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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Statistics with SAS
SASÀ propos de ce cours
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Niveau intermédiaire
Approx. 21 heures pour terminer
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Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Anglais, Espagnol
Résultats de carrière des étudiants
50%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 21 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Allemand, Russe, Anglais, Espagnol
Offert par
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.
Programme du cours : ce que vous apprendrez dans ce cours
1 heure pour terminer
Course Overview and Data Setup
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.
1 heure pour terminer
2 vidéos (Total 13 min), 5 lectures
3 heures pour terminer
Introduction and Review of Concepts
In this module you learn about the models required to analyze different types of data and the difference between explanatory vs predictive modeling. Then you review fundamental statistical concepts, such as the sampling distribution of a mean, hypothesis testing, p-values, and confidence intervals. After reviewing these concepts, you apply one-sample and two-sample t tests to data to confirm or reject preconceived hypotheses.
3 heures pour terminer
17 vidéos (Total 41 min), 2 lectures, 9 quiz
4 heures pour terminer
ANOVA and Regression
In this module you learn to use graphical tools that can help determine which predictors are likely or unlikely to be useful. Then you learn to augment these graphical explorations with correlation analyses that describe linear relationships between potential predictors and our response variable. After you determine potential predictors, tools like ANOVA and regression help you assess the quality of the relationship between the response and predictors.
4 heures pour terminer
29 vidéos (Total 70 min), 2 lectures, 14 quiz
2 heures pour terminer
More Complex Linear Models
In this module you expand the one-way ANOVA model to a two-factor analysis of variance and then extend simple linear regression to multiple regression with two predictors. After you understand the concepts of two-way ANOVA and multiple linear regression with two predictors, you'll have the skills to fit and interpret models with many variables.
2 heures pour terminer
13 vidéos (Total 43 min), 1 lecture, 5 quiz
2 heures pour terminer
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.
2 heures pour terminer
11 vidéos (Total 28 min), 3 lectures, 4 quiz
3 heures pour terminer
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.
3 heures pour terminer
18 vidéos (Total 46 min)
2 heures pour terminer
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.
2 heures pour terminer
11 vidéos (Total 27 min), 1 lecture, 4 quiz
Avis
Meilleurs avis pour STATISTICS WITH SAS
par CK18 mars 2021
The theoretical parts on introductory statistical analysis (in shorts tests, anova, regression) are well covered. The technical parts i.e coding applications complement the theoretical parts 100%.
par MS4 sept. 2019
The best course for statistics I've ever seen. I've learned statistics here not in university. Big like to all those people provide this valuable course for us. Thanks a million.
par CA22 mai 2020
A Guided lesson even for a beginner. It gives you a general overview of statistics with great emphasis on SAS programming and statistical interpretations of your analyses.
par SS7 mars 2021
Very useful and well organized course. It is useful in case you are new to modelling but also when you need to revise what you have learned before :)
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