Crash Course : SAS Programming from Scratch with workout
Crash Course : SAS Programming from Scratch with workout, available at $19.99, has an average rating of 4.2, with 66 lectures, 2 quizzes, based on 173 reviews, and has 941 subscribers.
You will learn about Create their SAS program comfortably Import, sort, merging, append, derived variable creation etc Conduct analysis on categorical data as well as numeric data Create basic Bar chart, Pie Chart, Stacked Bar Chart etc. Create pivot table kind of report Conduct regression, chi square, ANOVA analysis This course is ideal for individuals who are People trying to learn SAS or People trying to become comfortable in SAS It is particularly useful for People trying to learn SAS or People trying to become comfortable in SAS.
Enroll now: Crash Course : SAS Programming from Scratch with workout
Summary
Title: Crash Course : SAS Programming from Scratch with workout
Price: $19.99
Average Rating: 4.2
Number of Lectures: 66
Number of Quizzes: 2
Number of Published Lectures: 66
Number of Published Quizzes: 2
Number of Curriculum Items: 68
Number of Published Curriculum Objects: 68
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Create their SAS program comfortably
- Import, sort, merging, append, derived variable creation etc
- Conduct analysis on categorical data as well as numeric data
- Create basic Bar chart, Pie Chart, Stacked Bar Chart etc.
- Create pivot table kind of report
- Conduct regression, chi square, ANOVA analysis
Who Should Attend
- People trying to learn SAS
- People trying to become comfortable in SAS
Target Audiences
- People trying to learn SAS
- People trying to become comfortable in SAS
Learn SAS programming from industrial usage perspective. SAS is one of the most used tool for data science, analytics and statistical analysis domain. This course is designed to give you good start on SAS programming quickly. The course has following highlights
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Getting free access to SAS
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Importing data
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Getting basic feel of data- through contents, print, freq, univariate
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Data operations like merge, append, sort, truncate – rows / columns wise,
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derive new fields,
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analysis for each class
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Graphs – vertical bar chart / pie charts / stacked charts
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Statistical procedure
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Title and labels for enhancements
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Tabulate for pivot table kind of work
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Putting together analysis with ODS HTML and colorful title
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proc transpose to transpose the data
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proc compare to compare datasets
The course content in detail is as follows
Section 1 – Getting access to SAS and understand SAS environment
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Getting free access to learn SAS
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Get familiar with SAS environment
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Understand what is
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Program editor
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Log window
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Output window
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Library etc.
Section 2 – Most used data operations in SAS
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Get familiar with the Data for workout
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Import data in SAS
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Viewing Meta Data
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Viewing Data
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Understand various options to print
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Few records starting from a particular observation
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Few columns / all columns
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Direct data entry in SAS
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How to be careful for character format
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Frequency Distribution for categorical variables
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Understand Various parts of the output
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Default and quantity based sorting order
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Storing proc freq output into a SAS dataset
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Why one should avoid proc freq for numeric variable
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Numeric Variable Analysis
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Understand Proc Univariate and Proc Means
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Advantages of both the approaches
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Requesting few statistics only in the output
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Sorting Data
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Understand -How to sort on the basis of one variable / two variables
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How to keep original data as it is and store sorted data in a new dataset
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How to sort data in descending order
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How to remove duplicates
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What is first. and last. option and how to use it
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Merging n Dealing with missing data
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Understand What is merging data
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What are the Pre requisites of merging data
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What is left join, right join and equi join
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How to do various kinds of join
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How is missing value represented for numeric and character variable
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Syntax for replacing missing value for a numeric variable
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Syntax for replacing missing value for a character variable
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Appending datasets
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Understand What is appending datasets?
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How to append data?
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What happens when datsets have different columns and still you want to append it?
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Derive New field
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Write if else logic to create a derived field
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Learn to use OR operator
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Understand how to define length for proper display of variable
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Arithmetic Logical n comparison Operators
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Get to know the different Arithmetic, Logical and Comparison operators we have
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Demo of how to use them for the whole data set
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Also see how to keep only those records, which meets certain criteria
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Truncating data rows n columns wise
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Learn how to keep or drop few fields from a given dataset
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Learn to keep or delete few records meeting certain criteria
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Part of string using Substr
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Understand the syntax for substring
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See the workout example
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in operator
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Understand the usage of in operator
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See the demo to understand how does it make it easy to compare multiple string in one go
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CrossTab using SAS
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Understand How to create cross tab in SAS?
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How to interpret the output
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How to supress some statistics from the result?
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Numeric Variable Analysis for each class
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Understand how to conduct analysis for each distinct value of a particular categorical variable easily using class statement
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Dealing with dates
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Understand date 9 format
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The usage of mdy function to create date
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Find days / years spend between two dates
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Use round function to get nicely formatted value
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Proc SQL n Fetching data from database
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Understand the utility of Proc SQL
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Understand the process of getting data from databases using proc SQL
Section 3 – Statistical procedures and report enhancements
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Conducting linear regression analysis using SAS
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Understand how to conduct linear regression analysis using SAS
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How to get the regression equation, coefficient of determination etc.
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How to interpret coefficient of determination
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How to make out, it is a positive or negative relationship
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Conducting Chi square analysis using SAS
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Understand how to get chi square statistics for contingency table
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How to make sense of degree of freedom, chi square statistics, p value etc.
