User:Jukeboksi/BBA studies/Toolkit for Quantitative Surveys: Difference between revisions

    From Consumerium development wiki R&D Wiki
    (adding teacher name, categories and course code)
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    Teacher: Jutta Heikkilä
    Teacher: Jutta Heikkilä


    Type of course: [[:Category:Free choice studies|Free choice studies]], [[:Category:toolbox courses|toolbox courses]] in [[:Category:stastical methods|stastical methods]]
    Type of course: [[:Category:Free choice studies|Free choice studies]], [[:Category:toolbox courses|toolbox courses]] in [[:Category:stastical methods|stastical methods]] and [[:Category:Quantitative research|Quantitative research]] ([[:Category:Intenstive week courses|Intenstive week courses]])


    Course code: MET8LF001
    Course code: MET8LF001
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    [[Category:Toolbox courses]]  
    [[Category:Toolbox courses]]  
    [[Category:Stastical methods]]
    [[Category:Stastical methods]]
    [[Category:Quantitative research]]
    [[Category:Intenstive week courses]]

    Revision as of 15:24, 23 January 2015

    Teacher: Jutta Heikkilä

    Type of course: Free choice studies, toolbox courses in stastical methods and Quantitative research (Intenstive week courses)

    Course code: MET8LF001



    • Statistical inference is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation. ( Wikipedia )
    • A crosstab is another name for a contingency table, which is a type of table created by crosstabulation. In survey research (e.g., polling, market research), a "crosstab" is any table showing summary statistics. Commonly, crosstabs in survey research are concatenations of multiple different tables. For example, the crosstab below combines multiple contingency tables and tables of averages. ( Wikipedia )
    • The Pearson product-moment correlation coefficient (sometimes referred to as the PPMCC or PCC, or Pearson's r) is a measure of the linear correlation (dependence) between two variables X and Y, giving a value between +1 and −1 inclusive, where 1 is total positive correlation, 0 is no correlation, and −1 is total negative correlation. It is widely used in the sciences as a measure of the degree of linear dependence between two variables. It was developed by Karl Pearson from a related idea introduced by Francis Galton in the 1880s.,