Basic statistical analysis and Friedman Test in SPSS : measuring expert agreement on STEM teacher competencies (Egypt 2022) / Hanaa Ouda Khadri.

Format:

Book

Author/Creator:

Khadri, Hanaa Ouda, author.

Language:

English

Subjects (All):

Science teachers--Rating of--Research--Egypt--Methodology.

Science teachers.

Statistics--Methodology.

Statistics.

Data sets.

Physical Description:

1 online resource

Place of Publication:

London : SAGE Publications Ltd, 2026.

Summary:

This dataset includes nonparametric protocols to assess the agreement across many correlating ordinal scales. The dataset itself contains expert panel ratings (Egypt, 2020) on some STEM competency domains that were rated on the same Likert scale. Using SPSS, you‘re going to address a critical issue: “Do experts really agree on what makes an effective STEM teacher?” The Friedman test identifies substantial differences among competencies, Kendall’s W quantifies the intensity of consensus, and post hoc comparisons identify the competencies that matter. You‘ll interpret effect sizes to convey what‘s genuinely important, construct summary tables that decision-makers can immediately understand, and develop straightforward visualizations for nontechnical audiences. This isn’t just about having skills in statistics; it’s really your toolkit to create research that will influence how thousands of STEM teachers are trained and supported. It will be informed by the reasons for the nonparametric tests with ordinal data, their assumptions, and common pitfalls: ties, missingness, and so forth. Students will generate a brief report identifying which domains enjoy relatively high agreement and where more work is required. The dataset file is accompanied by a teaching guide, a student guide, and a how-to guide.

Notes:

Description based on XML content.

ISBN:

9781036249533

OCLC:

1594889650

Publisher Number:

T302219