Training Course on Data Management, Graphics and Statistical analysis using SPSS

SPSS is extensively applied in virtually every field including in government, business, and academia. It is a statistical analysis tool that allows any firm or individual to analyze huge chunks of data in order to understand it. The most common use of SPSS is to draw correlations between variables and to make statistically valid forecasts for future results.

Everything in our course is intended to making you a speedier and more casual SPSS user. Our courses are purposely pro-active including a lot of practical activities and examples to guarantee your proficiency in SPSS. We trust that product abilities that are created in practical situations are more profound than those created from classroom explanations. Our activities are precisely chosen to stress the key parts of every lesson.

Course Content

Module I: An overview of SPSS

a. Basic data quality checks

b. Basic Descriptive Statistics

c. Basic exploratory data analysis procedures

d. Basic statistical terms and concepts

e. Common inferential statistics

f. Concepts and Software for Data Processing

g. Creating and editing a data file

h. Data Processing using Surveys Processing Software (CsPro) and Census

i. Editing output

j. Frequently –used dialog boxes

k. Mouse and keyboard processing

l. Opening file and file extensions

m. Printing results

n. The core functions of inferential statistics

o. Use of Mobile Phones for Data Collection and Processing

Module II: Data Entry, management and Manipulation

a. Define and label variables

b. Enter categorical and continuous data

c. Exploring data Selecting and sorting cases

d. Help files

e. Merging files

f. Replacing missing values

g. Restructuring data

h. Syntax and output

i. Transform, recode and compute variables

j. Tabulations and Graphics

k. Creating and editing graphs and charts

l. Cross Tabulations

m. Frequency Tables

n. Graphing Qualitative data

o. Graphing Quantitative data

p. Stub and Banner Tables

Module III: Advanced Statistical Analysis

a. Correlation and simple linear regression

b. Data Reduction Methods

c. Introduction to Econometric Analysis

d. Introduction to estimation and hypothesis testing

e. Introduction to Longitudinal Analysis Using SPSS

f. Introduction to Time Series Analysis

g. One sample tests: sign, t-test, and signed rank tests

h. Quantitative Analysis using SPSS

i. Regression Analysis

j. Three or more samples

k. Two-sample tests: t-test, Mann-Whitney test