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Conducting one way ANOVA analysis using SAS
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Learn the syntax of ANOVA analysis using SAS
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Learn to interpret the box plot appearing with ANOVA analysis
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Learn to make sense of p value of ANOVA
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Graphs in SAS
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Learn to
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Create vertical bar chart
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Create horizontal bar chart
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How to get just the percentage or freq, percent all
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How to create stacked bar chart (where bars of numeric variable can show distribution of a categorical variable)
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How to create a pie chart
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Difference between proc gchart and proc chart
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How to create chart of a numeric variable for each class separately
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Title and Label
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How to put specific title above the print / graph output etc.
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How does title 1 and title 2 differ
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What is label
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What is the use of these title and label statement
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Proc tabulate – pivot table in SAS
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Understand the syntax of proc tabulate
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See proc tabulate and Excel pivot table side by side
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ODS HTML to package the output and rich text title (bold, colorful)
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Proc transpose to transpose the data
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Proc compare to compare datasets
Section 4 – Practice Case Studies – apply your knowledge to solve business problems
Course Curriculum
Chapter 1: Introduction to the course and getting ready to work on SAS
Lecture 1: Introduction to the course content
Lecture 2: Getting free access to SAS
Lecture 3: Understand SAS environment
Lecture 4: How to get best out of the course
Chapter 2: SAS syntax and data workout
Lecture 1: Content of the section – what will you learn
Lecture 2: Preamble to Data and download SAS code and data for the exercise
Lecture 3: Import data in SAS
Lecture 4: FAQ – data import issues
Lecture 5: View Meta Data
Lecture 6: View Data
Lecture 7: Direct data entry in SAS
Lecture 8: Analyze categorical variable – Frequency Distribution for categorical variables
Lecture 9: Analyze numeric variable – Univariate and means
Lecture 10: Sorting datasets
Lecture 11: Merging data and missing value replacement
Lecture 12: Appending datasets
Lecture 13: Derive New field
Lecture 14: Arithmetic Logical n comparison Operators
Lecture 15: Truncating data rows n columns wise
Lecture 16: Take part of string using Substr
Lecture 17: Replace the need of multiple conditions using – in operator
Lecture 18: CrossTab of categorical variables
Lecture 19: Numeric Variable Analysis for each class
Lecture 20: dealing with dates
Lecture 21: Proc SQL n Fetching data from database
Chapter 3: Other SAS procedure – for statistical analysis, graphs, tabulate & enhancements
Lecture 1: Section Overview
Lecture 2: FAQ for statistical topic
Lecture 3: Conducting linear regression analysis using SAS
Lecture 4: Conducting Chi square analysis using SAS
Lecture 5: Conducting one way ANOVA analysis using SAS
Lecture 6: Graphs in SAS
Lecture 7: Enhance SAS output readability using Title and Label
Lecture 8: Proc tabulate – pivot table in SAS
Lecture 9: SAS Array – simplification of SAS coding work
Lecture 10: ODS html to package analysis and Colorful / Bold titles for better readability
Lecture 11: Proc transpose to transpose your data
Lecture 12: Proc compare to compare datasets
Chapter 4: Practice Case Studies – apply your knowledge to solve business problems
Lecture 1: Why these practice case studies?
Lecture 2: Q 1: Find new in list B (B-A) stuff
Lecture 3: A 1: Find new in list B (B-A) stuff
Lecture 4: A 1s: Supplementary content on formatting the variable before B-A
Lecture 5: Q 2: Variable Substring Challenge
Lecture 6: A 2: Variable Substring Challenge
Lecture 7: Q 3: Investigate linear relationship between variables
Lecture 8: A 3: Investigate linear relationship between variables
Lecture 9: Q 4:Tabular report in presence of 2 class variable & different statistics neede
Lecture 10: A 4:Tabular report in presence of 2 class variable & different statistics neede
Lecture 11: Q 5s: Little help about seasonality and pair T test for next problem
Lecture 12: Q 5: Pair T Test in presence of seasonality
Lecture 13: A 5: Pair T Test in presence of seasonality
Lecture 14: Q 6: Calculate red car percentage for different age group & run chi square test
Lecture 15: A 6: Calculate red car percentage for different age group & run chi square test
Lecture 16: Q 7: Calculate relative variance (Coefficient of Variance)
Lecture 17: A 7s: What is Coefficient of Variance? Why it is required?
Lecture 18: A 7: Calculate relative variance (Coefficient of Variance)
Lecture 19: Q 8: Work with date and create stacked chart
Lecture 20: A 8: Work with date and create stacked chart
Lecture 21: Q 9: Using SQL within SAS for aggregate function based complexities
Lecture 22: A 9 Part1: Understand SQL syntax for the job
Lecture 23: A 9 Part2: Using SQL within SAS for agreegate function based complexities
Lecture 24: Q 10: Customized complex text for each row (row wise max/min and field name)
Lecture 25: A 10: Customized complex text for each row (row wise max/min and field name)
Lecture 26: Master SAS – How to master R now?
Lecture 27: Bonus Topic – Analytics / Data Science / Machine Learning Interview questions
Lecture 28: Real life example of SAS usage in industry
Lecture 29: Closing note
Instructors
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Gopal Prasad Malakar
Trains Industry Practices on data science / machine learning
Rating Distribution
- 1 stars: 8 votes
- 2 stars: 15 votes
- 3 stars: 26 votes
- 4 stars: 61 votes
- 5 stars: 63 votes
Frequently Asked Questions
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