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Overview

The course is designed to provide students with transferable skills, to understand the uses of SPSS, as a tool to summarize and aid in the interpretation of research findings.

On completing this course students will:

  • be comfortable using SPSS as a data analysis tool
  • understand how to work with SPSS
  • understand how to learn to use new features of SPSS on their own
  • understand how to acquire information (samples)
  • understand how to enter and reorganize information within SPSS
  • understand how to effectively summarize research finds using SPSS
    • through the use of appropriate indexes and tables
  • be able to choose charts to successfully highlight their research results
  • be able to understand and interpret charts
  • understand the basic principles behind inferential statistics
  • be able to carry out inferential statistical analysis using SPSS
  • be able to integrate information and build models
  • be able to edit SPSS output
  • be able to use SPSS output to produce scientifically sound research reports

Course Content

  • Introduction to SPSS
  • Overview of SPSS for Windows
  • Navigating
  • Getting your data in
  • Import Data from Excel, CSV File
  • Importing Data from a Text File
  • Saving your work
  • The Data Editor
  • The Syntax Editor
  • The Output Viewer
  • Creating and Defining Variables
  • Inserting and Deleting Cases and Variables
  • Computing New Variables
  • Using Condition during computing variable
  • Recoding Variables
  • Sorting Cases
  • Selecting Cases
  • What is Syntax?
  • Basic Syntax Rules
  • Using Syntax
  • Comparing Drop-Down Menus versus Syntax
  • When should I use syntax?
  • Learning Syntax
  • Mean, Sum, Standard Deviation, Variance
  • Minimum Value, Maximum Value, and Range
  • Frequency distributions
  • Bar Diagram
  • Line Diagram
  • Scatter Plot
  • Leaf and Stem Diagram
  • Box Plot
  • Table Builder Interface
  • Stacking Variables
  • Nesting Variables
  • Layers
  • Stacking Categorical Variables
  • Stacking with Crosstabulation
  • Nesting Categorical Variables
  • Swapping Rows and Columns
  • Pearson Correlation
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a Bivariate Pearson Correlation
  • Example: Understanding the linear association between weight and height
  • Example: Predicting Job Performance from IQ
  • Scatterplot Performance with IQ
  • Pearson Correlation Performance with IQ
  • Linear Relation – General Formula
  • Prediction Formula for Performance
  • B Coefficient – Regression Slope
  • Regression Intercept (“Constant”)
  • Chi-Square Test
  • Application of Chi Square distribution
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a Chi-Square Test of Independence
  • Example: Chi-square Test for 3×2 Table
  • Example: Chi-square Test for 2×2 Table
  • One Sample t Test
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a One Sample t Test
  • Example
  • Paired Samples t Test
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a One Sample t Test
  • Example
  • Independent Samples t Test
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Levene’s Test for Equality of Variances
  • Test Statistic
  • Data Set-Up
  • Run an Independent Samples t Test
  • Example: Independent samples T test when variances are not equal
  • One-Way ANOVA
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a One-Way ANOVA
  • Example

About the instructor

DIPU MAHARJAN

BI Solution Architect

Hi I am Dipu Maharjan. I am working as BI Solution Architect. I have experience more than 10 years as Data Analyst, Database Programmer, Developer and Trainer.

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    Course Features

  • Course Duration30 hrs
  • Course coverageSPSS for Beginners and Intermediate