This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.
Statistics with SAS
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作业
61 项作业
授课语言：英语（English）
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该课程共有8个模块
In this module you learn about the course and the data you analyze in this course. Then you set up the data you need to do the practices in the course.
涵盖的内容
2个视频5篇阅读材料
2个视频•总计13分钟
- Welcome and Meet the Instructor•2分钟
- Demo: Exploring Ames Housing Data•11分钟
5篇阅读材料•总计29分钟
- Learner Prerequisites•1分钟
- Access SAS Software and Set Up Practice Files (REQUIRED)•3分钟
- Completing Demos and Practices•10分钟
- Using Forums and Getting Help•5分钟
- Frequently Asked Questions•10分钟
In this module you learn about the models required to analyze different types of data and the difference between explanatory vs predictive modeling. Then you review fundamental statistical concepts, such as the sampling distribution of a mean, hypothesis testing, p-values, and confidence intervals. After reviewing these concepts, you apply one-sample and two-sample t tests to data to confirm or reject preconceived hypotheses.
涵盖的内容
17个视频2篇阅读材料9个作业
17个视频•总计41分钟
- Overview•1分钟
- Statistical Modeling: Types of Variables•1分钟
- Overview of Models•3分钟
- Explanatory versus Predictive Modeling•1分钟
- Population Parameters and Sample Statistics•2分钟
- Normal (Gaussian) Distribution•3分钟
- Standard Error of the Mean•1分钟
- Confidence Intervals•2分钟
- Statistical Hypothesis Test•4分钟
- p-Value: Effect Size and Sample Size Influence•3分钟
- Scenario•1分钟
- Performing a t Test•4分钟
- Demo: Performing a One-Sample t Test Using PROC TTEST•4分钟
- Scenario•1分钟
- Assumptions for the Two-Sample t Test•2分钟
- Testing for Equal and Unequal Variances•2分钟
- Demo: Performing a Two-Sample t Test Using PROC TTEST•5分钟
2篇阅读材料•总计20分钟
- Parameters and Statistics•10分钟
- Normal Distribution•10分钟
9个作业•总计100分钟
- Question 1.01•5分钟
- Question 1.02•5分钟
- Question 1.03•5分钟
- Question 1.04•5分钟
- Question 1.05•5分钟
- Practice - Using PROC TTEST to Perform a One-Sample t Test•20分钟
- Question 1.06•5分钟
- Practice - Using PROC TTEST to Compare Groups•20分钟
- Introduction and Review of Concepts•30分钟
In this module you learn to use graphical tools that can help determine which predictors are likely or unlikely to be useful. Then you learn to augment these graphical explorations with correlation analyses that describe linear relationships between potential predictors and our response variable. After you determine potential predictors, tools like ANOVA and regression help you assess the quality of the relationship between the response and predictors.
涵盖的内容
29个视频2篇阅读材料14个作业
29个视频•总计70分钟
- Overview•1分钟
- Scenario•1分钟
- Identifying Associations in ANOVA with Box Plots•2分钟
- Demo: Exploring Associations Using PROC SGPLOT•2分钟
- Identifying Associations in Linear Regression with Scatter Plots•1分钟
- Demo: Exploring Associations Using PROC SGSCATTER•2分钟
- Scenario•1分钟
- The ANOVA Hypothesis•1分钟
- Partitioning Variability in ANOVA•2分钟
- Coefficient of Determination•1分钟
- F Statistic and Critical Values•2分钟
- The ANOVA Model•3分钟
- Demo: Performing a One-Way ANOVA Using PROC GLM•7分钟
- Scenario•1分钟
- Multiple Comparison Methods•3分钟
- Tukey's and Dunnett's Multiple Comparison Methods•2分钟
- Diffograms and Control Plots•1分钟
- Demo: Performing a Post Hoc Pairwise Comparison Using PROC GLM•7分钟
- Scenario•1分钟
- Using Correlation to Measure Relationships between Continuous Variables•1分钟
- Hypothesis Testing for a Correlation•1分钟
- Avoiding Common Errors When Interpreting Correlations•5分钟
- Demo: Producing Correlation Statistics and Scatter Plots Using PROC CORR•6分钟
- Scenario•1分钟
- The Simple Linear Regression Model•1分钟
- How SAS Performs Simple Linear Regression•1分钟
- Comparing the Regression Model to a Baseline Model•2分钟
- Hypothesis Testing and Assumptions for Linear Regression•1分钟
- Demo: Performing Simple Linear Regression Using PROC REG•7分钟
2篇阅读材料•总计20分钟
- What Does a CLASS Statement Do?•10分钟
- Correlation Analysis and Model Building•10分钟
14个作业•总计155分钟
- Question 2.01•5分钟
- Question 2.02•5分钟
- Question 2.03•5分钟
- Question 2.04•5分钟
- Practice - Performing a One-Way ANOVA•20分钟
- Question 2.05•5分钟
- Question 2.06•5分钟
- Practice - Using PROC GLM to Perform Post Hoc Parwise Comparisons•20分钟
- Question 2.07•5分钟
- Question 2.08•5分钟
- Practice - Describing the Relationship between Continuous Variables•20分钟
- Question 2.09•5分钟
- Practice - Using PROC REG to Fit a Simple Linear Regression Model•20分钟
- ANOVA and Regression•30分钟
In this module you expand the one-way ANOVA model to a two-factor analysis of variance and then extend simple linear regression to multiple regression with two predictors. After you understand the concepts of two-way ANOVA and multiple linear regression with two predictors, you'll have the skills to fit and interpret models with many variables.
