Types of Data PDF

TYPES OF DATA  Learning Objective: - Identify the different types of data. https://byjus.com/maths/types-of-data-in-statistics/  DATA - it is the latin for fact. - it can be numbers, record names, or other labels. - not all data represented by...

TYPES OF DATA  Learning Objective: - Identify the different types of data. https://byjus.com/maths/types-of-data-in-statistics/  DATA - it is the latin for fact. - it can be numbers, record names, or other labels. - not all data represented by numbers are numerical data e.g. 1=male, 2=female - data are useless without their context. Retrieved from: https://www.cambridgeinternational.org/images/285017-data-information-and-knowledge.pdf  2 TYPES OF DATA 1.Quantitative Data 2.Qualitative Data https://www.nagwa.com/en/plans/475102183284/ QUANTITATIVE DATA - Quantitative data is also known as numerical data which represents the numerical value (i.e., how much, how often, how many). - Numerical data gives information about the quantities of a specific thing. - The quantitative data can be classified into two different types based on the data sets. EXAMPLES OF QUANTITATIVE DATA - Some examples of numerical data are height, length, size, weight - Height or weight of a person or object - Room Temperature - Scores and Marks (Ex: 59, 80, 60, etc.) - Time 2 CLASSIFICATION OF QUANTITATIVE DATA 1.Discrete Data - Discrete data can take only discrete values. Here, things can be counted in whole numbers. - Example: Number of students in the class 1.Continuous Data - Continuous data is data that can be calculated. It has an infinite number of probable values that can be selected within a given specific range. - Example: Temperature range EXAMPLES OF DISCRETE DATA - Total numbers of students present in a class - Cost of a cell phone - Numbers of employees in a company - The total number of players who participated in a competition EXAMPLES OF CONTINUOUS DATA - Height of a person - Speed of a vehicle - “Time-taken” to finish the work - Market share price QUALITATIVE DATA - Qualitative data, also known as the categorical data, describes the data that fits into the categories. Qualitative data are not numerical. The categorical information involves categorical variables that describe the features such as a person’s gender, home town etc. Categorical measures are defined in terms of natural language specifications, but not in terms of numbers. - These types of data are sorted by category, not by number. That’s why it is also known as Categorical Data. These data consist of audio, images, symbols, or text. The gender of a person, i.e., male, female, or others, is qualitative data. QUALITATIVE DATA - Sometimes categorical data can hold numerical values (quantitative value), but those values do not have a mathematical sense. - Examples of the categorical data are birthdate, favourite sport, school postcode. - Here, the birthdate and school postcode hold the quantitative value, but it does not give numerical meaning.  2 CLASSIFICATION OF QUALITATIVE DATA 1. Nominal Data - The name “nominal” comes from the Latin name “nomen,” which means “name.” With the help of nominal data, we cannot do any numerical tasks or cannot give any order to sort the data. These data don’t have any meaningful order; their values are distributed into distinct categories. - Examples of nominal data are letters, symbols, words, gender etc. 1. Ordinal Data - Ordinal data/variable is a type of data that follows a natural order. The significant feature of the nominal data is that the difference between the data values is not determined. This variable is mostly found in surveys, finance, economics, questionnaires, and so on. These data are used for observation like customer satisfaction, happiness, etc., but we can’t do any arithmetical tasks on them. Compared to nominal data, ordinal data have some kind of order that is not present in nominal data. EXAMPLES OF NOMINAL DATA Colour of hair (Blonde, red, Brown, Black, etc.) Marital status (Single, Widowed, Married) Nationality (Filipino, Indian, German, American) Gender (Male, Female, Others) EXAMPLES OF ORDINAL DATA When companies ask for feedback, experience, or satisfaction on a scale of 1 to 10 Letter grades in the exam (A, B, C, D, etc.) Ranking of people in a competition (First, Second, Third, etc.) Education Level (Higher, Secondary, Primary)