Learn about data cleaning, data imputation, and data summary in SPSS with data from the COVID-19 Pandemic School Closure Crisis Study (2020) / Ximena P. Suarez-Sousa, Boyd L. Bradbury.

Format:

Book

Author/Creator:

Suarez-Sousa, Ximena P., 1968- author.

Bradbury, Boyd L., author.

Language:

English

Subjects (All):

SPSS (Computer file)--Case studies.

SPSS (Computer file).

Data sets--Case studies.

Data sets.

COVID-19 Pandemic, 2020-2023--Research--Case studies.

COVID-19 Pandemic, 2020-2023.

Physical Description:

1 online resource : illustrations

Other Title:

Learn about data cleaning, data imputation, and data summary in Statistical Package for the Social Sciencs with data from the COVID-19 Pandemic School Closure Crisis Study (2020)

Place of Publication:

London : SAGE Publications Ltd, 2026.

Summary:

This dataset is designed to teach readers how to conduct data cleaning, how to impute missing data following descriptive techniques, and how to summarize and visualize data using descriptive statistics. The dataset is a subset of data collected from K-12 teachers during the COVID-19 pandemic. The dataset contains respondents' personal (e.g., age, highest degree earned) and professional demographic information (e.g., teaching position), as well as school closure teaching practices and measures of personal and professional challenges to help educational administrators triage groups in need of most immediate support. The dataset file is accompanied by a teaching guide, a student guide and how-to guide.

Notes:

Description based on XML content.

ISBN:

1-03-624204-8

9781036242046

OCLC:

1568964765

Publisher Number:

T300600