Factor Analysis Using the Principal Component (PCA) Method in SPSS With Data From CGAP Smallholder Household Survey (2016) / Mofoluke Akiode.

Format:

Book

Author/Creator:

Akiode, Mofoluke, author.

Language:

English

Subjects (All):

Exploratory factor analysis.

Physical Description:

1 online resource

Place of Publication:

London : SAGE Publications Ltd, 2025.

Summary:

This dataset explains and provides a step-by-step guide to Exploratory Factor Analysis (EFA) using the Principal Component (PCA) method. An EFA is an analytical method for finding and removing outliers, simplifying the data by keeping what is important, and extracting key information from it. EFA searches for evidence or clues within data during exploratory research. In this dataset, I explain the theoretical underpinnings and the process of carrying out EFA (PCA method) on secondary quantitative data from the Consultative Group to Assist the Poor (CGAP) Smallholder Household Survey. In the dataset, I provide a step-by-step tutorial on the analysis in IBM SPSS 29. The aim is to identify the principal components or factors that describe the smallholders' realities and entrepreneurial ecosystem support based on the patterns of responses of the smallholders. The dataset file is accompanied by a teaching guide, a student guide, and a how-to guide.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-03-621650-0

9781036216504

OCLC:

1523170952