**A) Context & Measures (*Sections 5.1 - 5.2*)** - **Data**: 01) **Raw data** - *CJ_00c raw CJ data Dots.RData* contains raw data of numerosity assessment - *Overview of 'CJ_00c raw CJ data Dots.RData'.pdf* describes the variables in the raw data file 02) **Data for analysis** - *01A DotsAnalysis12.RData* contains data used for analysis - *Overview of '01A DotsAnalysis12.RData'.pdf* describes the variables in the data for analysis - **Scripts** 01) **Preparation** includes the scripts that were used to - perform a general check (*01P Dots_gen_check.R*) - operationalize task exposure (*02P Dots_task_exp.R*) - estimate the relative quality of the objects (*03P Dots_est_qual.R*) - operationalize the three pair characteristics (*04P Dots_info_char.R*) - operationalize task difficulty (*05P Dots_task_dependent.R*) 02) **Outliers, distribution and subsetting** includes the scripts that were used to - check on outliers with regard to judgement time (*01ODS Dots_outliers.R*) - identify the distribution of judgement time (*02ODS Dots_JT_distribution.R*) - prepare the data for analysis (*03ODS Dots_data_prep.R*) 03) **Context & measures** includes the scripts that were used to - calculate the descriptive statistics reported in sections 5.1 and 5.2 (*01CM Dots_context_measures.R*) - create Figure 5.2 on the correlation during the assessment (*02CM Dots_plot_cor_dependents.R*) ---------- **B) Analyses** - **Judgement time** includes the scripts that were used to - model hypothesis 1 and select the best model(s) (*01A Dots_JT_H1.R*) - model hypothesis 2 and select the best model(s) (*02A Dots_JT_H2.R*) - model hypothesis 3 and select the best model(s) (*03A Dots_JT_H3.R*) - model hypothesis 4 and select the best model(s) (*04A Dots_JT_H4.R*) - model combinations of hypotheses 2-4 and select the best model(s) (*05A Dots_JT_H234.R*) - **Perceived task difficulty** includes the scripts that were used to - model hypothesis 1 and select the best model(s) (*01A Dots_PTD_H1.R*) - model hypothesis 2 and select the best model(s) (*02A Dots_PTD_H2.R*) - model hypothesis 3 and select the best model(s) (*03A Dots_PTD_H3.R*) - model hypothesis 4 and select the best model(s) (*04A Dots_PTD_H4.R*) - model combinations of hypotheses 2-4 and select the best model(s) (*05A Dots_PTD_H234.R*) - **Decision inaccuracy** includes the scripts that were used to - model hypothesis 1 and select the best model(s) (*01A Dots_DI_H1.R*) - model hypothesis 2 and select the best model(s) (*02A Dots_DI_H2.R*) - model hypothesis 3 and select the best model(s) (*03A Dots_DI_H3.R*) - model hypothesis 4 and select the best model(s) (*04A Dots_DI_H4.R*) - model combinations of hypotheses 2-4 and select the best model(s) (script *05A Dots_DI_H234.R*) ---------- **C) Results on *AIC* model selection (*Section 5.4*)** includes the scripts that were used to - summarize the results on *AIC* model selection (*01R Dots_summary_AIC.R*) - perform checks on multicollinearity and absolute fit of the selected models (reported in Tables 5.15 to 5.17) (*02R Dots_check_models.R*) ---------- **D) Evidence about hypotheses (*Sections 5.5 - 5.7*)** includes the scripts that were used to - create Tables 5.15 to 5.17 that summarize the parameters of the selected model(s) (*01E Dots_summary_models.R*) - create Figures 5.3, 5.4, 5.6, 5.7 and 5.10 on the relation of task exposure with the dependent variables (*02E Dots_H1_plots.R*) - create Figures 5.5, 5.8, 5.9, 5,11 and 5.12 on relation of pair characteristics with the dependent variables (*02E Dots_H234_plots.R*)