涵盖的内容
13个视频1篇阅读材料5个作业
13个视频•总计43分钟
- Overview•2分钟
- Scenario•1分钟
- Applying the Two-Way ANOVA Model•4分钟
- Demo: Performing a Two-Way ANOVA Using PROC GLM•7分钟
- Interactions•3分钟
- Demo: Performing a Two-Way ANOVA With an Interaction Using PROC GLM•6分钟
- Demo: Performing Post-Processing Analysis Using PROC PLM•4分钟
- Scenario•1分钟
- The Multiple Linear Regression Model•3分钟
- Hypothesis Testing for Multiple Regression•1分钟
- Multiple Linear Regression versus Simple Linear Regression•3分钟
- Adjusted R-Square•2分钟
- Demo: Fitting a Multiple Linear Regression Model Using PROC REG•7分钟
1篇阅读材料•总计10分钟
- The STORE Statement•10分钟
5个作业•总计80分钟
- Question 3.01•5分钟
- Practice - Performing a Two-Way ANOVA Using PROC GLM•20分钟
- Question 3.02•5分钟
- Practice - Performing Multiple Regression Using PROC REG•20分钟
- More Complex Linear Models•30分钟
In this module you explore several tools for model selection. These tools help limit the number of candidate models so that you can choose an appropriate model that's based on your expertise and research priorities.
涵盖的内容
11个视频3篇阅读材料4个作业
11个视频•总计28分钟
- Overview•1分钟
- Scenario•1分钟
- Approaches to Selecting Models•2分钟
- The All-Possible Regressions Approach to Model Building•1分钟
- The Stepwise Selection Approach to Model Building•3分钟
- Interpreting p-Values and Parameter Estimates•2分钟
- Demo: Performing Stepwise Regression Using PROC GLMSELECT•8分钟
- Scenario•1分钟
- Information Criteria•2分钟
- Adjusted R-Square and Mallows' Cp•1分钟
- Demo: Performing Model Selection Using PROC GLMSELECT•6分钟
3篇阅读材料•总计20分钟
- Activity - Optional Stepwise Selection Method Code•10分钟
- Information Criteria Penalty Components•10分钟
- All-Possible Selection•0分钟
4个作业•总计65分钟
- Question 4.01•5分钟
- Practice - Using PROC GLMSELECT to Perform Stepwise Selection•20分钟
- Practice - Using PROC GLMSELECT to Perform Other Model Selection Techniques•20分钟
- Model Building and Effect Selection•20分钟
In this module you learn to verify the assumptions of the model and diagnose problems that you encounter in linear regression. You learn to examine residuals, identify outliers that are numerically distant from the bulk of the data, and identify influential observations that unduly affect the regression model. Finally, you learn to diagnose collinearity to avoid inflated standard errors and parameter instability in the model.
涵盖的内容
18个视频7个作业
18个视频•总计46分钟
- Overview•1分钟
- Scenario•1分钟
- Assumptions for Regression•2分钟
- Verifying Assumptions Using Residual Plots•3分钟
- Demo: Examining Residual Plots Using PROC REG•5分钟
- Scenario•1分钟
- Identifying Influential Observations•1分钟
- Checking for Outliers with STUDENT Residuals•1分钟
- Checking for Influential Observations•3分钟
- Detecting Influential Observations with DFBETAS•1分钟
- Demo: Looking for Influential Observations Using PROC GLMSELECT and PROC REG•5分钟
- Demo: Examining the Influential Observations Using PROC PRINT•7分钟
- Handling Influential Observations•2分钟
- Scenario•1分钟
- Exploring Collinearity•2分钟
- Visualizing Collinearity•2分钟
- Demo: Calculating Collinearity Diagnostics Using PROC REG•5分钟
- Using an Effective Modeling Cycle•2分钟
7个作业•总计105分钟
- Practice: Using PROC REG to Examine Residuals•20分钟
- Question 5.01•5分钟
- Practice: Using PROC REG to Generate Potential Outliers•20分钟
- Question 5.02•5分钟
- Question 5.03•5分钟
- Practice: Using PROC REG to Assess Collinearity•20分钟
- Model Post-Fitting for Inference•30分钟
In this module you learn how to transition from inferential statistics to predictive modeling. Instead of using p-values, you learn about assessing models using honest assessment. After you choose the best performing model, you learn about ways to deploy the model to predict new data.
