The difference between the qualitative and quantitative data with examples

OlmekinjP
2021-02-09
Answered

The difference between the qualitative and quantitative data with examples

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2abehn

Answered 2021-02-10
Author has **88** answers

Step 1

In statistics, according to measurement, data can be categorized in two types, such as quantitative data and qualitative data.

Step 2

Quantitative variable can take numerical values, whereas qualitative variable is used to identify the characteristics of a variable as categories. Moreover, mathematical operations cannot be performed on qualitative data, but can be performed on quantitative data.

Quantitative data are easy to analysis, consistent and reliable. If the sampling procedure is procedure, then it representatives a proper study population.

However, quantitative data sometimes robust to understand complex issues. Moreover, it is difficult to understand the main matter of the phenomenon.

The selection procedure of qualitative data is cost efficient. It is not robust to understand complex issues.

However, it is very difficult to analyse and the selection procedure is time consuming.

Example of qualitative data: Eye color, gender, names of countries.

Example of quantitative data: Height of a person, Scores in an examination, Temperature.

In statistics, according to measurement, data can be categorized in two types, such as quantitative data and qualitative data.

Step 2

Quantitative variable can take numerical values, whereas qualitative variable is used to identify the characteristics of a variable as categories. Moreover, mathematical operations cannot be performed on qualitative data, but can be performed on quantitative data.

Quantitative data are easy to analysis, consistent and reliable. If the sampling procedure is procedure, then it representatives a proper study population.

However, quantitative data sometimes robust to understand complex issues. Moreover, it is difficult to understand the main matter of the phenomenon.

The selection procedure of qualitative data is cost efficient. It is not robust to understand complex issues.

However, it is very difficult to analyse and the selection procedure is time consuming.

Example of qualitative data: Eye color, gender, names of countries.

Example of quantitative data: Height of a person, Scores in an examination, Temperature.

asked 2020-12-24

True or False

1.The goal of descriptive statistics is to simplify, summarize, and organize data.

2.A summary value, usually numerical, that describes a sample is called a parameter.

3.A researcher records the average age for a group of 25 preschool children selected to participate in a research study. The average age is an example of a statistic.

4.The median is the most commonly used measure of central tendency.

5.The mode is the best way to measure central tendency for data from a nominal scale of measurement.

6.A distribution of scores and a mean of 55 and a standard deviation of 4. The variance for this distribution is 16.

7.In a distribution with a mean of M = 36 and a standard deviation of SD = 8, a score of 40 would be considered an extreme value.

8.In a distribution with a mean of M = 76 and a standard deviation of SD = 7, a score of 91 would be considered an extreme value.

9.A negative correlation means that as the X values decrease, the Y values also tend to decrease.

10.The goal of a hypothesis test is to demonstrate that the patterns observed in the sample data represent real patterns in the population and are not simply due to chance or sampling error.

1.The goal of descriptive statistics is to simplify, summarize, and organize data.

2.A summary value, usually numerical, that describes a sample is called a parameter.

3.A researcher records the average age for a group of 25 preschool children selected to participate in a research study. The average age is an example of a statistic.

4.The median is the most commonly used measure of central tendency.

5.The mode is the best way to measure central tendency for data from a nominal scale of measurement.

6.A distribution of scores and a mean of 55 and a standard deviation of 4. The variance for this distribution is 16.

7.In a distribution with a mean of M = 36 and a standard deviation of SD = 8, a score of 40 would be considered an extreme value.

8.In a distribution with a mean of M = 76 and a standard deviation of SD = 7, a score of 91 would be considered an extreme value.

9.A negative correlation means that as the X values decrease, the Y values also tend to decrease.

10.The goal of a hypothesis test is to demonstrate that the patterns observed in the sample data represent real patterns in the population and are not simply due to chance or sampling error.

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