Students

Data set collected in 2022 that contains 10 variables recorded on a convenience sample of 253 students enrolled in the first year at the University od Naples FedericoII and attending an introductory Statistics course.

Probabilistic distance clustering (PD-clustering) is an iterative, distribution free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership, under the constraint that the product of the probability and the distance of each point to any cluster centre is a constant. PD-clustering is a flexible method that can be used with non-spherical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different size. GPDC and TPDC uses a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high dimensional data sets.

Cristina Tortora

FPDclustering

PD-Clustering and Related Methods

Students function

A data frame with 253 observations and 10 variable.<dl>
<dt>Sex</dt>
<dd>gender, binary</dd><dt>HS_qual</dt>
<dd>high school type, categorical</dd><dt>Stud_stat</dt>
<dd>prior knowladge of statistics, binary</dd><dt>Course_modality</dt>
<dd>course modality of attendance (in presence, online, mixed), categorical</dd><dt>HE_Parents</dt>
<dd>parents' education degree, categorical</dd><dt>PMP</dt>
<dd>mathematical prerequisits for psychometric, continuous</dd><dt>SAS</dt>
<dd>statistical anxiety sale, continuous</dd><dt>RAI</dt>
<dd>relative authonomy index, continuous</dd><dt>S_EFF</dt>
<dd>self-efficacy, continuous</dd><dt>COG</dt>
<dd>cognitive competence, continuous</dd>
</dl>

Format

Statistics 1 students 
 — Students

A data frame with 253 observations and 10 variable.<dl>
<dt>Sex</dt>
<dd>gender, binary</dd>

<dt>HS_qual</dt>
<dd>high school type, categorical</dd>

<dt>Stud_stat</dt>
<dd>prior knowladge of statistics, binary</dd>

<dt>Course_modality</dt>
<dd>course modality of attendance (in presence, online, mixed), categorical</dd>

<dt>HE_Parents</dt>
<dd>parents' education degree, categorical</dd>

<dt>PMP</dt>
<dd>mathematical prerequisits for psychometric, continuous</dd>

<dt>SAS</dt>
<dd>statistical anxiety sale, continuous</dd>

<dt>RAI</dt>
<dd>relative authonomy index, continuous</dd>

<dt>S_EFF</dt>
<dd>self-efficacy, continuous</dd>

<dt>COG</dt>
<dd>cognitive competence, continuous</dd>


</dl>

Students: Statistics 1 students

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Examples