SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal

                         SPSS Training in Kathmandu Nepal @ Open Eyes IT Solution

In this course, you will learn about the principles and practice of data mining using the CRISP-DM methodology. The course structure follows the stages of a typical data-mining project, from collecting data, to data exploration, data transformation, and modeling to effective interpretation of the results. You will learn about modeling as well as the basics of how to read, prepare, and explore data with IBM SPSS Modeler.

SPSS Training in Kathmandu Nepal

1.Introduction to Data Mining

Two applications of data mining

Stages of the CRISP-DM process model

Successful data-mining projects and the reasons why projects fail

Skills needed for data mining

2.Working with IBM SPSS Modeler

MODELER user-interface

Work with nodes

Run a stream or a part of a stream

Open and save a stream

Use the online Help

SPSS Training in Kathmandu Nepal

3.Creating a Data-Mining Project

Basic framework of a data-mining project

Build a model

Deploy a model

4.Collecting Initial Data

Concepts "data structure", "unit of analysis", "field storage" and "field measurement level"

Import Microsoft Excel files

Import IBM SPSS Statistics files

Import text files

Import from databases

Export data to various formats

SPSS Training in Kathmandu Nepal

5.Understanding the Data

Audit the data

How to check for invalid values

Take action for invalid values

How to define blanks

SPSS Training in Kathmandu Nepal

6.Setting the Unit of Analysis

Set the unit of analysis by removing duplicate records

Set the unit of analysis by aggregating records

Set the unit of analysis by expanding a categorical field into a series of flag fields

SPSS Training in Kathmandu Nepal

7.Integrating Data

Integrate data by appending records from multiple datasets

Integrate data by merging fields from multiple datasets

Sample Records

8.Deriving and Reclassifying Fields

Use the Control Language for Expression Manipulation (CLEM)

Derive new fields

Reclassify field values

SPSS Training in Kathmandu Nepal

9.Identifying Relationships

Examine the relationship between two categorical fields

Examine the relationship between a categorical field and a continuous field

Examine the relationship between two continuous fields

SPSS Training in Kathmandu Nepal

10.Introduction to Modeling

List three modeling objectives

Use a classification model

Use a segmentation model

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal @ Open Eyes IT Solution

WHO SHOULD ATTEND?

Anyone with little or no experience of using SPSS for Windows. Especially useful for those new to using a statistical package for data analysis or to the Windows environment. Also recommended for those considering purchasing SPSS for Windows.

PREREQUISITES

Experience working in the Microsoft Windows environment and understanding of key Windows features. Experience with other Windows programs helpful. Experience with SPSS not necessary, though a basic understanding of purpose and functions of the software is helpful. No statistical background is necessary. 

