Explanation : The analyst is using an ordinal scale which involves sorting data into
categories that are ordered with respect to some characteristic, such as the
firms’ market capitalization value. An example is Standard & Poor’s star
ratings for mutual funds. One star represents the group of mutual funds
with the worst performance. Similarly, groups with two, three, four and five
stars represent groups with increasingly better performance.
Nominal scales categorize data but do not rank them. An example would
be the classification of mutual funds according to the investment
strategy followed – growth fund, value fund, income fund, emerging
equity fund etc.
Interval scales not only rank data, but also ensure that the differences
between scale values are equal. The Celsius and Fahrenheit scales are
examples of such scales. However, these scales do not have a true zero.
Explanation : The steps involved in statistical inference include forecasting, making
estimates, or using a smaller group to make judgments about a larger
group. Description of important aspects comes under descriptive
statistics.
Explanation : The height of basketball players in a team is measured on a ratio scale
as it is possible to express the height in terms of a ratio. For example,
the height of player A is 1.2 times the height of player B, etc.
Explanation : A parameter describes the characteristic of a population while a sample
statistic describes the characteristic of a sample. A ‘population’ is defined
as all members of a specified group.
Explanation : A subset of a population is known as a sample. A ‘sample statistic’
describes the characteristic of a sample. A parameter describes the
characteristic of a population.