Course Date: 23rd – 27th, 2019 for 5 Days
Click to view course outline and register as individual or group to attend
Click to Download 2019 Course Calendar in PDF
Organizer: Foscore Development Center
Introduction
The training is essential in the development of better understanding of the concepts of statistics. It will provide the participants with a general idea of computer assisted data analysis. Additionally, the training will also focus on developing skills that are crucial to the transformation of data using SPSS.
Course Objective:
 Performing operations with data: define variables, recode variables, create dummy variables, select and weight cases, split files
 Building charts in SPSS: column charts, line charts, scatterplot charts, boxplot diagrams
 Performing the basic data analysis procedures: Frequencies, Descriptives, Explore, Means, Crosstabs
 Testing the hypothesis of normality
 Detecting the outliers in a data series
 Transform variables
 Performing the main onesample analyses: onesample t test, binomial test, chi square for goodness of fit
 Performing the tests of association: Pearson and Spearman correlation, partial correlation, chi square test for association, loglinear analysis
Duration
5 days
Who should attend?
The course targets project staff, researchers, managers, decision makers, and development practitioners who are responsible for projects and programs in an organization.
Course content
 Introduction
 Defining Variables
 Variable Recoding
 Dummy Variables
 Selecting Cases
 File Splitting
 Data Weighting
 Creating Charts in SPSS
 Column Charts
 Line Charts
 Scatterplot Charts
 Boxplot Diagrams
 Simple Analysis Techniques
 Frequencies Procedure
 Descriptive Procedure
 Explore Procedure
 Means Procedure
 Crosstabs Procedure
 Assumption Checking. Data Transformations
 Checking for Normality  Numerical Methods
 Checking for Normality  Graphical Methods
 Detecting Outliers  Graphical Methods
 Detecting Outliers  Numerical Methods
 Detecting Outliers  How to Handle the Outliers
 Data Transformations
 OneSample Tests
 OneSample T Test  Introduction
 OneSample T Test  Running the Procedure
 Introduction to Binomial Test
 Binomial Test with Weighted Data
 Chi Square for GoodnessofFit
 Chi Square for GoodnessofFit with Weighted Data
 Pearson Correlation  Introduction
 Pearson Correlation  Assumption Checking
 Pearson Correlation  Running the Procedure
 Spearman Correlation  Introduction
 Spearman Correlation  Running the Procedure
 Partial Correlation  Introduction
 Chi Square For Association
 Chi Square For Association with Weighted Data
 Loglinear Analysis  Introduction
 Loglinear Analysis  Hierarchical Loglinear Analysis
 Loglinear Analysis  General Loglinear Analysis
 Tests for Mean Difference
 IndependentSample T Test  Introduction
 IndependentSample T Test  Assumption Testing
 IndependentSample T Test  Results Interpretation
 PairedSample T Test  Introduction
 PairedSample T Test  Assumption Testing
 PairedSample T Test  Results Interpretation
 OneWay ANOVA  Introduction
 OneWay ANOVA  Assumption Testing
 OneWay ANOVA  F Test Results
 OneWay ANOVA  Multiple Comparisons
 TwoWay ANOVA  Introduction
 TwoWay ANOVA  Assumption Testing
 TwoWay ANOVA  Interaction Effect
 TwoWay ANOVA  Simple Main Effects
 ThreeWay ANOVA  Introduction
 ThreeWay ANOVA  Assumption Testing
 ThreeWay ANOVA  Third Order Interaction
 ThreeWay ANOVA  Simple Second Order Interaction
 ThreeWay ANOVA  Simple Main Effects
 ThreeWay ANOVA  Simple Comparisons
 Multivariate ANOVA  Introduction
 Multivariate ANOVA  Assumption Checking
 Multivariate ANOVA  Result Interpretation
 Analysis of Covariance (ANCOVA)  Introduction
 Analysis of Covariance (ANCOVA)  Assumption Checking
 Analysis of Covariance (ANCOVA)  Results Intepretation
 ANOVA  Introduction
 ANOVA  Assumption Checking
 ANOVA  Results Interpretation
 ANOVA  Introduction
 ANOVA  Assumption Checking
 ANOVA  Interaction
 ANOVA  Simple Main Effects
 Mixed ANOVA  Introduction
 Mixed ANOVA  Assumption Checking
 Mixed ANOVA  Interaction
 Mixed ANOVA  Simple Main Effects
 Predictive Techniques
 Simple Regression  Introduction
 Simple Regression  Assumption Checking
 Simple Regression  Results Interpretation
 Multiple Regression  Introduction
 Multiple Regression  Assumption Checking
 Multiple Regression  Results Interpretation
 Regression with Dummy Variables
 Sequential Regression
 Binomial Regression  Introduction
 Binomial Regression  Assumption Checking
 Binomial Regression  GoodnessofFit Indicators
 Binomial Regression  Coefficient Interpretation
 Binomial Regression  Classification Table
 Multinomial Regression  Introduction
 Multinomial Regression  Assumption Checking
 Multinomial Regression  GoodnessofFit Indicators
 Multinomial Regression  Coefficient Interpretation
 Multinomial Regression  Classification Table
 Ordinal Regression  Introduction
 Ordinal Regression  Assumption Testing
 Ordinal Regression  GoodnessofFit Indicators
 Ordinal Regression  Coefficient Interpretation
 Ordinal Regression  Classification Table
 Scaling Techniques
 Reliability Analysis
 Multidimensional Scaling  Introduction
 Multidimensional Scaling  PROXSCAL
 Data Reduction
 Principal Component Analysis  Introduction
 Principal Component Analysis  Running the Procedure
 Principal Component Analysis  Testing For Adequacy
 Principal Component Analysis  Obtaining a Final Solution
 Principal Component Analysis  Interpreting the Final Solutions
 Principal Component Analysis  Final Considerations
 Correspondence Analysis  Introduction
 Correspondence Analysis  Running the Procedure
 Correspondence Analysis  Results Interpretation
 Correspondence Analysis  Imposing Category Constraints
 Grouping Methods
 Cluster Analysis  Introduction
 Cluster Analysis  Hierarchical Cluster
 Discriminant Analysis  Introduction
 Discriminant Analysis  Simple DA
 Discriminant Analysis  Multiple DA
 Multiple Response Analysis
General Notes

All our courses can be Tailormade to participants needs

The participant must be conversant with English

Presentations are well guided, practical exercise, web based tutorials and group work. Our facilitators are expert with more than 10 years of experience.

Upon completion of training the participant will be issued with Foscore Development Center certificate (FDCK)

Training will be done at Foscore Development Center (FDCK) in Nairobi Kenya. We also offer more than five participants training at requested location within Kenya, more than ten participant within east Africa and more than twenty participant all over the world.

Course duration is flexible and the contents can be modified to fit any number of days.

The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and a Certificate of successful completion of Training. Participants will be responsible for their own travel expenses and arrangements, airport transfers, visa application dinners, health/accident insurance and other personal expenses.

Accommodation, pickup, freight booking and Visa processing arrangement, are done on request, at discounted prices.

One year free Consultation and Coaching provided after the course.

Register as a group of more than two and enjoy discount of (10% to 50%) plus free five hour adventure drive to the National game park.

Payment should be done two week before commence of the training, to FOSCORE DEVELOPMENT CENTER account, so as to enable us prepare better for you.

For any enquiry to: [email protected] or +254712260031

Website: www.fdck.org

Click to view Research and Data Analysis courses calendar 2019