SPSS Training in Kathmandu Nepal

COURSE OUTLINE

Overview

¦Windows

¦Designated Window versus Active Window

¦Status Bar

¦Dialog Boxes

¦Variable Names and Variable Labels in Dialog Box Lists

¦Resizing Dialog Boxes

¦Dialog Box Controls

SPSS Training in Kathmandu Nepal

¦Selecting Variables

¦Data Type, Measurement Level, and Variable List Icons

¦Getting Information about Variables in Dialog Boxes

¦Basic Steps in Data Analysis

¦Statistics Coach

¦Finding Out More

Getting Help

¦GettingHelp on Output Terms

Data Files

¦Opening Data Files

¦To Open Data Files

¦Data File Types

¦Opening File Options

¦Reading Excel 95 or Later Files

¦Reading Older Excel Files & Other Spreadsheets

¦Reading dBase Files

¦Reading Stata Files

¦Reading Database Files

¦Text Wizard

¦Reading Dimensions Data

¦File Information

SPSS Training in Kathmandu Nepal

¦Saving Data Files

¦To Save Modified Data Files

¦Saving Data Files in External Formats

¦Saving Data Files in Excel Format

¦Saving Data Files in SAS Format

¦Saving Data Files in Stata Format

¦Saving Subsets of Variables

¦Exporting to a Database

¦Exporting to Dimensions

¦Protecting Original Data

¦Virtual Active File

¦Creating a Data Cache

SPSS Training in Kathmandu Nepal

Data Editor

¦Data View

¦Variable View

¦To Display or Define Variable Attributes

¦Variable Names

¦Variable Measurement Level

¦Variable Type

¦Variable Labels

¦Value Labels

¦Inserting Line Breaks in Labels

¦Missing Values

¦Column Width

¦Variable Alignment

SPSS Training in Kathmandu Nepal

¦Applying Variable Definition Attributes to Multiple Variables

¦Custom Variable Attributes

¦Customizing Variable View

¦Spell Checking Variable and Value Labels

¦Entering Data

¦To Enter Numeric Data

¦To Enter Non-Numeric Data

¦To Use Value Labels for Data Entry

¦Data Value Restrictions in the Data Editor

¦Editing Data

¦Replacing or Modifying Data Values

¦Cutting, Copying, and Pasting Data Values

¦Inserting New Cases

¦Inserting New Variables

¦To Change Data Type

¦Finding Cases or Variables

¦Finding and Replacing Data and Attribute Values

¦Case Selection Status in the Data Editor

¦Data Editor Display Options

¦Data Editor Printing

¦To Print Data Editor Contents

Working with Multiple Data Sources

¦Basic Handling of Multiple Data Sources

¦Working with Multiple Datasets in Command Syntax

¦Copying and Pasting Information between Datasets

¦Renaming Datasets

SPSS Training in Kathmandu Nepal

¦Suppressing Multiple Datasets

Working with Output

¦Viewer

¦Showing and Hiding Results

¦Moving, Deleting, and Copying Output

¦Changing Initial Alignment

¦Changing Alignment of Output Items

¦Viewer Outline

¦Adding Items to the Viewer

¦Finding and Replacing Information in the Viewer

¦Copying Output into Other Applications

¦To Copy and Paste Output Items into Another Application

¦Export Output

¦HTML, Word/RTF, and Excel Options

¦PowerPoint Options

¦PDF Options

¦Text Options

¦Options for Exporting Charts

¦Viewer Printing

¦To Print Output and Charts

¦Print Preview

¦Page Attributes: Headers and Footers

¦Page Attributes: Options

¦Saving Output

¦To Save a Viewer Document

Working with Command Syntax

¦Syntax Rules

¦Pasting Syntax from Dialog Boxes

¦To Paste Syntax from Dialog Boxes

¦Copying Syntax from the Output Log

¦To Copy Syntax from the Output Log

¦To Run Command Syntax

¦Unicode Syntax Files

¦Multiple Execute Commands

Crosstabs

¦Crosstabs Layers

¦Crosstabs Clutered Bar Charts

¦Crosstabs Statistics

¦Crosstabs Cell Display

¦Crosstabs Table Format

SPSS Training in Kathmandu Nepal

Overview of the Chart Facility

¦Building and Editing a Chart

¦Building Charts

¦Editing Charts

¦Chart Definition Options

¦Adding and Editing Titles and Footnotes

¦Setting General Options

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal @ Open Eyes IT Solution.

In this course, you will learn about the principles and practice of data mining using the CRISP-DM methodology. The course structure follows the stages of a typical data-mining project, from collecting data, to data exploration, data transformation, and modeling to effective interpretation of the results. You will learn about modeling as well as the basics of how to read, prepare, and explore data with IBM SPSS Modeler. 

SPSS Training in Kathmandu Nepal

1.Introduction to Data Mining

• Two applications of data mining
• Stages of the CRISP-DM process model
• Successful data-mining projects and the reasons why projects fail
• Skills needed for data mining

SPSS Training in Kathmandu Nepal

2.Working with IBM SPSS Modeler

• MODELER user-interface
• Work with nodes
• Run a stream or a part of a stream
• Open and save a stream
• Use the online Help

3.Creating a Data-Mining Project

• Basic framework of a data-mining project
• Build a model
• Deploy a model

SPSS Training in Kathmandu Nepal

4.Collecting Initial Data

• Concepts "data structure", "unit of analysis", "field storage" and "field measurement level"
• Import Microsoft Excel files
• Import IBM SPSS Statistics files
• Import text files
• Import from databases
• Export data to various formats

SPSS Training in Kathmandu Nepal

5.Understanding the Data

• Audit the data
• How to check for invalid values
• Take action for invalid values
• How to define blanks

SPSS Training in Kathmandu Nepal

6.Setting the Unit of Analysis

• Set the unit of analysis by removing duplicate records
• Set the unit of analysis by aggregating records
• Set the unit of analysis by expanding a categorical field into a series of flag fields

7.Integrating Data

• Integrate data by appending records from multiple datasets
• Integrate data by merging fields from multiple datasets
• Sample Records

SPSS Training in Kathmandu Nepal

8.Deriving and Reclassifying Fields

• Use the Control Language for Expression Manipulation (CLEM
• Derive new fields
• Reclassify field values

9.Identifying Relationships

• Examine the relationship between two categorical fields
• Examine the relationship between a categorical field and a continuous field
• Examine the relationship between two continuous fields

SPSS Training in Kathmandu Nepal

10.Introduction to Modeling

• List three modeling objectives
• Use a classification model
• Use a segmentation model

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal  @ Open Eyes IT Solution.

