Basic math

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$BASIC MATH : NOMINAL AND ORDINAL DATA MOHD SABIQ B. MOHD NOR ALI KHAIRI B MAZLAN.$

TYPES OF DATA ,[object Object],[object Object],[object Object],[object Object]

WHAT IS NOMINAL DATA? ,[object Object],[object Object],[object Object],[object Object],[object Object]

Nominal Data ,[object Object],[object Object],[object Object],[object Object],[object Object]

WHAT IS ORDINAL DATA? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Ordinal Data ,[object Object],[object Object],[object Object],[object Object],[object Object]

EXAMPLE OF NOMINAL DATA ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

EXAMPLE OF ORDINAL DATA ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

REFERENCES ,[object Object],[object Object],[object Object],[object Object]

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Categorical Data Categorical data represents characteristics. Therefore it can represent things like a person’s gender, language etc. Categorical data can also take on numerical values (Example: 1 for female and 0 for male). Note that those numbers don’t have mathematical meaning. Nominal Data Nominal values represent discrete units and are used to label variables, that have no quantitative value. Just think of them as „labels“. Note that nominal data that has no order. Therefore if you would change the order of its values, the meaning would not change. You can see two examples of nominal features below: The left feature that describes a persons gender would be called „dichotomous“, which is a type of nominal scales that contains only two categories. Ordinal Data Ordinal values represent discrete and ordered units. It is therefore nearly the same as nominal data, except that it’s ordering matters. You can see an example below: Note that the difference between Elementary and High School is different than the difference between High School and College. This is the main limitation of ordinal data, the differences between the values is not really known. Because of that, ordinal scales are usually used to measure non-numeric features like happiness, customer satisfaction and so on. Numerical Data 1. Discrete Data We speak of discrete data if its values are distinct and separate. In other words: We speak of discrete data if the data can only take on certain values. This type of data can’t be measured but it can be counted. It basically represents information that can be categorized into a classification. An example is the number of heads in 100 coin flips. You can check by asking the following two questions whether you are dealing with discrete data or not: Can you count it and can it be divided up into smaller and smaller parts? 2. Continuous Data Continuous Data represents measurements and therefore their values can’t be counted but they can be measured. An example would be the height of a person, which you can describe by using intervals on the real number line. Interval Data Interval values represent ordered units that have the same difference. Therefore we speak of interval data when we have a variable that contains numeric values that are ordered and where we know the exact differences between the values. An example would be a feature that contains temperature of a given place like you can see below: The problem with interval values data is that they don’t have a „true zero“. That means in regards to our example, that there is no such thing as no temperature. With interval data, we can add and subtract, but we cannot multiply, divide or calculate ratios. Because there is no true zero, a lot of descriptive and inferential statistics can’t be applied. Ratio Data Ratio values are also ordered units that have the same difference. Ratio values are the same as interval values, with the difference that they do have an absolute zero. Good e ...

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References: Agarwal, B. L. 2006. Basic Statistics. Revised Fourth Edition. New Age International (P) Ltd.: New Delhi. Broto, Antonio S. 2006. Statistics Made Simple. National Book Store: Mandaluyong City. Microsoft® Encarta® 2009. © 1993-2008 Microsoft Corporation. All rights reserved. Pennings, Paul, Keman, Hans, and Kleinnijenhuis, Jan 1999. Doing Research in Political Science: An Introduction to Comparative Methods and Statistics. Sage: London.

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Basic math

1. BASIC MATH : NOMINAL AND ORDINAL DATA MOHD SABIQ B. MOHD NOR ALI KHAIRI B MAZLAN.

9. EXAMPLE

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Basic math

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Basic math