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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.

Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical values are called discrete data. For instance, the number of phone calls received for each day of the week can be zero, one, two, or three, a whole number.

Data that include fractions, decimals, or irrational numbers are called continuous quantitative data. Continuous data are often the results of measurements like length, weight, or time. For example, the phone calls made in a day can have any numerical values such as 2.4 minutes, 7.5 minutes, or 11.0 minutes. The number of books that students carry in their backpacks is an example of discrete data, while the weight of the backpacks carried by the students is an example of continuous data.

This text is adapted from Openstax, Introductory Statistics, Section 1.1 Definitions of Statistics, Probability, and Key Terms

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Numerical DataQuantitative DataDiscrete DataContinuous DataCountableMeasurableAttributes Of A PopulationWhole NumbersFractionsDecimalsIrrational NumbersMeasurements

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1.3 : How Data are Classified: Numerical Data

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1.1 : 統計学入門

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1.2 : データの分類方法: カテゴリデータ

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1.4 : 測定の公称レベル

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1.5 : 測定の順序レベル

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1.6 : 測定のインターバルレベル

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1.7 : 測定の比率レベル

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1.8 : 観測値によるデータ収集

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1.9 : 実験によるデータ収集

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1.10 : 調査によるデータ収集

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1.11 : ランダムサンプリング法

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1.12 : 体系的なサンプリング法

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1.13 : コンビニエンスサンプリング方式

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1.14 : 層別サンプリング法

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1.15 : クラスター サンプリング方法

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