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.
oferecido por
Statistics with SAS
SASInformações sobre o curso
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Resultados de carreira do aprendiz
50%
consegui um benefício significativo de carreira com este curso
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 20 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
Resultados de carreira do aprendiz
50%
consegui um benefício significativo de carreira com este curso
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 20 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
oferecido por
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.
Programa - O que você aprenderá com este curso
1 hora para concluir
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 hora para concluir
2 vídeos (Total 13 mín.), 4 leituras
3 horas para concluir
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 horas para concluir
17 vídeos (Total 41 mín.), 2 leituras, 9 testes
4 horas para concluir
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 horas para concluir
29 vídeos (Total 70 mín.), 2 leituras, 14 testes
2 horas para concluir
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 horas para concluir
13 vídeos (Total 43 mín.), 1 leitura, 5 testes
2 horas para concluir
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 horas para concluir
11 vídeos (Total 28 mín.), 3 leituras, 4 testes
3 horas para concluir
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 horas para concluir
18 vídeos (Total 46 mín.)
2 horas para concluir
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 horas para concluir
11 vídeos (Total 27 mín.), 1 leitura, 4 testes
Avaliações
Principais avaliações do STATISTICS WITH SAS
por CK18 de Mar de 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%.
por MS4 de Set de 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.
por HH12 de Jul de 2021
He knows statistical concepts very well and is able to explain in a clear and concise manner. Better than other top school classes filled up with jargons and group homework.
por CA22 de Mai de 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.
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