AST 232 · Batch 31

Statistical Computing I

InstructorK.M. Tanvir
InstitutionISRT, University of Dhaka
LanguageR
FormatLab class, 15 meetings
Course is live, modules unlock as we progress
0 Available
9 Upcoming
9 Total
0 of 9 modules released

Block 1 · Demography in R

Module 1 Checking…

Basic Measures of Demography

Sex ratio, masculinity proportion, aged child ratio, child and old age dependency ratios, and constructing a population pyramid in R using realistic district level data.

⏱ Lab session Open lecture →
Module 2 Checking…

Fertility Measures

Crude Birth Rate, Monthly Birth Rate, General Fertility Rate, Age Specific Fertility Rate, Total Fertility Rate, Gross and Net Reproduction Rates, computed step by step in R on real Bangladesh data.

⏱ Lab session Open lecture →
Module 3 Checking…

Mortality Measures

Crude Death Rate, Age Specific Death Rate, completeness of registration adjustment, and direct standardisation in R for fair comparisons across populations.

⏱ Lab session Open lecture →
Module 4 Checking…

Life Table Construction

Complete and abridged life tables, the canonical columns from $l_x$ through $e_x$, and the Fergany method with a radix of 100,000, all built in R from age specific mortality rates.

⏱ Lab session Open lecture →
Exercise A Checking…

Exercise Class A, Demography Block

A graded practice round that mixes fertility, mortality, life tables, and dependency ratios on realistic Bangladesh and South Asia data, all solved in R.

⏱ Lab session Start exercises →

Block 2 · Design of Experiment in R

Module 5 Checking…

Completely Randomized Design (CRD)

The single factor fixed effects model in R, the ANOVA decomposition, the F test, model adequacy checks, Tukey HSD, and Bonferroni simultaneous intervals.

⏱ Lab session Open lecture →
Module 6 Checking…

Randomized Complete Block Design (RCBD)

Blocking one nuisance factor out, the RCBD ANOVA in R, treatment and block effect estimation, residual diagnostics, and deciding whether blocking helped.

⏱ Lab session Open lecture →
Module 7 Checking…

Latin Square Design (LSD)

Two nuisance factors handled in a p by p layout, the LSD ANOVA decomposition, the randomisation procedure, and when LSD is preferable to RCBD.

⏱ Lab session Open lecture →
Exercise B Checking…

Exercise Class B, Design of Experiment Block

A graded practice set covering CRD, RCBD, and Latin Square on agronomy, textile, and aquaculture style data, with the full R workflow from data to ANOVA to interpretation.

⏱ Lab session Start exercises →