Identifying variables as quantitative or categorical

In summary, the conversation discusses a problem with classifying variables in a dataset for a statistics assignment. The individuals in the dataset are breakfast cereals and the variables include sugars, almond delight, manufacturer, calories, cold, apple jacks, fibers, K, brand name, and all bran. The conversation also touches on the effectiveness of the course's teaching methods and the issue of using software that does not support popular browsers.
  • #1
cashflow
37
1

Homework Statement



Here is a small part of an EESEE data set, "Nutrition and Breakfast Cereals," that describes the nutritional content per serving of 77 brands of breakfast cereals:

cereal.jpg


What are the individuals in this data set?
For each individual, what variables are given? Which of these variables are categorical and which are quantitative?

Match your answers below.
1. Individual
2. Categorical variable
3. Quantitative variable
4. Specific variable value
5. None of the above

A. Sugars
B. Almond Delight
C. Manufacturer
D. Calories
E. Cold
F. Apple Jacks
G. Fibers
H. K
I. Brand name
J. All Bran

Homework Equations



N/A

The Attempt at a Solution



The individuals in the dataset are the cereals. I'm trying to classify the variables but I keep getting 9/10 right. I have 1 try left and I really want to get this concept correctly understood.

A. Sugars - Quantitative
B. Almond Delight - Individual
C. Manufacturer - Categorical
D. Calories - Quantitative
E. Cold - Specific variable value
F. Apple Jacks - Individual
G. Fibers - Quantitative
H. K - Specific variable value
I. Brand name - I tried None of the Above, Individual, and Categorical... still ending up with 9/10
J. All Bran - Individual
 
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  • #2
For Brand Name, my best guess is None of the Above. I wouldn't think that Brand Name was a category variable. I'm guessing that this is a computer-scored assignment. Is there someone who is knowledgeable about this software that you can ask?
 
  • #3
I sent an email to my professor. I thought it was None of the Above, too.
 
  • #4
Turns out it is None of the Above... I've got a different letter wrong and can't figure out what. Any ideas?
 
  • #5
cashflow said:
Turns out it is None of the Above... I've got a different letter wrong and can't figure out what. Any ideas?
Maybe this one:
E. Cold - Specific variable value

Cold/hot is a category, with variable values of C and H.
 
  • #6
Perhaps this post should go on a thread in a different section - the lounge or somewhere but - Is it just me or does anyone think the same?

If you got 10/10 on that test you should worry something is wrong with you. Waste no more time on that exercise!

What a way to start a course on anything, even statistics! Are you able to switch to a course on something substantial? Because as a general rule courses that start like this are like films whose first 15 min. are bad, they don't get better later. Or at least move ahead, read the book independently of and before the lessons and if you ever find you are stuck in a statistical analysis through not knowing whether manufacturers are categorical variables then look back to this lesson and I'm sure it will be more significant, memorable or more whatever it needs to be more.

Am I the only one with this reaction? Is statistics particularly afflicted by boring didactics or is it intrinsically boring so that it would be dishonest not to make these efforts to make sure it seems so?
 
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  • #7
epenguin said:
Perhaps this post should go on a thread in a different section - the lounge or somewhere but - Is it just me or does anyone think the same?
This is the appropriate section for this problem, not the lounge.
epenguin said:
If you got 10/10 on that test you should worry something is wrong with you. Waste no more time on that exercise!
The OP probably wants to make sure that he/she understands the material. I grant you that this question is overly pedantic in its concern about definitions that have very little to do with the meat of statistics.
epenguin said:
What a way to start a course on anything, even statistics! Are you able to switch to a course on something substantial? Because as a general rule courses that start like this are like films whose first 15 min. are bad, they don't get better later. Or at least move ahead, read the book independently of and before the lessons and if you ever find you are stuck in a statistical analysis through not knowing whether manufacturers are categorical variables then look back to this lesson and I'm sure it will be more significant, memorable or more whatever it needs to be more.

Am I the only one with this reaction? Is statistics particularly afflicted by boring didactics or is it intrinsically boring so that it would be dishonest not to make these efforts to make sure it seems so?
 
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  • #8
Mark44 said:
For Brand Name, my best guess is None of the Above. I wouldn't think that Brand Name was a category variable. I'm guessing that this is a computer-scored assignment. Is there someone who is knowledgeable about this software that you can ask?

You were right, it was a software bug. Ridiculous that they don't support something as important as Google Chrome (which has around 42.5% market share).
 

1. What is the difference between quantitative and categorical variables?

Quantitative variables are numerical in nature and represent a measurable quantity, such as age or height. Categorical variables, on the other hand, are non-numerical and represent a characteristic or category, such as gender or favorite color.

2. How can I identify if a variable is quantitative or categorical?

A simple way to identify a variable as quantitative or categorical is to ask yourself if the variable represents a number or a category. If it represents a number, it is quantitative. If it represents a category, it is categorical.

3. Can a variable be both quantitative and categorical?

No, a variable can only be one or the other. However, a categorical variable can sometimes be represented by numbers, such as assigning a number to each category (e.g. 1 for male and 2 for female). In this case, the variable is still considered categorical because the numbers do not have any numerical significance.

4. Why is it important to identify variables as quantitative or categorical?

Identifying variables correctly is important because it determines the appropriate statistical methods to use for analysis. Quantitative variables require different statistical tests than categorical variables, so misidentifying a variable can lead to incorrect conclusions.

5. Can the same variable be treated as both quantitative and categorical in different analyses?

Yes, in some cases a variable can be treated as either quantitative or categorical depending on the specific research question or analysis being conducted. However, it is important to be consistent and clearly define how the variable is being treated in each analysis.

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