Base on your examples, all of them are ordinal. Use scale if it the difference between two measurement points matter or makes sense. In your examples, the point between "none" and "hardly at all" does not really matter right? But you are able to rank them where none could be lower than "hardly at all". So that's ordinal. Where you are concerned about the ranking. Use scale if there are meaningful interpretation of the points in between two measurement points. For example. If you are measuring distance where your scale is 1KM, 2KM, 3KM and the last point is 5KM. If the answer of most people falls 2.2KM, that 0.2 difference matters right? and it make sense and can easily be quantified. So that is a scale under interval. So goes for ratios (anything you can divide that means something. for example, speed. Definitely if you have a scale from minimum speed of 100km/h to maximum speed of 1000km/h, if the average of all your respondents falls503.5km/h, that is still quantifiable and can be measured within the scale. That is then a ratio which is a scale data type). And oh! One more tip, you can change in SPSS the data type in this order (if you want but the reverse is not true and shouldn't be followed coz it doesn't make mathematical sense) Scale -> Ordinal -> Nominal. (the other way around don't do!)

@Nicco Lopez Thank you so much sir for your answer

You should select the "Ordinal" data type in SPSS. Based on your example the data type should be numeric and the measurement should be ordinal. In an ordinal scale, data points are categorized into groups that have a distinct order.

I think you should select ordinal data.

You can set ordinal type variable for analysis in SPSS

In this scenario, you can treat ordinal data as a scale or you recode your data orderly to maintain the ordinal scale.

In the case of the above research question, it indicates a meaningful order, but the differences between the categories might not be uniform. In that case, you should treat the variable as ordinal data and apply an appropriate non-parametric test.

I hope this will be helpful.

I think ordinal data thanks

1,2,3,2

You have ordinal measurement in the suggested answers. So, you have to choose this format. In an ordinal scale, data points are categorized into groups that have a distinct order, just like your examples.

thanks your answer You're right, but the questions asked were only selected as rankings, there is no degree. Cannot be weighted