SPSS Statistics is a GUI and syntax based statistical analysis package with capabilities of Data management, Statistical analysis, Graphics, Simulations and Custom programming. SPSS Statistics is easy to use and you can start experiencing its productivity instantly. Using SPSS Statistics you can improve your business insight, reign over complex datasets, take rationale decision and ensure your business growth.
Contents of Training:
This course is designed for the data analysts, managers and other professionals who need to manage and take decision based on large amount data. At the end of course day, you will be capable of **
Managing large amount of data using SPSS Statistics;
Conduct descriptive and complex analysis on you data for taking research based decisions;
Create smart graphical presentation on system generated huge data file;
Reporting and sharing your data analysis findings and decisions with your peers and top level managers.
Introduction to SPSS and Questionnaire: Introduction to SPSS, Types of statistical data, variables and its types, Scale of measurement in SPSS, Creating a data file in SPSS, Using questionnaire to create data file in SPSS data editor window.
Data Management: Data Manipulation: (a) Inserting Variables (b) Inserting Case (c) Finding Cases/variables (d) Merging files : (i) Same variables under same name/different names (ii) different variables.
Data Manipulation: (a) Splitting File consist (i) group comparison (ii) organizing output by groups (b) Case selection © Selecting a random sample.
Data Transformation: Compute functions using Calculator Pad, Compute variable: if cases, Recoding values: (i) Recode into same variables (ii) different variables.
Computing descriptive statistics: Frequency distribution, Mean, Median, Mode, Quartile, Deciles and Percentiles, Measures of dispersion: (i) absolute measures of dispersion (II) Relative measures of dispersion.
Statistical graphs and Cross table: Pie Charts, Bar Charts, Histogram, Steam and Leaf plots, Line graph, Box Plots, Cross Table, Scatter plots.
Test of Hypothesis and Correlation analysis: One sample T test, Paired Samples T test, Independent Sample t- test, Chi Square test. Simple Correlation Coefficient (r), Bivariate correlation, Rank Correlation, Partial Correlation.
Regression analysis: Simple linear regression, Multiple linear regressions, Logistic regression.
Analysis of variance: One way ANOVA (LSD), ANOVA (RBD).
Non-Parametric Test: Chi square test, Wilcoxon sign rank test, Mann-Whitney U Test.