Descriptive Statistics

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School

Colorado Technical University *

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Course

502

Subject

Statistics

Date

Apr 3, 2024

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docx

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Uploaded by MajorWaterFinch27

Introduction Consider the statistic for the average price of homes in your area. A number would be given as the average cost of the home. If you were told that one in every five women has blue eyes, you would still be a given a number of women, but the actual statistic is about having blue eyes. The average price of the homes and the eye color of women are both descriptions. The data collected are in two categories: numbers and characteristics. Learning Material Descriptive statistics present basic features of data in a study. Statistics are typically numbers that are used to summarize the data set. For example, 40% of the employees in the office are women. The role of descriptive statistics is to provide a unique piece of information about the data set. Consider ways that you describe items. You may describe a person by name, hair color, age, or height. You may describe a level of pain as minor or severe. Data collected in a study may be an attribute (such as name or color) or a number (such as a score). These different types of data are defined as qualitative and quantitative. Qualitative data are non-numerical measurements, like data collected in the form of a name or label. Examples of qualitative data are hair color, eye color, gender, and marital status. A concept to consider for qualitative data is whether the data can be ranked or not. If you were asked to rank a color, you could provide your opinion, but you cannot truly define a ranking to the best color. Other data may be ranked. Have you ever been asked to rate your pain? Your answer could range from minor to severe. Each response is a label but can be ranked as to its severity. Popup Qualitative data The qualities, attributes, or categorical features of a group of individuals or objects. Quantitative data are numerical measurements. Examples of quantitative data are height, weight, prices, and number of hours. Quantitative data can be discrete, which means that the number or amount is countable. An example of quantitative data would be 35 students in a class or the number of tax audits completed in a day. The data can be continuous. Data, such as time, weight, and height, are considered continuous.

Popup Quantitative Data Quantitative data is information regarding quantities or measurable amounts. Summary Descriptive statistics have the same purpose whether they are qualitative or quantitative. The statistics summarize the results and answer questions about the data set. Interactive Example Quantitative data about a job would not include: Status of employee review Is filing status for tax returns considered qualitative or quantitative data? Qualitative Is temperature in the office considered discrete or continuous data? Continuous Questions Qualitative data about a person would not include: Weight Quantitative data include which of the following? Hours worked In a medical study, which data are quantitative? Temperature Is someone’s level of satisfaction considered attribute or measurement data?

Attribute When completing your income tax return, you have to provide information. Which of the following is quantitative? Total income At the doctor’s office, you are asked questions regarding symptoms. Which of the following results is qualitative? Level of pain Which qualitative data can be ranked? Military titles

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