This course reviews and expands upon core topics statistics through the study and practice of data analysis. Topics include numerical and graphical summaries of data, counts and tables, analysis of variance, regression. Upon completion of this course, students should be able to think critically about data and apply standard statistical inference procedures to draw conclusions from such analyses. This course will be computationally, not mathematically, intensive and will use the R language and environment for statistical computing and graphics.
Unpaid
1. Installation of R- Software, Basic of Calculator, functions, data entry, missing data, matrix operators.
2. Data management with repeated ,sorting, ordering and list
3. Calculation of measures of central tendency and dispersion
4. Graphs and diagrams
5. Correlation and regression analysis
6. Time series analysis
6 weeks (2 lectures per week)
Assignment after every topic.
Examination after completion of course.