 Introduction

SPSS COURSE Statistical Package for the Social Sciences (SPSS) is a comprehensive and flexible statistical analysis and data management solution produced by IBM and makes statistical data analysis straightforward. SPSS can take data from almost any type of file and use them to generate tabulated reports, charts, and plots of distributions and trends, descriptive statistics, and conduct complex statistical analyses

SPSS Training in Kathmandu Nepal

WHY THIS SPSS COURSE?

SPSS is a widely used program for statistical analysis in social science. SPSS is a powerful suite of data analytics, reporting and modeling software. It is the data analytics software package of choice for people who need to analyze large amounts of quantitative data and is used as standard by a wide range of users who need to quickly and accurately carry out statistical analysis of that data such as market researchers, health researchers, survey companies, government, education researchers, marketing organizations and data miners.

SPSS Training in Kathmandu Nepal

SPSS functionality ranges from simple plots and charts; through to much more sophisticated statistical tests. Although very broadly applicable, SPSS is very well-suited to analyzing survey data. It has a very broad range of applications from the relatively simple like calculating frequencies and creating lists and charts through to the far more advanced like variance analysis, multivariate statistical analysis and cluster analysis. It is also useful in building predictive models.

SPSS Training in Kathmandu Nepal

ABOUT THE COURSE:

This SPSS course will teach you the fundamentals of using SPSS. This SPSS course involves working on a number of practical, hands on examples and exercises in a workshop environment. Led by highly experienced SPSS trainers with many years of experience here at GOOLEE mean that our hands-on courses will leave you with lots of practical SPSS experience as well as useful tips and tricks. Our course will show you how to make the most of SPSS software package

COURSE GOAL:

The goal of the course is to increase knowledge and requisite skills of participants on the use of SPSS and to enable them make the most of this powerful software package while allowing them to work independently with SPSS on their own data and provide a solid foundation for advanced data analysis work.

SPSS Training in Kathmandu Nepal

OBJECTIVES OF THE COURSE:

To introduce participants to the basic practice of statistics by using SPSS Statistics, a statistical software program used for data management and data analysis and learn how to perform basic statistical analyses. v To introduce participants to the use of advanced SPSS for analyzing project data for reporting purposes focusing on database management tasks, descriptive statistics and graphics, and basic inferential statistics for comparisons and correlations.

SPSS Training in Kathmandu Nepal

1. Introduction

About SPSS

Defining Variables: Qualitative and Quantitative Variables

Brief Concept of Measurement of scale

Entering Data in the SPSS Spreadsheet

Importing and Exporting Data

Coding the Data

SPSS Training in Kathmandu Nepal

2.Data Management

Inserting and deleting cases and variables

Sorting cases

Select Cases with and without random sampling

Data Transformation

Computing New Variables

Re-Coding

3.Data Processing and Tabulation

Presentation and Tabulation of Data

Summarizing Data

Descriptive Statistics

4.Data Exploration

Box and Whisker plot

Histogram with Normality Plot

Stem and Leaf Plot

5.Graphical Presentation

Concept of Charts and diagrams

Simple, sub-divided, Multiple diagrams

Pie-Charts

Scatter/Dot Plots

Popularity Pyramid

SPSS Training in Kathmandu Nepal

6.Analysis I

Cross Tabulation for

Two Attributes

Three Attributes

7.Analysis II

Concept of Estimation and Hypothesis Testing

T-test for single Mean

Z-test for single Mean

T-test for Difference of Two Means

Z-test for Difference of Two Means

Paired t-test for single Means

One way ANOVA

POST-HOCK tests

WHAT YOU REQUIRE:

Interested organizations/institutions/individuals are expected to have laptop(s) while attending the workshop, and individuals attending should be from any discipline. Please feel free to bring your own datasets for practice while performing the tasks demonstrated by the trainer. If you have SPSS already installed on your machine the better. However it is not a must because you will be provided with a temporary version for the training.

 Further more details call us at: 977-9843617299, 977-1-4104372 and our mailing address: info@openeyesit.com.

