Answer:
1. Nominal Scale; 2. Ordinal Scale; 3. Ordinal Scale; 4. Nominal Scale.
Step-by-step explanation:
<h3>Q1 and Q4</h3>
The variable in Question 1 (Q1)<em> </em>could be described as <em>The</em> <em>attributes of the restaurant, </em>with possible values<em>: </em>service, prices, quality of food, menu options (four values).
The variable in Question 4 (Q4) could be mentioned as <em>Eaten before in the restaurant</em>, with possible values: yes or not (two values).
These values are, in fact, simply names, and although they can be represented using numbers, they have no numerical meaning at all.
For instance, the values in Q1 can be labeled by 0 (service), 1 (prices), 2 (quality of food), 3 (menu options) and 0 (not) or 1 (yes), in Q4; for purposes of data analysis, 3 (menu options) is a label and does not mean a higher score than 1 or 0. <em>These numbers are labels rather than meaningful numbers</em>, and this is a characteristic of the Nominal Scale of measurement. Then, the possible response for questions Q1 and Q4 is the Nominal Scale.
<h3>Q2 and Q3</h3>
The variable in Q2 is the <em>Rating of the restaurant</em>, with possible values: excellent, good, fair, poor.
The variable in Q3 is <em>Prices, </em>with possible values: high, average, low.
As can be seen, any possible value in either question, like excellent or high, has a greater value than fair or low, respectively. In other words, they have different values concerning others, but we do not the <em>distance</em> among them. <em>High</em> is greater than <em>Average</em>, and the latter is greater than the <em>Poor </em>value, but we do not know what distance separates one value from the other, and this is a characteristic of the Ordinal Scale of measurement. Thus, the possible response for questions Q2 and Q3 is the <em>Ordinal Scale</em>.
