Data Management, Analysis and Graphics with R in Nairobi, Kenya
Details
R is the language of big data—a statistical programming language that helps describe, mine and test relationships between large amounts of data. Learn how to Model statistical relationships using graphs, calculations, tests, and other analysis tools. Learn how to enter and modify data; create charts, scatter plots, and histograms; examine outliers; calculate correlations; and compute regressions, bivariate associations, and statistics for three or more variables.
- Trainees are expected to have a basic understanding of statistics.
- The 5 day training will be enough to get you comfortable with R Statistics.
How to register:
To register, send an email to: [email protected] You can also visit our website on www.opencastlabs-africa.com and fill an online application form and submit to us.
February 10th - 14th 2020
Register Online: https://cutt.ly/qrQh4G6
View Related Courses: http://opencastlabs-africa.com/data-collection-and-analysis/
Contact Details:
Rwanda:
P.O Box 4543 Kigali
3rd Floor La Bonne Address House
Avenue de la Revolution
Tel: Kigali +250 788 470 532
The Training Coordination Office (Joab/Diana)
Capacity Building Division
Argwings Kodhek Road, opposite YAYA Center
P.o Box 30225 – 00100 , Nairobi, Kenya
Tel: +254 0204409651 Mobile: +254 723870644
Email : [email protected]
Language
Participants should be reasonably proficient in English.
Fee Exceptions
All international participants will cater for their, travel expenses, visa application, insurance, accommodation and other personal expenses.
Accommodation
Accommodation is arranged upon request. For reservations contact us below.
Email: [email protected]
Payment:
Payment should be transferred through bank 5 days before commencement of training.
Cancellation policy
- All requests for cancellations must be received in writing.
- Changes will become effective on the date of written confirmation being received.
- The appropriate cancellation charge will apply
Outline
-
The preliminaries
- Installing R on your computer
- Using RStudio
- Familiarizing with the R interface
- R packages
- The built-in R datasets
- Manual data entry
- Importing data
- Converting tabular data to row data
- Colours and R
- TheColorbrewer
-
One Variable Charts
- Bar charts for categorical variables
- Pie charts for categorical variables
- Histograms for quantitative variables
- Box plots for quantitative variables
- Overlaying plots
- Saving images
-
One Variable Statistics
- Calculating frequencies
- Calculating descriptives
- Single proportion: Hypothesis test and confidence interval
- Single mean: Hypothesis test and confidence interval
- Single categorical variable: One sample chi-square test
- Examining robust statistics for univariate analyses
-
Data modification
- Examining outliers
- Transforming variables
- Computing composite variables
- Coding missing data
- Quiz
-
Working with the Data File
- Case selection
- Subgroup analysis
- Merging files
-
Charts for Associations
- Bar charts of group means
- Grouped box plots
- Scatter plots
-
Association statistics
- Correlation
- Computing a bivariate regression
- Comparing means with the t-test
- Comparing paired means- Paired t-test
- Comparing means with a one-factor ANOVA
- Comparing proportions
- Creating cross tabs for categorical variables
- Computing robust statistics for bivariate associations
-
Charts for Three or More Variables
- Clustered bar charts for means
- Scatter plots for grouped data
- Scatter plot matrices
- 3D scatter plots
-
Statistics for Three or More Variables
- Multiple regression
- Comparing means with a two-factor ANOVA
- Cluster analysis
- Conducting a principal components/factor analysis
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