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

Name: A00-240: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling Training Course
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SKU: A00-240: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling
Price: 14.99 USD
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Best Seller 79 Lectures 10h 29m

Prepare for your SAS Institute examination with our training course. The A00-240 course contains a complete batch of videos that will provide you with profound and thorough knowledge related to SAS Institute certification exam. Pass the SAS Institute A00-240 test with flying colors.

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Curriculum For This Course

1. Free cloud-based SAS software option for learning: SAS OnDemand for Academics

4 lectures 23m

1. Create a SAS account to access SAS ondemand for Academics 3m
2. Upload course data files and SAS programs into SAS ondemand for academics 6m
3. change file path/directory in SAS ondemand for academics 7m
4. examples: update and run SAS programs in SAS ondemand for academics 7m

2. Analysis of Variance (ANOVA)

18 lectures 1h 59m

1. ANOVA 0 10m
2. Using Proc Univariate to Test the Normality Assumption Using the K-S Test 3m
3. ANOVA 1 10m
4. ANOVA 2 7m
5. ANOVA 3 4m
6. ANOVA 4 4m
7. ANOVA 5 3m
8. ANOVA 6 4m
9. 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

3. Prepare Inputs Vars for predictive Modeling

6 lectures 47m

1. Prepare Inputs Vars_1 6m
2. Prepare Inputs Vars_2 13m
3. Prepare Inputs Vars_3.Categorical Input Variable_1.Knowledge points 5m
4. Prepare Inputs Vars_3 7m
5. Prepare Inputs Vars_4 11m
6. Prepare Inputs Vars_5 5m

4. Linear Regression Analysis

17 lectures 2h 54m

1. Exploring the Relationship between Two Continuous Variables using Scatter Plots 10m
2. Producing Correlation Coefficients Using the CORR Procedure 15m
3. Multiple Linear Regression: fit multiple regression with Proc REG 10m
4. Multiple Linear Regression: Measures of fit 6m
5. Multiple Linear Regression: Quantifying the Relative Impact of a Predictor 3m
6. Multiple Linear Regression: Check Collinearity Using VIF, COLLIN, and COLLINOINT 11m
7. fit simple linear regression with Proc GLM 15m
8. Multiple Linear Reg: Var Selection With Proc REG:all possible subset: adjust R2 12m
9. 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

5. Logistic Regression Analysis

18 lectures 2h 16m

1. Logistic Regression Analysis: Overview 10m
2. logistic regression with a continuous numeric predictor Part 1 5m
3. logistic regression with a continuous numeric predictor Part 2 15m
4. Plots for Probabilities of an Event 5m
5. Plots of the Odds Ratio 6m
6. logistic regression with a categorical predictor: Effect Coding Parameterization 10m
7. logistic reg with categorical predictor: Reference Cell Coding Parameterization 5m
8. Multiple Logistic Regression: full model SELECTION=NONE 8m
9. 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

6. Measure of Model Performance

16 lectures 2h 10m

1. Measure of Model Performance: Overview 10m
2. PROC SURVEYSELECT for Creating Training and Validation Data Sets 10m
3. Measures of Performance Using the Classification Table: PowerPoint Presentation 7m
4. Using The CTABLE Option in Proc Logistic for Producing Classification Results 10m
5. Assessing the Performance & Generalizability of a Classifier: PowerPoint slides 4m
6. The Effect of Cutoff Values on Sensitivity and Specificity Estimates 11m
7. Measure of Performance Using the Receiver-Operator-Characteristic (ROC) Curve 7m
8. Model Comparison Using the ROC and ROCCONTRAST Statements 5m
9. 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

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

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