Certification training

A00-240A00-240: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling

Prepare for your SAS Institute exam with a structured video course built for focused study, topic review, and repeatable progress before exam day.

79Lectures
10h 29mDuration
SAS InstituteVendor
A00-240: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling course cover Best seller
SAS Institute certification training A00-240 79 lessons arranged in a guided course path
Course overview

Study with a clear path.

Move through focused sections, review lecture timing, and return directly to the objectives that need more work.

Sequenced lessons

Follow the course in order or jump directly to the section you need to revisit.

Video-first prep

Use concise lecture blocks for technical review before moving into exam practice.

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Curriculum

Course sections.

6 sections, 79 lessons, and lecture-level duration details.

01 Create a SAS account to access SAS ondemand for Academics 3m
02 Upload course data files and SAS programs into SAS ondemand for academics 6m
03 change file path/directory in SAS ondemand for academics 7m
04 examples: update and run SAS programs in SAS ondemand for academics 7m

01 ANOVA 0 10m
02 Using Proc Univariate to Test the Normality Assumption Using the K-S Test 3m
03 ANOVA 1 10m
04 ANOVA 2 7m
05 ANOVA 3 4m
06 ANOVA 4 4m
07 ANOVA 5 3m
08 ANOVA 6 4m
09 ANOVA 7 12m
10 ANOVA 8 10m
11 ANOVA 9 16m
12 ANOVA 10 3m
13 ANOVA 11 3m
14 ANOVA 12 5m
15 ANOVA 13 8m
16 ANOVA 14 11m
17 ANOVA 15 3m
18 ANOVA 16 3m

01 Prepare Inputs Vars_1 6m
02 Prepare Inputs Vars_2 13m
03 Prepare Inputs Vars_3.Categorical Input Variable_1.Knowledge points 5m
04 Prepare Inputs Vars_3 7m
08 Prepare Inputs Vars_4 11m
10 Prepare Inputs Vars_5 5m

01 Exploring the Relationship between Two Continuous Variables using Scatter Plots 10m
02 Producing Correlation Coefficients Using the CORR Procedure 15m
03 Multiple Linear Regression: fit multiple regression with Proc REG 10m
04 Multiple Linear Regression: Measures of fit 6m
05 Multiple Linear Regression: Quantifying the Relative Impact of a Predictor 3m
06 Multiple Linear Regression: Check Collinearity Using VIF, COLLIN, and COLLINOINT 11m
07 fit simple linear regression with Proc GLM 15m
08 Multiple Linear Reg: Var Selection With Proc REG:all possible subset: adjust R2 12m
09 Multiple Linear Reg: Var Selection With Proc REG:all possible subset: Mallows Cp 6m
10 Multiple Linear Regression:Variable Selection With Proc REG:Backward Elimination 8m
11 Multiple Linear Regression:Variable Selection With Proc REG: Forward selection 9m
12 Multiple Linear Regression:Variable Selection With Proc REG: Stepwise selection 4m
13 Multiple Linear Regression:Variable Selection With Proc GLMSELECT 15m
14 Multiple Linear Regression: PowerPoint Slides on regression assumptions 8m
15 Multiple Linear Regression: regression assumptions 13m
16 Multiple Linear Regression: PowerPoint Slides on influential observations 11m
17 Multiple Linear Regression: Using statistics to identify influential observation 18m

01 Logistic Regression Analysis: Overview 10m
02 logistic regression with a continuous numeric predictor Part 1 5m
03 logistic regression with a continuous numeric predictor Part 2 15m
04 Plots for Probabilities of an Event 5m
05 Plots of the Odds Ratio 6m
06 logistic regression with a categorical predictor: Effect Coding Parameterization 10m
07 logistic reg with categorical predictor: Reference Cell Coding Parameterization 5m
08 Multiple Logistic Regression: full model SELECTION=NONE 8m
09 Multiple Logistic Regression: Backward Elimination 8m
10 Multiple Logistic Regression: Forward Selection 6m
11 Multiple Logistic Regression: Stepwise Selection 7m
12 Multiple Logistic Regression: Customized Options 12m
13 Multiple Logistic Regression: Best Subset Selection 5m
14 Multiple Logistic Regression: model interaction 14m
15 Multiple Logistic Reg: Scoring New Data: SCORE Statement with PROC LOGISTIC 6m
16 Multiple Logistic Reg: Scoring New Data: Using the PLM Procedure 5m
17 Multiple Logistic Reg: Scoring New Data: the CODE Statement within PROC LOGISTIC 4m
18 Multiple Logistic Reg: Score New Data: OUTMODEL & INMODEL Options with Logistic 5m

01 Measure of Model Performance: Overview 10m
02 PROC SURVEYSELECT for Creating Training and Validation Data Sets 10m
03 Measures of Performance Using the Classification Table: PowerPoint Presentation 7m
04 Using The CTABLE Option in Proc Logistic for Producing Classification Results 10m
05 Assessing the Performance & Generalizability of a Classifier: PowerPoint slides 4m
06 The Effect of Cutoff Values on Sensitivity and Specificity Estimates 11m
07 Measure of Performance Using the Receiver-Operator-Characteristic (ROC) Curve 7m
08 Model Comparison Using the ROC and ROCCONTRAST Statements 5m
09 Measures of Performance Using the Gains Charts 11m
10 Measures of Performance Using the Lift Charts 4m
11 Adjust for Oversample: PEVENT Option for Priors & Manually adjust Classification 16m
12 Manually Adjusting Posterior Probabilities to Account for Oversampling 5m
13 Manually Adjusted Intercept Using the Offset to account for oversampling 7m
14 Automatically Adjusted Posterior Probabilities to Account for Oversampling 6m
15 Decision Theory: Decision Cutoffs and Expected Profits for Model Selection 12m
16 Decision Theory: Using Estimated Posterior Probabilities to Determine Cutoffs 5m
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