Essential Statistical Terms for Business Analytics Quiz

In data analysis and statistics, a characteristic or property that can change or vary is referred to as a variable. While the incorrect answers are related to characteristics as well, they do not specifically address the concept of variability in the context of elements.

In this scenario, the data can be ranked but the differences between the ranks do not have a consistent unit of measure, making it ordinal scale of measurement.

Gender is typically considered a categorical value as it represents distinct categories or groups (male, female, other) without any inherent order or numerical value attached to them.

Temperature is a quantitative variable because it represents a measurable amount on a scale. Categorical, qualitative, and ordinal variables involve non-numeric data that can't be measured in the same way as temperature.

Profits of Fortune 500 companies can be measured and expressed as numerical values, making it an example of quantitative data. Qualitative data refers to descriptive information that cannot be quantified. Categorical data groups observations into categories. Ordinal data is a type of categorical data that has an order or rank.

Nominal data is used to label variables without any quantitative value.

In the context of ordinal data, the rank or order of the data points is important, rather than the actual numeric values, alphabetical order, or frequency of occurrence.

An interval in terms of data refers to a numeric data type with a fixed unit of measure, making it suitable for mathematical operations. It is not a textual representation, does not have a variable unit of measure, and is different from categorical data which represents distinct categories.

In statistics, the population refers to the complete set of individuals or items that the researcher is interested in studying. It is important to distinguish between population and sample, as the sample is a subset of the population.

A census involves gathering information from every individual in a population, as opposed to sampling which involves selecting a subset of the population. Surveys may only capture information from a portion of the population. Estimation involves making an educated guess or approximation, rather than collecting data from all elements in a population.

A sample survey involves collecting data from a portion of a population to draw conclusions about the entire population.

The term 'discrete' refers to specific values that are distinct and separate from each other, as opposed to continuous values which form a range.

Discrete data refers to items that can be counted and are distinct and separate. In the given correct answer, the number of people in a class is a clear example of discrete data as it involves counting individuals.

The correct term for the data collected in a study is known as a 'Data Set'. A data set contains information or raw data points that are analyzed to draw conclusions or make inferences.

Nominal and ordinal scales are both nonnumeric scales of measurement, allowing for categories or rankings without specific numerical values. Interval and ratio scales, on the other hand, are strictly numeric in nature.

Interval scale of measurement allows for meaningful mathematical operations like addition and subtraction, which is applicable to SAT scores but not to blood type, gender, and height.

In statistics, a sample is a subset of individuals or objects drawn from a larger population. It is used to make inferences about the population from which it is drawn.

Intervals represent a range of values with consistent intervals between each value. SAT scores fall under this category as they can range from a minimum to maximum score, with consistent intervals between each possible score.

In mathematics, ratio represents the comparison between two values, often with respect to their sizes or quantities.

Statistical inference involves making interpretations or conclusions about populations based on data from a sample, through estimation, hypothesis testing, and prediction.

A continuous variable can have an infinite number of values within a given range, making it different from discrete variables which can only take on distinct, separate values.

Relative frequency is a statistical concept that represents the proportion or percentage of a particular class within the total number of data items. It is calculated by dividing the number of occurrences of the class by the total number of data items in the set.

Observations refer to the collection of measurements or data points for a specific element, while the other options do not specifically describe the act of collecting measurements.