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal @ Open Eyes IT Solution

Mastering SPSS is a comprehensive course for using SPSS. The course includes overviews of the interface and help section; editing, preparing, and transforming data; creating, handling, and transforming files; working with output and command syntax; performing a wide range of analysis techniques; creating charts and tables; customizing menus and toolbars; using the production and scripting facilities; and managing output 

SPSS Training in Kathmandu Nepal

Course Lessons:

Overview

Getting Help

Data Files

Distributed Analysis Mode

Data Editor

Working with Multiple Data Sources

Data Preparation

Data Transformations

File Handling and File Transformations

SPSS Training in Kathmandu Nepal

Working with Output

Pivot Tables

Working with Command Syntax

Frequencies

Descriptives

Explore

Crosstabs

Summarize

Means

OLAP Cubes

T Tests

SPSS Training in Kathmandu Nepal

One-Way ANOVA

GLM Univariate Analysis

Bivariate Correlations

Partial Correlations

Distances

Linear Regression

Ordinal Regression

Curve Estimation

SPSS Training in Kathmandu Nepal

Partial Least Squares Regression

Discriminant Analysis

Factor Analysis

Choosing a Procedure for Clustering

TwoStep Cluster Analysis

Hierarchical Cluster Analysis

K-Means Cluster Analysis

Nonparametric Tests

Multiple Response Analysis

Reporting Results

Reliability Analysis

Multidimensional Scaling

Ratio Statistics

ROC Curves

Overview of the Chart Facility

Utilities

SPSS Training in Kathmandu Nepal

Options

Customizing Menus and Toolbars

Production Jobs

Output Management System

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal @ Open Eyes IT Solution

Get up to speed in SPSS quickly and easily in this two-day course. The course guides you through the fundamentals of using SPSS for typical data analysis process. Learn the basics of read data, data definition, data modification, and data analysis and presentation of your results. See how easy it is to get your data into SPSS so that you can focus on analyzing the information. In addition to the fundamentals, learn shortcuts that will help you save time.

Anyone with little or no experience of using SPSS for Windows. Especially useful for those new to using a statistical package for data analysis or to the Windows environment. Also recommended for those considering purchasing SPSS for Windows.Experience working in the Microsoft Windows environment and understanding of key Windows features. Experience with other Windows programs helpful. Experience with SPSS not necessary, though a basic understanding of purpose and functions of the software is helpful.

