main lecturer
Liu Shaoqing, associate professor, has 14 years of teaching experience, 8 years of experience in data mining projects; specializes in designing data mining business application solutions, can propose analysis models based on user business characteristics, select appropriate data mining algorithms for portfolio analysis, evaluation analysis Results; familiar with a variety of statistical software and databases. He has worked on projects for a number of companies, and has also trained as a trainer for data mining and data analysis for many companies or MBA seminars. He has extensive project and training experience.
Training objectives
Combine a supermarket sales data, through the case analysis method, from simple to complex, explain the decision-making problem based on data mining, to achieve the following objectives:
1. Understand SPSS graphics applications, simple statistical analysis algorithms, analyze data characteristics, and know "what happened"
2. Understand the application of algorithms such as SPSS decision tree, analyze category features, perform category prediction, and know “what will happenâ€
3. Understand the application of SPSS logistic regression and other algorithms, find out the influencing factors of an event, and know "why will happen"
4, encounter similar business problems, can be applied in a short time, use SPSS tools to select the appropriate algorithm for analysis
Course content introduction
Combine a supermarket sales data, through the case analysis method, introduce the following:
1. "What happened" problem and SPSS related functions and applications
Through the relevant functions of SPSS, the data is analyzed and it is found that the data tells us what has happened, but we did not notice.
(1) SPSS drawing function and common graphic application
(2) SPSS description analysis and precautions for application of main data feature indicators
(3) SPSS mean value test, one-sample T test, independent sample T test and principle of variance analysis, and its application in understanding data characteristics
(4) Analysis of the relationship between SPSS correlation analysis and data
(5) SPSS regression analysis thoughts and modeling process considerations (mainly linear regression)
2, "What will happen" modeling complete process and SPSS related function application
Through the relevant functions of SPSS, the data is introduced into the complete process of deep modeling, and the law of occurrence of things is found from the data, so as to guide us to take corresponding measures.
(1) SPSS decision tree ideas and application in case, introduce the complete process of modeling: including SPSS-based data processing, model construction, model checking, model application
(2) Differences between decision trees and cluster analysis, briefly introduce the ideas of cluster analysis, the realization of SPSS, and the interpretation of results
3, "Why will happen" problem and SPSS related function application
Through the relevant functions of SPSS, the data is deeply modeled, and the reason for the occurrence of the event is found from the data, so as to guide us to take corresponding measures.
(1) Basic thinking and modeling of logistic regression of SPSS
4. Introduction to other algorithms
Brief description of basic ideas and application scenarios of principal component analysis, factor analysis, neural network, etc.
Note: Please bring your own computer to operate on the machine.
Class time: November 26, 2017
9:00-12:00 am, 1:30-4:30 pm
Study fee: free
Class location: Jinan
contact us
Phone: 010 82784677 62669215
Fax: 010 62981484
Email:
SPSS software QQ exchange group
SPSS previous training
2017 [August 14th to 15th] SPSS Statistics Software Application Training
2017 [April 26] Free Open Course of SPSS Modeler Software (Guangzhou)
2016 [November 26] Free Open Course for SPSS Software (Beijing)
2016 [May 28th] SPSS software free public class (Chongqing)
2016 [May 14th] SPSS software free public class (Harbin)
2016 [April 23] SPSS software free open class (Tianjin)
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