Applied statistics (CPH: BD)

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Data collection 2

Literature

[A] Section 10.2.

Also look at R for Data Science. Especially chapter 5 (Data transformation), 11 (Data import) and 12 (Tidy data).

Lecture material

This lecture as: slideshow (html), Rmarkdown (Rmd), notes (pdf).

The entire module: notes (pdf).

Exercises

In any order (read about both before starting):

• PISA 2015
  1. Go to http://www.oecd.org/pisa/data/2015database/
  2. Download questionnaires in English (extract and delete all except CY6_QST_MS_SCQ_CBA_Final.pdf)
  3. Download SPSS School questionnaire data file data and extract
  4. Discuss the PISA study (in terms of sampling etc.), see the general site http://www.oecd.org/pisa/
  5. Make relevant analyses (e.g. plots, tables, statistical)
• Data for energy sectors (technical exercise practising R):
  1. Go to https://ens.dk/service/statistik-data-noegletal-og-kort/data-oversigt-over-energisektoren and download "Data for eksisterende og afmeldte møller"
  2. Load the data in R (use the sheet IkkeAfmeldte-Existing turbines, but maybe not the entire sheet, see range in ?readxl::read_xlsx)
  3. Get an impression of the data (format, variables, ..)
  4. Construct some relevant tables and plots
  5. Discuss the concepts of sample and population
  6. Restrict the dataset to Manufacture %in% c("Vestas Wind Systems A/S", "NEG Micon", "BONUS", "SIEMENS") (hint: tidyverse::filter())
  7. Do a descriptive analysis of Manufacture (Fabrikat) and Capacity (kW) (Kapacitet (kW)), e.g. tables and/or figures
  8. Assuming this is a random sample from a larger population, do a statistical analysis (e.g. are the population means of Capacity (kW) the same for each of the four manufactures?)
  9. Now include Rotor-diameter (m) and do a descriptive analysis
  10. Assuming this is a random sample from a larger population, do a statistical analysis

Afterwards, finish exercises from previous lectures.