SPSS Training in Kathmandu Nepal

No statistical background is necessary.Overview

Windows

Designated Window versus Active Window

Status Bar

Dialog Boxes

variable Names and Variable Labels in Dialog Box Lists

Resizing Dialog Boxes

Dialog Box Controls

Selecting Variables

Data Type, Measurement Level, and Variable List Icons

Getting Information about Variables in Dialog Boxes

Basic Steps in Data Analysis

Statistics Coach

Finding Out More

Getting Help

SPSS Training in Kathmandu Nepal

GettingHelp on Output Terms

Data Files

Opening Data Files

To Open Data Files

Data File Types

Opening File Options

Reading Excel 95 or Later Files

Reading Older Excel Files & Other Spreadsheets

Reading dBase Files

Reading Stata Files

Reading Database Files

Text Wizard

Reading Dimensions Data

File Information

Saving Data Files

To Save Modified Data Files

Saving Data Files in External Formats

Saving Data Files in Excel Format

Saving Data Files in SAS Format

Saving Data Files in Stata Format

Saving Subsets of Variables

Exporting to a Database

Exporting to Dimensions

Protecting Original Data

Virtual Active File

Creating a Data Cache

Data Editor

SPSS Training in Kathmandu Nepal

Data View

Variable View

To Display or Define Variable Attributes

Variable Names

Variable Measurement Level

Variable Type

Variable Labels

Value Labels

Inserting Line Breaks in Labels

Missing Values

Column Width

Variable Alignment

Applying Variable Definition Attributes to Multiple Variables

Custom Variable Attributes

Customizing Variable View

spell Checking Variable and Value Labels

Entering Data

To Enter Numeric Data

To Enter Non-Numeric Data

To Use Value Labels for Data Entry

Data Value Restrictions in the Data Editor

Editing Data

Replacing or Modifying Data Values

Cutting, Copying, and Pasting Data Values

Inserting New Cases

Inserting New Variables

To Change Data Type

Finding Cases or Variables

Finding and Replacing Data and Attribute Values

Case Selection Status in the Data Editor

Data Editor Display Options

Data Editor Printing

To Print Data Editor Contents

Working with Multiple Data Sources

SPSS Training in Kathmandu Nepal

Basic Handling of Multiple Data Sources

Working with Multiple Datasets in Command Syntax

Copying and Pasting Information between Datasets

Renaming Datasets

Suppressing Multiple Datasets

Working with Output

Viewer

Showing and Hiding Results

Moving, Deleting, and Copying Output

Changing Initial Alignment

Changing Alignment of Output Items

Viewer Outline

Adding Items to the Viewer

Finding and Replacing Information in the Viewer

Copying Output into Other Applications

To Copy and Paste Output Items into Another Application

Export Output

HTML, Word/RTF, and Excel Options

PowerPoint Options

PDF Options

Text Options

SPSS Training in Kathmandu Nepal

Options for Exporting Charts

Viewer Printing

To Print Output and Charts

Print Preview

Page Attributes: Headers and Footers

Page Attributes: Options

Saving Output

To Save a Viewer Document

Working with Command Syntax

SPSS Training in Kathmandu Nepal

Syntax Rules

Pasting Syntax from Dialog Boxes

To Paste Syntax from Dialog Boxes

Copying Syntax from the Output Log

To Copy Syntax from the Output Log

To Run Command Syntax

Unicode Syntax Files

Multiple Execute Commands

Crosstabs

SPSS Training in Kathmandu Nepal

Crosstabs Layers

Crosstabs Clutered Bar Charts

Crosstabs Statistics

Crosstabs Cell Display

Crosstabs Table Format

Overview of the Chart Facility

SPSS Training in Kathmandu Nepal

Building and Editing a Chart

Building Charts

Editing Charts

Chart Definition Options

Adding and Editing Titles and Footnotes

Setting General Options

 

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal

SPSS Training in Kathmandu Nepal @ Open Eyes IT Solution

 Workshop Goal and Objectives

The goal of these workshops is to introduce the SPSS and Sample Power applications to faculty, staff, and students with no knowledge or basic skill in SPSS. This workshop will teach participants the fundamental procedures that will allow them to continue by their own. After completing these workshops, participants will be able to:

SPSS Training in Kathmandu Nepal

• Describe the SPSS interface

• Enter and save data

• Import data from Excel

• Data preparation and exploratory data analysis

• Create charts, histograms, and box plots

• Transform variables

• Perform statistical analyses such as t-test, one-way ANOVA, simple and multiple linear regression,    Chi-squared, and logistic regression. Some of these tests will have the corresponding non-parametric  procedure.

• Carry out the power analysis for each of the Statistics tests mentioned above.

SPSS Training in Kathmandu Nepal

Workshop Description

IBM SPSS Statistics 24 is a comprehensive system for analyzing data. SPSS can take data from almost any type of file and use them to generate tabulated reports, charts, and plots o distributions and trends, descriptive statistics, and complex statistical analyses. SPSS makes statistical analysis more accessible for the beginner and more convenient for the experienced user. Simple menus and dialog box selections make it possible to perform complex analyses without typing a single line of command syntax. The Data Editor offers a simple and efficient spreadsheet-like facility for entering data and browsing the working data file.

SPSS Training in Kathmandu Nepal

This worshop has not been designed to teach Statistics. Participants should know basic and advanced Statistics in order to take these workshops. Some background material needs be covered in order to understand the analysis, but the theory behind each analysis will not be explained.

SPSS Training in Kathmandu Nepal

The traning methods will follow the classical training session composes of lecturing and hand-on activities, in which participants take the dynamic role of having attention, asking questions, and working on exercises. Class will be limited to 30 students, and we will meet for 3 hours in each workshop per week. We will have six workshops scheduled as explained in the next page.

SPSS Training in Kathmandu Nepal

Workshop Schedule

Data preparation and exploratory data analysis

•Getting familiar with the interface

•Importing data from Excel

•Data preparation and exploratory data analysis

•Plotting several types of charts

•Transforming variables

SPSS Training in Kathmandu Nepal

Inferential Statistics for the mean and the median

•Descriptive statistics for two or more variables

•Creating and editing charts for two or more variables

•Inferential statistics for the mean and the median

•One-sample t-test

•T-test and Mann-Whitney U Test

•Paired-difference t-test & Wilcoxon Signed-Rank Test

•Power Analysis for t-test

SPSS Training in Kathmandu Nepal

ANOVA and simple linear regression

•One-way ANOVA & Kruskal-Wallis Test

•Bivariate linear regression

•Power Analysis for ANOVA and simple linear regression

SPSS Training in Kathmandu Nepal

Multiple linear regression

•Multiple linear regression and correlation

•Model building and selection

•Interpreting regression coefficients and confidence intervals

•Quantifying and dealing with multicolinearity

•Power Analysis for multiple linear regression

SPSS Training in Kathmandu Nepal

Inferential statistics for the proportion

•Inferential statistics for categorical variables:

•One-sample binomial test

•One-sample Chi-square

•Chi-Squared Test of Independence

•Power Analysis for the proportion

Logistic regression

•Assumptions

•Estimating and interpreting regression coefficients and confidence intervals

•Maximum likelihood estimator and Wald statistics

•Modeling with categorical variables

•Power analysis for logistic regression