FAQs

Data preparation

1. How to code multiple response items?

You should create one variable for each option and use 1 or 0 to denote whether the option is chosen or not. For example, if there are three options (A, B, C) under Q5, you can create the variables Q5.A, Q5.B, Q5.C. If someone answers A and C, then you can put Q5.A=1, Q5.B=0, and Q5.C=1. (For simplicity, you can also ignore the 0 and leave it as missing.) After that, you can group the variables and analyze the frequency distribution. See: https://www.dummies.com/education/math/statistics/creating-and-using-a-multiple-response-set-in-spss/ for details.

2. How to code ranked items?

Ranked items can be coded in a similar way as multiple response items except that you put down the ranks (e.g. 1, 2, 3, 4…) instead of whether it is selected or not (1, 0) as the data. Alternatively, you can use one variable for each rank and put down the option in that rank. For example, if the data under Q4 is A, C, B, D then you can create four variables Q4.1, Q4.2, Q4.3, Q4.4 and put A, C, B, D in them respectively.

3. How to code open-ended items?

Open-ended items can be entered as is. Just remember to use string as variable type, and make sure that the width of the string is long enough to hold your data.

4. How to detect and fix abnormalities in the data?

Try using Data -> Validation to quickly check the distribution and range of the data. You can also define rules for SPSS to do the checking. You may also check whether there are strange-looking data, e.g., the same option is chosen in all the items. This probably implies that the respondent was not giving their true responses.

5. Shall I delete the cases with missing data?

Usually not. SPSS is good at handling missing data and for most cases it will ignore the missing data in the analysis. However, in some occasions it may be better off discarding all the incomplete cases (cases with missing data). For example, if most of the answers in the case are missing, then the other answers may not be reliable neither.

6. How to import data from Google Form into SPSS?

You can download your data in CSV format directly from your Google Form, or you can create a spreadsheet from it and then download the spreadsheet as Excel format. In either way, you can import the file into SPSS after download.

7. What should I do if SPSS says the worksheet is empty when I import data from Excel?

This is usually caused by illegal characters (often Chinese characters in non-UTF-8 encoding scheme), or other problems in the Excel file. In that case, try CSV instead. If that does not resolve the problem, try to copy the paste the data from Excel. The shortcoming is that it does not copy the variable names and you have to input the variable names one by one.

8. What should I do if the Chinese characters are not shown properly on import into SPSS?

This is usually due to non-UTF-8 encoding in Chinese characters. You can open the data file in Excel and then save it as another file while changing the character encoding setting (under web options in the save dialogue box) to UTF-8 when you save.

Alternatively, you can tell SPSS to read those non-UTF-8 encoded characters. To do so, close all your data sets and restart SPSS. Then, with an empty data set, choose Edit -> Options -> General -> Language and then change the Locale setting in the Locals's writing system section.

9. What level of measurement should I use for Likert scale data?

Likert scale is ordinal level although some people regard it as scale level.

10. Should I use string or numeric when coding nominal and ordinal data?

Numeric is more desirable. First, you don’t have to worry about mis-spelling if you input your data by hand. Second, some procedures (e.g. ANOVA) requires that the grouping variable be numeric.

11. How to recode string data to numeric?

First, use either Automatic Recode or Recode into Same Variables or Recode into Different Variables to recode the data. Then, in the variable view, change the variable type from string to numeric. (Warning: Do not reverse the order of these two steps. If you change the variable type to numeric first, SPSS will convert all your string data to missing. You will end up losing your data!)

12. How can I regroup some of the categories in categorial data (ordinal or nominal)?

You can use recode. For example, if your original data have three categories: 1, 2, 3, and you want to combine 2 and 3 into a new group, then you can use Transform -> Recode into Same Variables to recode 1 to 1 (1->1) and then 2 and 3 to 2 (2->2, 3->2). The new variable will then contain the regrouped categories.

13. Shall I remove the cases that are screened out by my screening questions?

I would suggest keeping them in the data set so that at least you know how many of the cases are screened out. To skip these cases in your analysis, you can use Data -> Select cases to select only the cases you want to analyze.

14. What is the actual difference between nominal and ordinal data in SPSS?

Ordinal data have ordered categories, which is essential if you want SPSS to follow a particular order when displaying these data in tables and charts. If you set ordinal data as nominal, SPSS may get the ordering wrong.

Data analysis

1. What kind of data analysis can I do?

It depends on the levels of measurement of your data.

