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There are four levels of measures, one of them being ordinal. Ordinal data merely orders subjects according to a certain rationale. Numbers indicates a position, indicating that the individual or object possesses more or less of the studied characteristic. As such, an example of ordinal data would be to put all the students in a classroom in order of height, or according to their average in mathematics. However, as we can see, this would not allow to know the height or average of the students. It also doesn't indicate the quantitative difference between each rank. As a consequence, the difference between two ranks does not mean there is a significant difference on what is measured. (Example:1st:95%, 2nd:90%, 3rd: 89%. We would not know the average, only the rank. Also, as we can see, between the first and second rank there is a 5% difference, whereas there is only a 1% difference between the second and third rank.)
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∙ 16y ago
Ordinal data refers to a type of data that has a natural order or ranking. This means that the values can be ranked or sorted in a particular order, but the differences between the values are not numerically quantifiable. Examples include rankings (such as "1st," "2nd," "3rd") and Likert scale responses (such as "strongly agree," "agree," "neutral," "disagree," "strongly disagree").
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What is nominal and ordinal in qualitative variables?
In qualitative variables, nominal data involves categories with no inherent order, such as colors or types of fruit. Ordinal data, on the other hand, includes categories that have a meaningful order or ranking, such as education levels or customer satisfaction ratings.
What is ordinal data?
are categorical data where there is logical ordering to the categories, eg, 1 = strongly agree, 2 = Agree, 3 = Neutral, 4 = Disagree, 5 = Strongly disagree. It is data that only show their relationship to each other, but they do not give us actual values to tell how much difference there is. Ordinal data almost always starts at 1 and progresses in order to some number that is equal to the n of the original data. Any time you see 1st, 2nd, 3rd, etc, you are dealing with ordinal data. If the data doesn't tell you how much better person 1 did than person 2, then it is probably ordinal. There is a race between 6 friends. If the researcher wanted to collect Ordinal data, he or she would have everybody start at the same time and record who came in first, second, third etc. The data would be able to show who was the fastest, but it would be useless to a newcomer who wanted to see where they fit into the group. If he or she raced alone and "won" first, that would not make that person a faster or slower runner than a friend who raced and came in second or third. If they had kept track of the time (interval or ratio data depending on how it was recorded) then they would be able to compare the newcomer easily by comparing the new time. Some other ordinal examples... "The Third tallest person in the class" (we don't know how tall, only that there are two others taller than this person) "Now serving #7" (we don't know when they got in line, but we know it was after #6 and before #8) "I'm the worst soccer player at my school" (maybe this person's school has extremely good soccer players, we don't know how good this person is, only that he or she is not good relative to their peers.)
Which research method assesses how well one variable predicts another without specifying a cause and effect relationshop between the variables?
For numerical date: Calculation of the product moment correlation coefficient (PMCC). Regression analysis goes beyond what is required by the question. For ordinal data: The Spearman's Rank coefficient.
What does interval data mean?
Interval data is a type of quantitative data where the difference between two values is meaningful and consistent. It has a fixed unit of measurement and a true zero point. Examples of interval data include temperature in Celsius and time.
What The sum of the difference of score around the mean is?
The sum of the differences between each score and the mean is always zero. This is because the mean is the "center" of the data and any deviation from the mean in one direction is offset by an equal deviation in the opposite direction. This property is essential in understanding the concept of the mean as a measure of central tendency.
Should The mean or median be used in ordinal data?
The median is used when reporting ordinal data.
IS GPA nominal data or ordinal?
It is ordinal.
What is ordinal statistics?
Ordinal statistics or data is classified as ordinal if the values can be rated on a scale or put i order. Ordinal data can be counted but never measured.
Is asking your birth year a ordinal data?
No, but the answers provide ordinal data.
How do you convert ordered data to nominal data?
I think you mean ordinal data. Similar to the golf tournament, you need to determine where to "cut" (from the ordinal data) so as to divide the data into different categories (to the nominal data). For example, if the ordinal data range from 1 to 6 (where 1 = the best) and the cut is 3, then you convert all the numbers from 1 to 3 to "1" (which represents "good") and the all numbers from 4 to 6 to "2" (which represents "bad"). In other words, 1, 2, and 3 from the original ordinal data set are converted to "1" (ordinal data); whereas 4, 5, and 6 from the original date set now become "2" (ordinal data). Eddie T.C. Lam
Which measure of central tendency cannot be applied to ordinal data?
The mean cannot be used with ordinal data. The best measure of central tendency for ordinal data is usually the median. A common example of ordinal data is the scale you see in many surveys. 1=Strongly disagree; 2=Disagree; 3=Neutral; 4=Agree; 5=Strongly agree. The mean would have not meaning here ( no pun intended) The median is simple the middle value. The mode does have meaning.
What are the advantages and disadvantages transforming of continuous data into either discrete or ordinal data?
1.) Discrete: restricted to integers; ordinal subjective
What is Data that is ranked but not with even intervals?
ordinal
Are eye colors ordinal data?
no, they are categorical
Major advantage of ordinal data over nominal data?
its sick blad
What measure of central tendency may not exist for all numeric data sets?
Measurement Scale Best measure of the 'middle' Numerical mode Ordinal Median Interval Symmetrical data- mean skewed data median Ratio Symmetrical data- Mean skewed data median
What is the measure of central tendency for nominal and ordinal data?
The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.The mode can be used with both kinds of data. The median may be used with ordinal data but great care is required if the median falls between two classes of observations.
