1 / 18

Statistical Techniques for Specific Problems of Analysis

9:37 PM. Levels of statistical analysis. Statistics are either descriptive or inferrential,from simple to complexDescriptives include frequency distributions, means, medians, standard deviations, standard error, indicators of departurefrom normality (skewness, kurtosis),proportions (percentage

monita
Download Presentation

Statistical Techniques for Specific Problems of Analysis

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. 4:47 AM Statistical Techniques for Specific Problems of Analysis

    2. 4:47 AM Levels of statistical analysis

    3. 4:47 AM Three general categories of analysis are used depending on the stage of analysis and nature of the question

    4. 4:47 AM

    5. 4:47 AM

    6. 4:47 AM

    7. 4:47 AM

    8. 4:47 AM

    9. 4:47 AM

    10. 4:47 AM

    11. 4:47 AM

    12. 4:47 AM

    13. 4:47 AM Multivariate statistical techniques can be divided into four general types of analytic problems Problems that require evaluation of the associations among two or more variables. In univariate or bivariate cases, these include bivariate correlation (r), simple regression (R) and chi square (?2). Multivariate cases include canonical R, multiple R, sequential R, and multiway frequency analysis (fancy chi square). When the problem calls for testing the significance of group mean score differences. In univariate or bivariate analysis, these include t test and one-way analysis of variance. Multivariate techniques include factorial ANOVA and various forms of multiple analysis of variance (MANOVA) and analysis of covariance (ANCOVA & MANCOVA).

    14. 4:47 AM When the question calls for predicting group membership; e.g., what combination of variables separate republicans, democrats, and independents from one another? In the two group case, we use logistic regression or two-group discriminant function analysis. More than two groups employ multiple discriminant analysis. When the problem is to discern the latent structure underlying a set of variables. Coping with stress may have underlying structures like escape vs confrontation or social distance vs social contact. Principal components analysis (PCA) and factor analysis (FA) assess how variables group together to form latent structures. A more complex form is structural equation modeling.

    15. 4:47 AM

    16. 4:47 AM

    17. 4:47 AM

    18. 4:47 AM

    19. 4:47 AM

More Related