Question

Ivan, a sales manager, just finished reading some sales statistics comparing his company's performance to that of competitors. The statistics summarize a mass of raw figures into a few meaningful measures that Ivan will use to determine whether he needs to change his sales strategy. The statistics in the printout are

A. information, while the raw figures used to compute the statistics are data B data, while the raw figures used to compute the statistics are information. C. less useful to Ivan than the raw figures would have been, since summarizing the figures necessarily reduces their accuracy D.an example of how managers have a tendency to oversimplify by reducing complex issues into a few simple numbers.

Answer 1

The statistics in the printout are data, while the raw figures used to compute the statistics are information.

Step-by-step explanation:

The correct answer is A. information, while the raw figures used to compute the statistics are data.

In this context, raw figures are considered as data, which are the actual measurements or observations made in an investigation. These raw data need to be organized and summarized into meaningful measures, which are known as statistics. These statistics provide actionable information for decision-making.

For example, Ivan, the sales manager, analyzes the sales statistics comparing his company's performance to that of competitors. The statistics summarize the raw sales figures, such as revenue, units sold, or market share, into meaningful measures that allow Ivan to evaluate his company's performance and determine if any changes are needed in the sales strategy.

Answer 2

The statistics Ivan reads are information summarized from raw data to aid in decision-making; this process is known as descriptive statistics. Such summarization is crucial for efficiently understanding complex data sets and influencing strategic choices. Inferential statistics take this further by using probability to extrapolate conclusions from the data.

Step-by-step explanation:

The statistics that Ivan is reviewing can be classified as information, while the raw figures they are based on qualify as data. When raw data is collected, it consists of the basic numbers and measurements obtained from business activities, customer interactions, or market research. However, to turn this data into information that is useful for decision-making, it must be organized, analyzed, and summarized into a form that is understandable and actionable for managers. This process is the essence of descriptive statistics, which includes techniques such as graphing and calculating averages to present data in ways that reveal trends and patterns.

It is through descriptive statistics that managers like Ivan can compute key metrics that are relative to business performance, customer preferences, or competitive positioning. As he considers changes to his sales strategy, these condensed and interpreted figures provide a more direct insight than raw data would. It is important to note that while summarization may lead to a loss of some granularity, the value lies in enhancing the ability to make strategic decisions efficiently.

Lastly, it is worth mentioning that the practice of interpreting these summaries falls into another branch of statistics known as inferential statistics, which uses probability to draw conclusions about a larger population from a sample. Inferential statistics help provide a level of confidence in the decisions based on the data analyzed.