£1,150.00

Price for this course

2 HOURS

Duration

Classroom IBM

Delivery

Available dates


Mon14Dec 20 TO Tue15Dec 20

Where

Tech Data
The Capitol Building, Oldbury
Bracknell
RG12 8FZ

Code

TR-646370
Mon14Dec 20 TO Tue15Dec 20

Where

Tech Data ILO UK
Connection details will be communicated separately
Instructor Led
Online

Code

TR-646371
Mon14Dec 20 TO Tue15Dec 20

Where

Tech Data
2nd Floor, Broadwall House, 21 Broadwall Street
London
SE1 9PL

Code

TR-646372
Mon29Mar 21 TO Tue30Mar 21

Where

Tech Data ILO UK
Connection details will be communicated separately
Instructor Led
Online

Code

TR-664262
Mon28Jun 21 TO Tue29Jun 21

Where

Tech Data ILO UK
Connection details will be communicated separately
Instructor Led
Online

Code

TR-664263

Overview

This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases.

Audience

Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions.

Prerequisites

  • Experience with IBM SPSS Statistics (navigation through windows; using dialog boxes)
  • Knowledge of statistics, either by on the job experience, intermediate-level statistics oriented courses, or completion of the Statistical Analysis Using IBM SPSS Statistics (V25) course.

Objective

  • Introduction to advanced statistical analysis
  • Group variables: Factor Analysis and Principal Components Analysis
  • Group similar cases: Cluster Analysis
  • Predict categorical targets with Nearest Neighbor Analysis
  • Predict categorical targets with Discriminant Analysis
  • Predict categorical targets with Logistic Regression
  • Predict categorical targets with Decision Trees
  • Introduction to Survival Analysis
  • Introduction to Generalized Linear Models
  • Introduction to Linear Mixed Models

Course Outline

Introduction to advanced statistical analysis
• Taxonomy of models
• Overview of supervised models
• Overview of models to create natural groupings

Group variables: Factor Analysis and Principal Components Analysis
• Factor Analysis basics
• Principal Components basics
• Assumptions of Factor Analysis
• Key issues in Factor Analysis
• Improve the interpretability
• Use Factor and component scores

Group similar cases: Cluster Analysis
• Cluster Analysis basics
• Key issues in Cluster Analysis
• K-Means Cluster Analysis
• Assumptions of K-Means Cluster Analysis
• TwoStep Cluster Analysis
• Assumptions of TwoStep Cluster Analysis

Predict categorical targets with Nearest Neighbor Analysis
• Nearest Neighbor Analysis basics
• Key issues in Nearest Neighbor Analysis
• Assess model fit

Predict categorical targets with Discriminant Analysis
• Discriminant Analysis basics
• The Discriminant Analysis model
• Core concepts of Discriminant Analysis
• Classification of cases
• Assumptions of Discriminant Analysis
• Validate the solution

Predict categorical targets with Logistic Regression
• Binary Logistic Regression basics
• The Binary Logistic Regression model
• Multinomial Logistic Regression basics
• Assumptions of Logistic Regression procedures
• Testing hypotheses

Predict categorical targets with Decision Trees
• Decision Trees basics
• Validate the solution
• Explore CHAID
• Explore CRT
• Comparing Decision Trees methods

Introduction to Survival Analysis
• Survival Analysis basics
• Kaplan-Meier Analysis
• Assumptions of Kaplan-Meier Analysis
• Cox Regression
• Assumptions of Cox Regression

Introduction to Generalized Linear Models
• Generalized Linear Models basics
• Available distributions
• Available link functions

Introduction to Linear Mixed Models
• Linear Mixed Models basics
• Hierachical Linear Models
• Modeling strategy
• Assumptions of Linear Mixed Models



FAQs

What do I need to bring with me to my public class?

All required learning materials and equipment are provided in the classroom.

 

 

 

 

When do public training course fees have to be paid?

For public training classes payment must be received no later than three business days prior to the first day of class in order to remain in the class and confirm your seat. Failure to provide payment by this date may result in removal from the class, and/or late cancellation fees applied. You can submit payment in the form of a Purchase Order or credit card.

 

 

 

 

On-site (private) Course Pricing:

To find out more about On-site training e-mail us at enablement@agilesolutions.co.uk or call one of our offices.

 

 

 

 

What is the cancellation policy?

Requests for cancellations or date transfers need to be received at least ten (10) business days prior to the event start date in order to receive a full refund. If a cancellation or reschedule request is received less than ten (10) business days before the start date, the penalty of 100% of the cost of the course will be applied, resulting in no amount of the fee being refunded. Refunds will not be allowed for “no-shows” in our public training or IVA courses. This cancellation policy is strictly enforced.

 

 

 

 

What happens if Agile Solutions needs to cancel or reschedule a course?

Agile Solutions reserves the right to cancel events for any reason at any time. Cancellation liability for Agile Solutions, if Agile Solutions cancels the course, is limited to the return of course payment ONLY. Agile Solutions will not reimburse registrants for any other costs including but not limited to any travel cancellation fees or penalties, including airfare and hotel costs. PLEASE NOTE: If your registration status is either “Approved”, or “Pending Payment” you have not been confirmed for the class and it is recommended that you do not make any travel arrangements until you have received a confirmation e-mail letting you know the class and registration is confirmed.

 

 

 

 

How will I know if my course has been rescheduled?

Agile Solutions reserves the right to reschedule or cancel a course due to low enrollment or if necessitated by other circumstances. Agile Solutions will contact you via e-mail or phone to inform you of the change of schedule. Once you have been notified you may reschedule or receive a full credit. Agile Solutions shall not be liable for any other costs including but not limited to any non-refundable travel arrangements if a course is rescheduled or cancelled.