<s>[INST] context: Ordinal Repeat from All India 07, AIIMS May 2005, Nov. 2003 Statistical data can be of two types -Qualitative data -Quantitative data Qualitative Data In such data there is no notion of magnitude or size of the variables as they cannot be measured Variables can be categorized according to some characterstics or quality. eg: Sex, occupation marital status, education level, vaccinated or not vaccinated, acquired the disease or not, died or cured, grades in the class. The qualitative data can be placed on 2 scales - i) Nominal ii) Ordinal. Nominal scale - Nominal scale data are divided into qualitative categories or groups, such as male / female, black / white, died / cured, attacked / not attacked, vaccinated / not vaccinate, urban / sub urban / rural. - There is no implication of order or ratio, means that the data cannot be placed in a meaningful order. Ordinal Scale - Here the data can be placed into categories that can be rank ordered (eg. students may be ranked / 2nd / 3rd / 4th in their class or into grades A/B/C, the activity of an animal can be rated on a scale of 1 to 6, hardness scale for water etc.) However, there is no information about the size of the interval ie no conclusion can be drawn about whether the difference between the first and second students is the same as the difference between the second and third. Variables in the form of mild, moderate and severe (or very satisfied, satisfied and dissatisfied) are analyzed by ordinal scale as they can be arranged in a meaningful order but there is no information about the size of the interval between them. Quantitative data The quantitative data have a magnitude ie they can be measured. Eg. - height, weight, blood pressure, serum cholesteral level, temperature, number of children in a family etc. Quantitative data can be measured on 2 scales i) Interval ii) Ratio scales Interval scale - Interval scale data are like ordinal data in that they can be placed in a meaningful order; in addition, they have meaningful intervals between items, which can be measured. - eg: Temperature on the Celsius scale (the difference between 80 deg and 70 deg is the same as between 40 deg and 30deg) - However, interval scale data do not have an absolute zero, ratios of the scores are not meaningful ie 80deg C of Celsius temperature is not twice as hot as 40degC because 0degC does not indicate a complete absence of heat. Ratio Scale - A ratio scale has the same propeies as an interval scale, however, because it has an absolute zero, meaningful ratio do exist. - eg. weights, time, blood pressure, temperature on the Kelvin scale (not Celsius scale) On the Kelvin scale, zero degrees indicate an absolute absence of heat, just as a zero pulse indicates an absolute absence of heabeat. Thus we can say that 400 K is twice as hot as 200 K. Dichotomous Scale is a type of nominal scale in which nominal data fall into only two groups eg black / white, died / cured, failed / passed. [/INST] question: In a study following interpretation are obtained: Satisfied,Very satisfied,Dissatisfied. Which type of scale is this? | options: A: Nominal B: Ordinal C: Interval D: Ratio | answer: B </s>