Introduction to SAS, GUI
Concepts of Libraries, PDV, data execution etc
Building blocks of SAS (Data & Proc Steps - Statements & options)
Debugging SAS Codes
Importing different types of data & connecting to data bases
Data Understanding(Meta data, variable attributes(format, informat, length, label etc)
SAS Procedures for data import /export / understanding(Proc import/Proc contents/Proc print/Proc means/Proc feq)
Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type converstions, renaming, formatting, etc)
Data manipulation tools (Operators, Functions, Procedures, control structures, Loops, arrays etc)
SAS Functions (Text, numeric, date, utility functions)
SAS Procedures for data manipulation (Proc sort, proc format etc)
SAS Options (System Level, procedure level)
Introduction exploratory data analysis
Descriptive statistics, Frequency Tables and summarization
Univariate Analysis (Distribution of data & Graphical Analysis)
Bivariate Analysis(Cross Tabs, Distributions & Relationships, Graphical Analysis)
SAS Procedures for Data Analysis(proc freq/Proc means/proc summary/proc tabulate/Proc univariate etc)
SAS Procedures for Graphical Analysis (Proc Sgplot, proc gplot etc)
Introduction to Reporting
SAS Reporting Procedures (Proc print, Proc Report, Proc Tabulate etc)
Exporting data sets into different formats (Using proc export)
Concept of ODS (output delivery system)
ODS System - Exporting output into different formats
Introduction to Advanced SAS - Proc SQL & Macros
Understanding select statement (From, where, group by, having, order by etc)
Proc SQL - Data creation/extraction
Proc SQL - Data Manipulation steps
Proc SQL - Summarizing Data
Proc SQL - Concept of sub queries, indexes etc
SAS Macros - Creating/defining macro variables
SAS Macros - Defining/calling macros
SAS Macros- Concept of local/global variables
Introduction of Statistics
Descriptive and inferential statistics
Explanatory Versus Predictive Modeling
Population and samples
Uses of variable independent and dependent
Types of variables quantitative and categorical
Descriptive Statistics Introduction
Descriptive Statistics Introduction
Measures of shape skewness
Statistical graphics procedures
The SGPLOT Procedure
ODS Graphics Output
Using SAS to picture your data
Confidence Intervals for the Mean Introduction
Distribution of sample means
Normality and the central limit theorem
Calculation of 95% confidence interval
Hypothesis Testing introduction
Decision Making Process
Steps in Hypothesis Testing
Types of error and power
The p value effect size and sample size
Statistical Hypothesis Test
the t statistic t distribution and two sided t test
Using proc univariate to generate a t statistic
To explore the key windows in SPSS
The syntax editor
How to create variables
Enter Data and adjust the properties of your variables
How to Load Files and Save
Opening Excel Files
Deleting/Inserting a Case or a Column
Using SPSS Help
The art of presenting data
The SPSS Chart Builder
Histograms: a good way to spot obvious problems
Boxplots (box–whisker diagrams)
Graphing means: bar charts and error bars
Simple bar charts for independent means
Graphing relationships: the scatterplot
Simple and grouped -D scatterplots
Simple dot plot or density plot
Type I and Type II errors
What are assumptions?
Assumptions of parametric data
The assumption of normality
Quantifying normality with numbers
Exploring groups of data
Testing whether a distribution is normal
Kolmogorov–Smirnov test on SPSS
Testing for homogeneity of variance
Correcting problems in the data
Looking at relationships
Standardization and the correlation coefficient
The significance of the correlation coefficient
Confidence intervals for r
Comparing independent rs
Calculating the effect size
How to report correlation coefficients
An introduction to regression
Some important information about straight lines
The method of least squares
Assessing the goodness of fit: sums of squares, R and R2
Doing simple regression on SPSS
Multiple regression: the basics
How to do multiple regression using SPSS
Background to logistic regression
What are the principles behind logistic regression?
Assessing the model: the log-likelihood statistic
Assessing the model: R and R2
Methods of logistic regression
Interpreting logistic regression
How to report logistic regression
Predicting several categories: multinomial logistic regression
Running multinomial logistic regression in SPSS
Looking at differences
Rationale for the t-test
Reporting the dependent t-test
Reporting the independent t-test
Between groups or repeated measures?
The t-test as a general linear model
Comparing several means : ANOVA (GLM)
The theory behind ANOVA
The theory behind ANOVA
Inflated error rates
ANOVA as regression
Assumptions of ANOVA
Post hoc procedure
Introduction to Tableau Desktop
Use and benefits of Tableau Desktop
Data Source Page
Creating a Basic View
Visual Cues for Fields
Cross Database Joins
Joining vs. Blending
Creating Data Extracts
Writing Custom SQL
Creating Combined Fields
Creating Groups and Defining Aliases
Working with Sets and Combined Sets
Drilling and Hierarchy
Adding Grand Totals and Subtotals
Changing Aggregation Functions
Cross Data Source Filter
Effectively use Titles, Captions, and Tooltips
Format Results with the Edit Axes
Formatting your View
Formatting results with Labels and Annotations
Enabling Legends per Measure
Use Strings, Date, Logical, and Arithmetic Calculations
Create Table Calculations
Discover Ad-hoc Analytics
Perform LOD Calculations
Creating Basic Charts such as Heat Map, Tree Map, Bullet Chart, and so on
Creating Advanced Chart as Waterfall, Pareto, Gantt, Market Basket
Build Interactive Dashboards
Explore Dashboard Actions
Best Practices for Creating Effective Dashboards
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