Customer's Perception Ratings of Problems Associated with Electricity Distribution in Kaduna, North-West Nigeria

Published: 29 April 2022| Version 1 | DOI: 10.17632/hsb6g4gwx5.1
Jonathan Tsetimi,


The dataset on problems with electricity generation in Nigeria from Kaduna state is the 4th in the series of data collected across the six political zones in Nigeria in a nationwide survey [1]. Datasets have already been published from the nationwide survey for south-south, south-west and southeast geo-political zones. [2,3,4] The Kaduna data consists of information from electricity customers on their perception as to the nature and extent of the problems facing the distribution sector especially as it relates to the services of distribution companies. The dataset is available in two different formats, i.e. IBM SPSS (database) and Microsoft Excel (Spreadsheet). The dataset contains 206 records each with each row corresponding to responses from a particular respondent to items in a questionnaire administered as the major means of data collection. The first row in the spreadsheet file is actually the header row. The files contain 49 variables(columns). The variable names and other variable parameters can be accessed in the variable view of SPSS. References 1. Tsetimi, J., Atonuje, A., & Mamadu, J. (2021). Survey Data on Problems with Electricity Distribution in Delta State, South-South, Nigeria. Journal of Advances in Mathematics and Computer Science, 36(1), 1-15. 2. Tsetimi, Jonathan (2020), “Customers' Problems with Electricity Distribution in Delta State Nigeria”, Mendeley Data, V1, doi: 10.17632/msrhyv489k.1 3. Tsetimi, Jonathan (2021), “Metropolitan Lagos Dataset on Customers' Perception Ratings of Problems Associated with Electricity Distribution”, Mendeley Data, V3, doi: 10.17632/jddmfmy7ry.3 4. Tsetimi, Jonathan (2022), “Customers’ Perception Data on Problems with Electricity Distribution in Anambra State, South-East Nigeria.”, Mendeley Data, V1, doi: 10.17632/9d4wmj7shc.1



Delta State University


Electricity, Data Analysis, Applied Computer Science, Database