Quantitative Methods MCQ - Quantitative Methods Section 1

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.

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.

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.

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.