Advanced Statistical Analysis Using Statistical Package for Social Sciences SPSS

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13/05/2024-17/05/2024 Advanced Statistical Analysis Using Statistical Package for Social Sciences SPSS

Introduction

Statistical Package for the Social Sciences (SPSS) is designed for complex statistical data analysis in the social sciences. It facilitates thorough data management offering users significant control in organizing and managing data. The software excels in data screening and cleaning preventing accidental data deletion through its well-organized output window and data editor. This 5-day course aims to equip participants with advanced techniques for utilizing SPSS emphasizing its capabilities in statistical analysis data management and output organization to enhance participants' proficiency in leveraging the software for in-depth data analysis.

Duration

5 days

Target Participants

Researchers students anyone who interested in enhancing his/ her data analysis skills

Course Objectives

By the end of the training you will be able to:

• Understand both descriptive and inferential statistics
• Understand various data collection techniques and data processing methods
• Use basic functions and navigation within Stata and SPSS software
• Create and manipulate graphs and figures in SPSS software

 Topics

Module 1: Statistical Concepts

• Statistical Concepts
• Types of data
• Data Structures and Types of Variables
• Overview of SPSS
• Working with the SPSS software (file management editing functions viewing options)
• Output Management

 Module 2: Data Entry/Management

• Entering categorical and continuous data
• Defining and labeling variables
• Validation and Sorting variables
• Transforming recording and computing variables
• Restructuring data
• Merging files and restructuring
• Splitting files selecting cases  and weighing cases
• Syntax and output

 Module 3:

Statistical Inference and Descriptive Statistics

• Tests of Association
• Tests of Difference
• Hypothesis testing

 Measures of Variability and Central Tendency  

• Describing quantitative data
• Describing qualitative data

 Graphics in Data Analysis

• Graphing quantitative data
• Graphing qualitative data
• Advanced graphics options

 Correlation  

• Correlation of bivariate data
• Subgroup Correlations
• Scatterplots of Data by Subgroups
• Overlay Scatterplots

 Module 4: Test statistics

Comparing Means

• One Sample t-tests
• Paired Sample t-tests
• Independent Samples t-tests
• Comparing Means Using One-Way ANOVA 
• MANOVA: multivariate analysis of variance
• Repeated Measures ANOVA

 Tests of associations

• Goodness of Fit Chi Square All Categories Equal
• Goodness of Fit Chi Square Categories Unequal
• Chi Square for Contingency Tables
• Pearson Correlation
• Spearman Correlation

 Nonparametric Statistics 

• Mann-Whitney Test
• Wilcoxon’s Matched Pairs Signed-Ranks Test
• Kruskal-Wallis One-Way ANOVA
• Friedman’s Rank Test for k Related Samples

 Comparing Means Using Factorial ANOVA 

• Factorial ANOVA Using GLM Univariate
• Simple Effects

 Module 5:

Comparing Means Using Repeated Measures ANOVA 

• Using GLM Repeated Measures to Calculate Repeated Measures ANOVAs
• Multiple Comparisons

 Other topics

• Multiple Regression Analysis
• Logistic regression (Binary & Multinomial)
• Cluster Analysis
• Factor analysis

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Requirements

Participants should be reasonably proficient in English.  During the trainings participants should come with their own laptops.

Training Fee

The course fee covers the course tuition training materials two break refreshments lunch and study visits.

 Cancellation Policy

• All requests for cancellations must be received in writing.
• Changes will become effective on the date of written confirmation being received.

Host or Publisher fineresults research