涵盖的内容
11个视频1篇阅读材料4个作业
11个视频•总计27分钟
- Overview•2分钟
- Scenario•0分钟
- Predictive Modeling Terminology•2分钟
- Model Complexity•1分钟
- Building a Predictive Model•3分钟
- Model Assessment and Selection•2分钟
- Demo: Building a Predictive Model Using PROC GLMSELECT•11分钟
- Scenario•0分钟
- Preparing for Scoring•1分钟
- Methods of Scoring•1分钟
- Demo: Scoring Data Using PROC PLM•4分钟
1篇阅读材料•总计10分钟
- Partitioning a Data Set Using PROC GLMSELECT•10分钟
4个作业•总计75分钟
- Question 6.01•5分钟
- Practice: Building a Predictive Model Using PROC GLMSELECT•20分钟
- Practice: Scoring Using the SCORE Statement in PROC GLMSELECT•20分钟
- Model Building for Scoring and Prediction•30分钟
In this module you look for associations between predictors and a binary response using hypothesis tests. Then you build a logistic regression model and learn about how to characterize the relationship between the response and predictors. Finally, you learn how to use logistic regression to build a model, or classifier, to predict unknown cases.
涵盖的内容
25个视频18个作业
25个视频•总计73分钟
- Overview•2分钟
- Scenario•1分钟
- Associations between Categorical Variables•2分钟
- Demo: Examining the Distribution of Categorical Variables Using PROC FREQ and PROC UNIVARIATE•6分钟
- Scenario•1分钟
- The Pearson Chi-Square Test•3分钟
- Odds Ratios•4分钟
- Demo: Performing a Pearson Chi-Square Test of Association Using PROC FREQ•5分钟
- Scenario•0分钟
- The Mantel-Haenszel Chi-Square Test•1分钟
- The Spearman Correlation Statistic•1分钟
- Demo: Detecting Ordinal Associations Using PROC FREQ•2分钟
- Scenario•1分钟
- Modeling a Binary Response•4分钟
- Demo: Fitting a Binary Logistic Regression Model Using PROC LOGISTIC•7分钟
- Interpreting the Odds Ratio•3分钟
- Comparing Pairs to Assess the Fit of a Logistic Regression Model•5分钟
- Scenario•1分钟
- Specifying a Parameterization Method•5分钟
- Demo: Fitting a Multiple Logistic Regression Model with Categorical Predictors Using PROC LOGISTIC•7分钟
- Scenario•1分钟
- Interactions between Variables•2分钟
- Demo: Fitting a Multiple Logistic Regression Model with Interactions Using PROC LOGISTIC•4分钟
- Demo: Fitting a Multiple Logistic Regression Model with All Odds Ratios Using PROC LOGISTIC•3分钟
- Demo: Generating Predictions Using PROC PLM•2分钟
18个作业•总计190分钟
- Question 7.01•5分钟
- Question 7.02•5分钟
- Practice: Using PROC FREQ to Examine Distributions•20分钟
- Question 7.03•5分钟
- Question 7.04•5分钟
- Question 7.05•5分钟
- Question 7.06•5分钟
- Practice: Using PROC FREQ to Perform Tests and Measures of Association•20分钟
- Question 7.07•5分钟
- Question 7.08•5分钟
- Practice: Using PROC LOGISTIC to Perform a Binary Logistic Regression Analysis•20分钟
- Question 7.09•5分钟
- Question 7.10•5分钟
- Practice: Using PROC LOGISTIC to Perform a Multiple Logistic Regression Analysis with Categorical Variables•20分钟
- Question 7.11•5分钟
- Question 7.12•5分钟
- Practice: Using PROC LOGISTIC to Perform Backward Elimination and PROC PLM to Generate Predictions•20分钟
- Categorical Data Analysis•30分钟
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4.7 (105个评价)授课教师评分
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SAS
Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.
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学生评论
4.7
301 条评论
- 5 stars
83.05%
- 4 stars
12.29%
- 3 stars
2.32%
- 2 stars
0.66%
- 1 star
1.66%
显示 3/301 个
T
T
5·
已于 Apr 10, 2022审阅
Very professional and useful course. I like it. The level of difficulty is very balanced, neither easy nor very hard.
S
SS
5·
已于 May 1, 2022审阅
The course was very useful to reinforce the basics of Statistics. The real life examples to drive the concepts were very good and easy to understand
R
RN
5·
已于 Oct 28, 2019审阅
best course to learn n rewind concepts. helped me at lot for my placement preparations
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