Statistics project involving different kinds of analysis and the use of SPSS. Interpretation of output
€6-12 EUR/tim
The project takes place on 03/09/2020 at 08:00 Netherlands(GMT+2) until 18:00 (GMT +2).
The project is a second year Communication Science Bachelor statistics project which involves the usage of SPSS. During the project a fictive data set needs to be analysed. Therefore it would useful if you are able to perform the following analysis and tasks:
- code nominal variables with more than 2 categories into dummy variables
- perform an ANOVA F-test of significance, using the BY keyword in SPSS UNIANOVA syntax
- interpret results of ANOVA F-tests of significance and can report them in APA-format
- identify moderation in research questions and theoretical models
- identify a possible interaction graphically for one dichotomous and one continuous variable
- interpret interaction terms in a linear regression equation and know how to compute predicted values for y with them
- report interaction results in APA style
- identify a possible interaction graphically for two categorical variables
- create a graph for an interaction effect based on predicted y value
- formulate null hypotheses regarding contrasts and can conduct planned comparisons for linear models with nominal variables with more than 2 categories as independent variables
- conduct post-hoc tests for linear models with nominal variables with more than 2 categories as independent variables and understand when these are appropriate
- formulate null hypotheses regarding contrasts and can conduct planned comparisons for 2x2 and 2x3 designs
- conduct post-hoc tests for 2x2 and 2x3 designs and understand when these are appropriate
- report the results of planned comparisons and post-hoc tests in APA format
- identify a pre-post intervention design and distinguish it from a between-group design
- name the units of analysis and the clustering variable for a given research design
- compute the Pearson correlation for observations in wide format and know it quantifies the extent of clustering
- pre-post intervention design data sets in long format
- perform a simple linear mixed model analysis for a pre-post intervention design
- interpret the output of a simple linear mixed model analysis for any within design (two levels), make predictions, calculate confidence intervals and do hypothesis testing & interpret the variance of the random effects
- report a simple linear mixed model analysis in APA form
- interpret and calculate intraclass correlations based on output
- recognize a mixed design: distinguishing within person (repeated measures) and between person variables (group variable or covariate).
Students can put mixed design data in long format
- perform a linear mixed model analysis on a mixed design data set with interaction effects
- interpret the output by making predictions, calculating confidence intervals and hypothesis testing
- interpret mixed design output: predicting values, calculate confidence intervals and hypothesis testing
- report mixed design analyses in APA format
- know that you can’t do a regression analysis when you want the dependent variable to be treated ordinally or when the model assumption of normally distributed residuals is not met
- choose, perform and interpret a Kruskall Wallis test for a nominal independent variable and an ordinal dependent variable, or when the model assumption of normally distributed residuals is not met
- choose, perform and interpret a rank order correlation for two ordinal variables (Spearman and Kendall)
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Feel free to ask any questions. If necessary I'll provide any materials that are needed.
Projekt-id: #24728285
About the project
26 frilansare har lagt bud på i genomsnitt €11/timme för det här jobbet
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