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SAS

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Description

The data analysis training with SAS is used in the management of data, analysis, and graphics. It comprises of advanced functions which includes forecasting, survival analysis, data analysis, and time series analysis and survey methods. It can be utilized via graphical interface using very intuitive language.

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Course Modules

Module 1: Research Design, Analysis and interpretation
  • Introduction to Research and the Research Process
  • Problem Definition
  • Research Design and Secondary Data Sources
  • Qualitative Methods
  • Descriptive Research Design and Observation
  • Causal Research Design
  • Measurement, Scaling and Sampling
  • Data Preparation and Analysis Strategy
  • Hypothesis testing, Frequencies and Cross-tabulation
  • Testing for Significant Differences – t-test/ANOVA
  • Testing for Association – Correlation and Regression
Module 2: Understanding the Workflow
  • The Workflow
  • SAS Basics
  • Data Importing - Instream data and Proc Import
  • Import Wizard for SAS 9.x
  • Data Importing in SAS Studio
  • Bring in Data from Pre-existing SAS Dataset and Create Permanent Dataset
  • Data importing - excel data
Module 3: Data Manipulation - Naming Convention and IF THEN/ELSE Statement
  • Naming Convention and Variable Types
  • IF THEN/ELSE Statement
  • Keep and Drop Variables
  • Data Manipulation - SAS Functions and DO Loop
  • SAS Functions
  • DO Loop
  • Dataset Manipulation - Subset and Append
Module 4: Dataset Manipulation - Merge and Transposition
  • Merge
  • Merge two datasets into a single dataset
  • Project part 3: Merge two datasets
  • Transpose
  • A comprehensive task using several techniques to subset, transpose data
Module 5: Descriptive Statistics - Frequency and Univariate Analysis
  • Explore the Data Using PROC PRINT and CONTENTS Procedures
  • Descriptive Statistics
  • Calculate the mean of the sample
  • PROC FREQ
Module 5: Perform descriptive statistical analysis
  • One, Two Sample T-Test and ANOVA
  • One Sample T-Tes
  • Two Sample T-Test
  • Two Sample T-Test and paired T-Test
  • Sample ANOVA
  • Non-parametric Analysis
Module 7: Linear Regression - Predicting the Outcome
  • Linear Regression
  • Use Linear Regression model to predict the MSRP
  • Dummy Variable
  • Include some categorical variables into the model

Duration: 4 -6 weeks

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