Question

The author surveyed a sample from the population of her statistic class by selecting 5 females and 5 males.

Answer 1

The question pertains to sampling methods in mathematics which are used to select a part of a population for study. Various sampling methods include simple random, stratified, systematic, cluster, and convenience sampling, each with different applications and implications for the reliability and validity of a study's conclusions.

Step-by-step explanation:

The subject of this question pertains to sampling methods used in statistics, a branch of mathematics. Sampling is a technique that involves selecting a part of a population to represent the whole population.

Different types of sampling methods include simple random sampling, stratified sampling, systematic sampling, cluster sampling, and convenience sampling.

In the scenarios given, different methods are used.

For example, when the author surveyed a sample from the population of her statistics class by selecting 5 females and 5 males, this appears to be a form of stratified sampling because the population is divided into two subgroups (females and males) and members are sampled from each subgroup

. In another example, a sociologist mails questionnaires randomly to members of a local business and professional women's club.

The population in this study includes all the members of that women's club, and the given sample would be randomly selected from that population.

Understanding the various sampling methods is crucial as they can either reinforce or undermine the reliability and validity of a study's conclusions. Representative samples allow researchers to generalize their findings to the larger population without significant bias.

Answer 2

Since the author’s survey only categorizes individuals into two groups (females and males) without any inherent order or numerical value associated with it, the type of data collected in this scenario is nominal.

Step-by-step explanation:

Nominal data is the simplest level of measurement that represents categories or names without any inherent order or numerical value. In this case, the author surveyed a sample from her statistic class and selected 5 females and 5 males. The data collected only categorizes individuals into two groups based on their gender, without any specific order or numerical value associated with it.

To further understand the different levels of measurement, let’s briefly discuss the other three types:

• Ordinal: This level of measurement involves data that can be ranked or ordered. However, the differences between the ranks or categories are not necessarily equal. For example, if the author ranked the students in her statistic class based on their academic performance as “excellent,” “good,” “average,” and “poor,” it would be considered ordinal data.
• Interval: Interval data has the properties of ordinal data but also includes equal intervals between values. It does not have a true zero point but can represent meaningful differences between values. An example of interval data would be measuring temperature on the Celsius or Fahrenheit scales.
• Ratio: Ratio data is similar to interval data but includes a true zero point, representing an absence of the measured attribute. It allows for meaningful ratios and comparisons between values. Examples of ratio data include age, weight, height, and income.

Complete question:

The author rated the movie Star Wars: The Force Awakens with 5 stars on a scale of 5 stars.

(Nominal, Ordinal, Ratio, or Interval?)