The correlations and network structure amongst individuals in datasets today—whether explicitly articulated, or deduced from biological or behavioral connections—pose new issues around privacy guarantees, because of inferences that can be made about one individual from another’s data. This motivates quantifying privacy in networked contexts in terms of ‘inferential privacy’—which measures the c...

The inferential reasoning account of causal learning holds that effortful reasoning processes underpin causal judgments. Evidence for this account comes from demonstrations that performance on cue competition tasks is affected by pretraining showing causal cues to be additive in their effects. If inferential reasoning underpins the additivity effect, then we might expect this effect to emerge d...

A think-aloud method was used to examine the content of information available to working memory during narrative comprehension in a CHI population. Twenty severe CHI participants (>1 year post-injury) and 20 controls talked aloud after they read each sentence of story narratives. Trabasso and Magliano's (1996a) verbal protocol analysis was then used to code for the production of inferential and...

The article investigates how 14to 15year-olds build informal conceptions of inferential statistics as they engage in a modelling process and build their own computer simulations with dynamic statistical software. This study proposes four primary phases of informal inferential reasoning for the students in the statistical modeling and simulation process. Findings show shifts in the conceptual st...

Informal inferential reasoning is a relatively recent concept in the research literature. Several research studies have defined this type of cognitive process in slightly different ways. In this paper, a working definition of informal inferential reasoning based on an analysis of the key aspects of statistical inference, and on research from educational psychology, science education, and mathem...

Valid, prior-free, and situation-specific probabilistic inference is desirable for serious uncertain inference, especially in bio-medical statistics. This chapter∗ introduces such an inferential system, called the Inferential Model (IM) framework, proposed recently. IMs do not require a prior to be specified, yet they produce probabilistic inferential results that have desireable frequency prop...

In a recent paper James Bogen and James Woodward denounce a set of views on confirmation that they collectively brand ‘IRS’. The supporters of these views cast confirmation in terms of Inferential Relations between observational and theoretical Sentences. Against IRS accounts of confirmation, Bogen and Woodward unveil two main objections: (a) inferential relations are not necessary to model con...