predictive Modelling
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SAS
Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.
강의 계획표 - 이 강좌에서 배울 내용
Course Overview (Review from Introduction to Statistics: Hypothesis Testing)
In this module you learn about the course and the data you analyze in this course. Then you set up the data you need to do the practices in the course.
Model Building and Effect Selection
In this module you explore several tools for model selection. These tools help limit the number of candidate models so that you can choose an appropriate model that's based on your expertise and research priorities.
Model Post-Fitting for Inference
In this module you learn to verify the assumptions of the model and diagnose problems that you encounter in linear regression. You learn to examine residuals, identify outliers that are numerically distant from the bulk of the data, and identify influential observations that unduly affect the regression model. Finally, you learn to diagnose collinearity to avoid inflated standard errors and parameter instability in the model.
Model Building for Scoring and Prediction
In this module you learn how to transition from inferential statistics to predictive modeling. Instead of using p-values, you learn about assessing models using honest assessment. After you choose the best performing model, you learn about ways to deploy the model to predict new data.
Categorical Data Analysis
In this module you look for associations between predictors and a binary response using hypothesis tests. Then you build a logistic regression model and learn about how to characterize the relationship between the response and predictors. Finally, you learn how to use logistic regression to build a model, or classifier, to predict unknown cases.
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- 5 stars82.14%
- 4 stars14.28%
- 3 stars3.57%
REGRESSION MODELING FUNDAMENTALS의 최상위 리뷰
Must have taken the prior Course. In the Specialization.
Thanks so much to our instructor, Jordan Bakerman for teaching this course!
Great Study material & Ease of understanding of the concepts.
SAS 비즈니스 통계 분석가 전문 자격증 정보
This program is for those who want to enhance their predictive and statistical modeling skills to drive data-informed business outcomes. If modeling data for business outcomes is relevant in your job role or industry, this certificate is a valuable indication of your proficiency.

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