This applies to the variables on family business, business category and effects of covid-19 on business. It does not matter what codes one uses because gender is a nominal variable and therefore there is no meaningful order in the codes used. The variable “gender” was coded 1 for male, and 2 for female. The codebook for the sample questionnaire is shown below:Īs seen in the image above, questions 1, 4, 5, 8, and 12 were not coded because of the nature of their data. Some variables do not need codes because they are left open for the respondent to fill. Lastly, in the fourth column insert the codes for each variable, where applicable. This is important for coding and data analysis. In column three, include the levels of measurement of the variables, that is, whether they are nominal, ordinal, interval or ratio. In the second column, insert the questions as they are in the questionnaire. In the first column, insert the names of the variables (the names in the first row of “data view”). To create the codebook, the researcher will open another sheet called “variable view” where all the codes for the responses will be generated. The sheet with the raw data is called the “data view.” Question 12: this is a ranking question where the respondent is asked to rank the four measures in order of their preference, from 1 (most preferred) to 4 (least preferred).Īfter specifying the variable names in the column headers, the researcher (or research assistants) will now add the raw data for each questionnaire in rows each questionnaire on its own row. Question 11: the responses take a yes/no form yes for the responses which are applicable to the respondent and no for the responses which are not applicable.
Questions 11 and 12 are a bit different from question 1-10 because of the responses provided is a variable on its own, hence each of them will have its own column. This is the first column and represents the unique number assigned to each filled questionnaire. The section below explains the variable names used for the sample questionnaire above. The latter (short form of the question) is preferred because it is easier for readers to know what the variable is about without referring back to the questionnaire.įor the sample questionnaire above, the column headers will look like this:Įach question represents a specific type of data and level of measurement, which determines how it is coded. For example, “what is your gender” can be entered as “gender” as the variable name. When writing the variable names, you can either use the question number or short form of the question.
It is therefore important to assign a unique identification number to each filled questionnaire before data entry begins. In Excel, the columns represent the variables, while the rows represent the observations (respondents to the questionnaire).
#Spss codebook download#
Sample-questionnaire Download Variable names The post will use a fictitious questionnaire (the sample questionnaire below) for the practical step-by-step instructions.
#Spss codebook how to#
This post is a demonstration of how to create a codebook in MS Excel. Excel is also a powerful tool for preliminary data analysis and data visualisation. The advantage of creating the codebook and entering the raw data into Excel before exporting to other programs is that it is easier to clean and manipulate data in Excel than it is in the other programs.
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