SAS Programming from Scratch & Practice Case Studies workout

  • 3.9
4.5 hours on-demand video
$ 10.99
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Brief Introduction

Learn SAS programming through data workout. See sorting, merging, appending, graphs, tabulate, statistical procedure etc

Description

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

  • Getting free access to SAS
  • Importing data
  • Getting basic feel of data- through contents, print, freq, univariate 
  • Data operations like merge, append, sort, truncate – rows / columns wise, 
  • derive new fields, 
  • analysis for each class 
  • Graphs – vertical bar chart / pie charts / stacked charts 
  • Statistical procedure
  • Title and labels for enhancements
  • Tabulate for pivot table kind of work
  • Putting together analysis with ODS HTML and colorful title
  • proc transpose to transpose the data
  • proc compare to compare datasets



The course content in detail is as follows

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Section 1 : Getting access to SAS and understand SAS environment

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  • Getting free access to learn SAS
  • Get familiar with SAS environment

Understand what is

  1. Program editor
  2. Log window
  3. Output window
  4. Library etc.



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Section 2 : Most used data operations in SAS

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  • Get familiar with the  Data for workout
  • Import data in SAS
  • Viewing Meta Data
  • Viewing Data

Understand various options to print









  1. Few records starting from a particular observation
  2. Few columns / all columns
  3. precaution
  • Direct data entry in SAS
    1. How to be careful for character format
  • Frequency Distribution for categorical variables

Understand

  1. Various parts of the output
  2. Default and quantity based sorting order
  3. Storing proc freq output into a SAS dataset
  4. Why one should avoid proc freq for numeric variable
  • Numeric Variable Analysis

Understand

  1. Proc Univariate and Proc Means
  2. Advantages of both the approaches
  3. Requesting few statistics only in the output
  • Sorting Data

Understand

  1. How to sort on the basis of one variable / two variables
  2. How to keep original data as it is and store sorted data in a new dataset
  3. How to sort data in descending order
  4. How to remove duplicates
  5. What is first. and last. option and how to use it
  • Merging n Dealing with missing data

Understand

  1. What is merging data
  2. What are the Pre requisites of merging data
  3. What is left join, right join and equi join
  4. How to do various kinds of join
  5. How is missing value represented for numeric and character variable
  6. Syntax for replacing missing value for a numeric variable
  7. Syntax for replacing missing value for a character variable
  • Appending datasets

Understand

  1. What is appending datasets?
  2. How to append data?
  3. What happens when datsets have different columns and still you want to append it?
  • Derive New field
  1. Write if else logic to create a derived field
  2. Learn to use OR operator
  3. Understand how to define length for proper display of variable
  • Arithmetic Logical n comparison Operators
  1. Get to know the different Arithmetic, Logical and Comparison operators we have
  2. Demo of how to use them for the whole data set
  3. Also see how to keep only those records, which meets certain criteria
  • Truncating data rows n columns wise
  1. Learn how to keep or drop few fields from a given dataset
  2. Learn to keep or delete few records meeting certain criteria
  • Part of string using Substr
  1. Understand the syntax for substring
  2. See the workout example
  • in operator
  1. Understand the usage of in operator
  2. See the demo to understand how does it make it easy to compare multiple string in one go
  • CrossTab using SAS

Understand

  1. How to create cross tab in SAS?
  2. How to interpret the output
  3. How to supress some statistics from the result?
  • Numeric Variable Analysis for each class
  1. Understand how to conduct analysis for each distinct value of a particular categorical variable easily using class statement
  • dealing with dates
  1. Understand date 9 format
  2. The usage of mdy function to create date
  3. Find days / years spend between two dates
  4. Use round function to get nicely formatted value
  • Proc SQL n Fetching data from database
  1. Understand the utility of Proc SQL
  2. Understand the process of getting data from databases using proc SQL



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Section 3 : Statistical procedures and report enhancements

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  • Conducting linear regression analysis using SAS
  1. Understand how to conduct linear regression analysis using SAS
  2. How to get the regression equation, coefficient of determination etc.
  3. How to interpret coefficient of determination
  4. How to make out, it is a positive or negative relationship
  • Conducting Chi square analysis using SAS
  1. Understand how to get chi square statistics for contingency table
  2. How to make sense of degree of freedom, chi square statistics, p value etc.
  • Conducting one way ANOVA analysis  using SAS
  1. Learn the syntax of ANOVA analysis using SAS
  2. Learn to interpret the box plot appearing with ANOVA analysis
  3. Learn to make sense of p value of ANOVA
  • Graphs in SAS

Learn to

  1. Create vertical bar chart
  2. Create horizontal bar chart
  3. How to get just the percentage or freq, percent all
  4. How to create stacked bar chart (where bars of numeric variable can show distribution of a categorical variable)
  5. How to create a pie chart
  6. Difference between proc gchart and proc chart
  7. How to create chart of a numeric variable for each class separately
  • Title and Label
  1. How to put specific title above the print / graph output etc.
  2. How does title 1 and title 2 differ
  3. What is label
  4. What is the use of these title and label statement
  • Proc tabulate - pivot table in SAS
  1. Understand the syntax of proc tabulate
  2. See proc tabulate and Excel pivot table side by side
  • ODS HTML to package the output and rich text title (bold, colorful)
  • Proc transpose to transpose the data
  • Proc compare to compare datasets

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Section 4 - Practice Case Studies - apply your knowledge to solve business problems

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Requirements

  • Requirements
  • Basic computer skills
  • Internet Connectivity - throughout the course

Keywords

$ 10.99
English
Available now
4.5 hours on-demand video
Gopal Prasad Malakar
Udemy

Instructor

Gopal Prasad Malakar

  • 3.9 Raiting

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