1 / 11

Challenges for Data Analysis for Public Administrators

Challenges for Data Analysis for Public Administrators. Biruta Sloka University of Latvia Biruta.Sloka@lu.lv. Specialised training program “Data Analysis”.

shandi
Télécharger la présentation

Challenges for Data Analysis for Public Administrators

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Challenges for Data Analysis for Public Administrators Biruta Sloka University of Latvia Biruta.Sloka@lu.lv

  2. Specialised training program “Data Analysis” • School of Public Administration, Republic of Latvia has organised preparation of specialised training program “Data Analysis” and provision of training to employees in institutions of public administration • For development of requirements of the trainin program there were involved participants freom different institutions: Central Statictical Bureau of Republic of Latvia, Bank of Latvia and other institutions taking into account experience in realisation of such programs in other countries

  3. Planned trained persons and lengths for each level courses Planned trained persons were 608 persons (31 group), including: • 1) first level course 380 participants (19 groups) • 2) second level course 228 participants (12 groups) Number of participants in one training group around 20 (+/-5) persons Lengths for each level couses: • 1) for first level course 24 academic hours realised during 3 days • 2) for second level course 40 academic hours realised during 5 days

  4. Requirements Training was realised according the training aim to ensure improvement of knowledge in data analysis (including statistical analysis) that after the respective training in respective level course (first level or second level) participants could know certain amount of information/knowledge

  5. Requirements first level course participants (a) 1) understand aims of statistics 2) understand differences between qualitative and quantitative data and would know possible application of those data 3) understand conception of population and would know the advantages and dissadvantages of sampling method 4) understand differences between census data and survey data, and would know the advantages and dissadvantages of those methods 5) understand the advantages and dissadvantages of statistics 6) will be familiar with different kinds of data 7) could calculate basic indicators of central tendency or location and indicators of variability or dispersion

  6. Requirements first level course participants (b) 8) could perfoerm basic analysis of two and more variables 9) could select necessary indicators for analysis of problematic issues 10) could understand principles and methods of basic data analysis 11) could perform analysis with data bases in Latvia and international organisations 12) will understand principles of quality of statistics 13) will understand principles of questionnaire development 14) will know the most important requirements for graphical presentation of data 15) will know principles of statistical communication

  7. Requirements second level course participants 1) will know data analysis software principles and could perform basic activities with data analysis programs (it was wonderful to introduce for most of the participants SPSS) 2) will know basic of probability theory 3) will know statistical distributions 4) could apply practically basic principles of sampling theory 5) will know and could practically perform data analysis in the situation of non-response 6) could apply basic data imputauion methods 7) could develop basic regression models and analyse quality of those models 8) will know basics of time series analysis 9) will know basic methods of risk analysis

  8. Methods used for training • lectures • practical classes • disscussions • group work • presentations

  9. Used materials • For realisation of the courses it was widelly used materials of • Council of Statistics of Latvia available on webpage of Central Statistics Buruau of Latvia – in many situations course participants were very thankful for information availavle on CSB webpage • Materials from Readings of Association of Statisticians of Latvia was used also very often – including materials about census, quality of tatistics and about application of program R

  10. Materials for practical calculations For practical calculations there were used results of • Household Finance and Consumption Network conducted the Eurosystem's Household Finance and Consumption Survey (HFCS), which collects household-level data on households' finances and consumption • databases of Central Statistical Bureau of Latvia, data files (SPSS) of Household Surveys • SILC surveys • Employment Surveys It was nice that participants could use real data files and make their calculations and analysis

  11. Thank you for attention!

More Related