Enroll Course: https://www.coursera.org/learn/sas-statistics
Are you looking to enhance your data analysis skills, particularly within the powerful SAS environment? The “Statistics with SAS” course on Coursera is an excellent starting point for anyone who needs to perform statistical analyses using SAS/STAT software. This introductory course is meticulously designed for users who want to get hands-on with essential statistical techniques.
The course kicks off with a thorough “Course Overview and Data Setup,” ensuring you’re comfortable with the platform and the data you’ll be working with. This foundational module is crucial for a smooth learning experience.
Next, the “Introduction and Review of Concepts” module is a gem. It effectively bridges the gap between theoretical statistical concepts and their practical application in SAS. You’ll revisit fundamental ideas like sampling distributions, hypothesis testing, p-values, and confidence intervals. The real strength here lies in applying these concepts to one-sample and two-sample t-tests, allowing you to confirm or reject hypotheses with real data.
The “ANOVA and Regression” module delves into the core of statistical modeling. You’ll learn to leverage graphical tools to identify useful predictors and then use correlation analyses to understand linear relationships. Following this, ANOVA and regression techniques are introduced to assess the quality of these relationships, providing a solid understanding of how to model your data.
Building on this, “More Complex Linear Models” expands your toolkit by introducing two-factor ANOVA and multiple linear regression. This progression equips you to handle more intricate datasets with multiple variables, a common scenario in real-world analysis.
The course doesn’t stop at fitting models; it also covers the critical aspects of “Model Building and Effect Selection.” You’ll explore various tools that help you choose the most appropriate model based on your specific research needs and expertise.
Furthermore, “Model Post-Fitting for Inference” is indispensable for ensuring the reliability of your models. This section teaches you how to verify assumptions, diagnose problems like outliers and influential observations, and understand collinearity, all vital for robust statistical inference.
Transitioning from inference to prediction, “Model Building for Scoring and Prediction” guides you on assessing models for their predictive power and deploying them to forecast new data. This practical application is highly valuable for predictive analytics.
Finally, the “Categorical Data Analysis” module introduces you to analyzing categorical data, including hypothesis tests for associations and building logistic regression models. You’ll learn to characterize relationships and use logistic regression for classification tasks.
Overall, “Statistics with SAS” is a highly recommended course for anyone looking to gain practical proficiency in statistical analysis using SAS. The structured syllabus, combined with hands-on application, makes complex statistical concepts accessible and manageable. Whether you’re a student, a researcher, or a data professional, this course will undoubtedly elevate your SAS and statistical analysis capabilities.
Enroll Course: https://www.coursera.org/learn/sas-statistics