SAS programming concepts(Base+Advanced)
- 3.4
-
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2.5 hours on-demand video
$
12.99
Brief Introduction
Learn about SAS Base and Advanced programming concepts using real world examples.Description
- This course will prepare you for SAS certifications.It will be a great start to enhance your career as SAS programmer.
- Additional documents for better understanding and learning
- Real world working experience to the students
- Creation of SAS Arrays and SAS Macros
- Working with Temporary and Permanent library in SAS
- PROC and SET statements
- Basic terms and measures used in Statistics such as mean, median, mode, skewness, kurtosis, standard deviation and variance.
- Use of statistical procedures to analyses statistical data
- Descriptive statistics: Proc Means(Summary) with and without options, VAR and CLASS, PROC FREQ , PROC UNIVARIATE using data sets. All data sets are attached with the respective courses.
- Proc Correlation (Pearson moment correlation coefficient)
- Proc ANOVA (Example provided using p value to accept the null and alternate hypothesis)
- Explains hypothesis testing used in SAS using Proc t-test, predictive analytics such as linear regression, logistic regression.
- Clustering method in SAS using K-means method on an insurance dataset using Proc Fastclus Procedure. Attached Data set.
- Creation of ARIMA model for forecasting the sales data by using the Box Inkins approach.
- 2 Assignments for practice
- 2 Quizzes to test the understanding of the students
- Introduction to Big Data
Requirements
- Requirements
- Good internet connection and curiosity to learn
Knowledge
- Real world working experience using SAS
- Creation of SAS Arrays and SAS Macros
- Working knowledge of PROC and SET statements
- Working with Temporary and Permanent library in SAS
- Basic terms and measures used in Statistics such as mean, median, mode, skewness, kurtosis, standard deviation and variance
- Use of statistical procedures to analyses statistical data
- Descriptive statistics: Proc Means(Summary) with and without options, VAR and CLASS, PROC FREQ , PROC UNIVARIATE using data sets. All data sets are attached with the respective courses
- Proc Correlation (Pearson moment correlation coefficient)
- Proc ANOVA (Example provided using p value to accept the null and alternate hypothesis)
- Explains hypothesis testing used in SAS using Proc t-test, predictive analytics such as linear regression, logistic regression
- Clustering method in SAS using K-means method on an insurance dataset using Proc Fastclus Procedure. Attached Data set
- Creation of ARIMA model for forecasting the sales data by using the Box Inkins approach
- Learn about the concepts of Big Data,Hadoop and how it addresses the Big data challenges and Hadoop ecosystem
Ankita khanna
3.4 Raiting
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