This course covers predictive modeling using SAS/STAT software with emphasis on the LOGISTIC procedure. This course also discusses selecting variables and interactions, recoding categorical variables based on the smooth weight of evidence, assessing models, treating missing values, and using efficiency techniques for massive data sets. You learn to use logistic regression to model an individual's behavior as a function of known inputs, create effect plots and odds ratio plots, handle missing data values, and tackle multicollinearity in your predictors. You also learn to assess model performance and compare models.


Predictive Modeling with Logistic Regression using SAS
ę¬čƾēØęÆ SAS Statistical Business Analyst äøäøčÆä¹¦ ēäøéØå

ä½ęåøļ¼Marc Huber
8,128 人已注å
å
å«åØ äø
ļ¼63 ę”čÆč®ŗļ¼
ęØå°č·å¾ēęč½
č¦äŗč§£ē详ē»äæ”ęÆ

ę·»å å°ęØēé¢č±ę”£ę”
40 锹ä½äø
äŗč§£é”¶ēŗ§å ¬åøēåå·„å¦ä½ęę”ēéØęč½

积瓯 Data Analysis é¢åēäøäøē„čÆ
- åč”äøäøå®¶å¦ä¹ ę°ę¦åæµ
- č·å¾åÆ¹äø»é¢ęå·„å ·ēåŗē”ēč§£
- éčæå®č·µé”¹ē®å¹å »å·„ä½ēøå ³ęč½
- éčæ SAS č·å¾åÆå ±äŗ«ēčäøčÆä¹¦

评课ēØå ±ę7个樔å
ę¶µēēå 容
1äøŖč§é¢7ēÆé 读ęę
In this module, you review the fundamentals of predictive modeling. Then you explore the business scenario data that is used throughout the course. Finally, you learn about common analytical challenges that you might encounter as a modeler.
ę¶µēēå 容
15äøŖč§é¢1ēÆé 读ęę6äøŖä½äø
In this module, you investigate the concepts behind the logistic regression model. Then you learn to use the LOGISTIC procedure to fit a logistic regression model. Finally, you learn how to score new cases and adjust the model for oversampling.
ę¶µēēå 容
18äøŖč§é¢1ēÆé 读ęę4äøŖä½äø
In this module, you learn how to deal with common problems with your predictor variables such as missing values, categorical predictors with many levels, a high number of redundant predictors, and nonlinear relationships with the response variable.
ę¶µēēå 容
26äøŖč§é¢9äøŖä½äø
In this module, you learn how to select the most predictive variables to use in your model.
ę¶µēēå 容
23äøŖč§é¢1ēÆé 读ęę12äøŖä½äø
In this module, you learn how to assess the performance of your model and how to determine allocation rules that maximize profit. Finally, you learn how to generate a family of increasingly complex predictive models and how to select the best model.
ę¶µēēå 容
30äøŖč§é¢1ēÆé 读ęę9äøŖä½äø
ę¶µēēå 容
1ēÆé 读ęę1äøŖåŗēØēØåŗé”¹ē®
č·å¾čäøčÆä¹¦
å°ę¤čÆä¹¦ę·»å å°ęØē LinkedIn äøŖäŗŗčµęćē®åę屄åäøćåØē¤¾äŗ¤åŖä½å绩ęčę øäøåäŗ«ć
ä½ęåø

ęä¾ę¹
ä» Data Analysis ęµč§ę“å¤å 容
- ē¶ęļ¼é¢č§
- ē¶ęļ¼å 蓹čÆēØ
- ē¶ęļ¼å 蓹čÆēØ
人们为ä»ä¹éę© Coursera ę„åø®å©čŖå·±å®ē°čäøåå±




å¦ēčÆč®ŗ
63 ę”čÆč®ŗ
- 5 stars
79.36%
- 4 stars
14.28%
- 3 stars
0%
- 2 stars
3.17%
- 1 star
3.17%
ę¾ē¤ŗ 3/63 äøŖ
å·²äŗ Jun 14, 2021å®”é
Thank you so much to the instructor, Michael J Patetta for teaching this course!
å·²äŗ Apr 10, 2021å®”é
Great training sets of problems. Good guidance & teaching.

éčæ Coursera Plus å¼åÆę°ēę¶Æ
ę éå¶č®æé® 10,000+ äøēäøęµē课ēØćå®č·µé”¹ē®åå°±äøå°±ē»ŖčÆä¹¦čÆ¾ēØ - ęęčæäŗé½å å«åØęØē订é äø
éčæåØēŗæå¦ä½ęØåØęØēčäøēę¶Æ
č·åäøēäøęµå¤§å¦ēå¦ä½ - 100% åØēŗæ
å å „č¶ čæ 3400 å®¶éę© Coursera for Business ēå Øēå ¬åø
ęååå·„ēęč½ļ¼ä½æå ¶åØę°åē»ęµäøč±é¢čåŗ
åøøč§é®é¢
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
ę“å¤é®é¢
ęä¾å©å¦éļ¼