Scale data:

Descriptive statistics: Mean, standard deviation, histogram, correlation, regression, etc.
Inferential statistics: t-test, ANOVA, etc.

Ordinal data (e.g. Likert scale):

Descriptive statistics: Median, frequency table, bar chart, etc.
Inferential statistics: non-parametric tests

For scale and ordinal data, you can either analyze all the cases as a whole, or (most often) you can also do some cross-comparisons. e.g.,

Independent samples: Compare your data across demographic grouping variables (e.g. gender, income range, academic level).
Paired / dependent samples: Compare your data across two different items obtained from the same respondents (e.g. pre-test vs. post-test).

Nominal data:

Descriptive statistics: frequency table, cross-tabulation, bar chart, etc.
Inferential statistics: chi-square test, etc.

Qualitative data (e.g. open-ended comments):

Thematic analysis, discourse analysis, etc.

2. How to compare data by groups?

Use Data -> Split File to split the variables by grouping variables. All the analysis from this point on will be conducted separately to each group.

3. What can I do with Likert scale data?

Likert scale is ordinal level. You can analyze its frequency distribution, draw bar charts, find the median, or conduct non-parametric tests. Just remember to avoid mean, standard deviation, t-test, ANOVA, etc. or other analyses specifically for scale level data.

4. Why can’t I use Ordinal Level in Non-Parametric Tests in SPSS?

Although Likert Scale is ordinal level, if you set it to ordinal level in SPSS then some non-parametric tests will not work. This is due to some programming consideration not to be detailed here. In short, if you need to conduct these non-parametric tests to your Likert scale data, you need to set the variables to scale level even though they are ordinal.

5. Why can’t I use ANOVA when the grouping variable is a string?

The ANOVA procedure in SPSS requires a numeric grouping variable. You can recode your data using the suggestions given above.

6. How can I keep good track of my outputs?

You can rename your output in the left pane of your output window. Also remove the outputs that you do not want.

7. How do I make a scatter plot of Likert scale data?

You can use the Graph Builder for scatter plot. However, unless you have a strong reason to do so (e.g. to do what the literature suggests), you should not plot Likert scale data in a scatter plot.

8. How do I find the mean of some variables?

If you have variables X1, X2, X3 and you want to find their mean, you can click Transform -> Compute Variable and then input the formula MEAN(X1,X2,X3) in the Numeric Expression box. See here for details: https://libguides.library.kent.edu/spss/computevariables.

Note: You can do other calculations on the variables in a similar manner. e.g. To find the sum between X1 and X2 you can input X1+X2 instead.

Data reporting

1. How can I export my tables and charts to MS Word?

You can simply copy and paste your tables and charts into MS Word. Just be reminded that charts cannot be edited once they are pasted into Word, so you need to do all the editing (e.g. change the bar colors, fonts, etc.) in SPSS before exporting.

2. How to report demographic data?

It is a norm to use one single big table to list the demographic statistics. Include usually the frequency table with count and percentage for each item. Also include a total in the last row to represent the total sample size.

3. What should I do if there are too many graphs to plot?

You don’t have to report everything in your data, at least not directly. You can consider aggregating your data in some way, or in case you need to report the frequency distribution of a large number of variables, consider a frequency table instead of a histogram / bar chart.

4. How should I report the results of hypothesis tests?

Report the null and alternative hypothesis, the test you use, and p-value, and the decision (e.g. retain or reject). Then write a paragraph to explain the meaning and implications of this decision with respect to your particular research question.

5. How should I report open-ended answers?

You can list the open-ended responses one by one in a table and then write a few paragraphs to interpret the meaning of these data.

Optionally, you can also code these responses by tags. e.g. If someone responds "Very good" and another one says "Very nice", you can group them together as "Positive feedbacks" since they essentially mean the same thing although written differently. You can then count the frequency of each tag, then sort them by descending order of frequency in a table. This helps to show what kind of comments are the most frequently mentioned.

6. What should I put in my discussion section?

Focus on the following:

The results that verify your theoretical assumptions;
The results that answer your research questions;
(More importantly) the unexpected results, which appear to contradict with literature or your theoretical assumptions. Contradiction is a good thing in research because it is often where new knowledge is found. Try to explain the discrepancy. e.g.
- Is the theory wrong?
- Is the context your study different from the ones used in literature?
- Is there any limitation in your research design?

Miscellaneous Questions

1. Where can I download SPSS for use at home?

SPSS is a proprietary software and you need to pay to use it.

However, you can apply for a 14-day free trial at https://www.ibm.com/hk-en/analytics/spss-trials.