Considering this from a physics point of view, age or the progression of time d*/dt is continuous. I know I am continuously aging. Of course when we speak of our age we tend to jump and ignore fractional changes right? One day we're 28 and stay that way for 364 days, then bang we're 29. No one says well I'm 28.6 years old. Some seem to be stuck at 29, until they have to be honest about it and there is an abrupt change to say 40.
Neither. It is a discrete variable.
It is just a factor or categorical variable. On the other hand for instance, If your age is continuous (rather than age brackets) then it would be a covariate. If your age is given as age-brackets, then it wont be covariate.
It depends how we have computed %age. By and large, percentage is a summary statistic. Its a categorical variable (may be nominal or ordinal). That way its a discrete. In case of assay or yield computations it becomes a continuous variable. Naresh K Chawla nkchawla@gmail.com
Age is acontinuousvariable because it can bemeasured with numbers. A categorical variable deals with nominal variables example male or female, political view, etc
It can be used to describe continuous or discreet data but not categorical or ordered data, unless that data is also numercal which is very unlikely
continuous discrete
A categorical variable (also known as a discrete variable) is one whose range is countable; e.g. the variable answ has values [yes, no, not sure]. answ is a categorical variable with range 3.A continuous variable is one which is not categorical; e.g. weight is a continuous variable which can take any value between 0 and 1000 kg (say) for a human being.
The correlation ratio, often denoted as η (eta), measures the strength and direction of association between a continuous variable and a categorical variable. It quantifies how much variability in the continuous variable can be explained by the categorical variable. Unlike Pearson's correlation, which is limited to linear relationships between two continuous variables, the correlation ratio can capture relationships involving categorical data. It is particularly useful in statistical analysis to understand the influence of categorical factors on continuous outcomes.
Neither. It is a discrete variable.
It is just a factor or categorical variable. On the other hand for instance, If your age is continuous (rather than age brackets) then it would be a covariate. If your age is given as age-brackets, then it wont be covariate.
No, categorical data cannot be continuous. Categorical data consists of distinct categories or groups, such as colors, brands, or yes/no responses, where values represent different classifications rather than quantities. Continuous data, on the other hand, can take any value within a range and is measured on a scale, such as height or temperature. Thus, the two types of data are fundamentally different in nature.
BMI (Body Mass Index) is considered a continuous measure because it calculates a numeric value based on an individual's weight and height. However, it is often used in a categorical manner to classify individuals into categories such as underweight, normal weight, overweight, and obese based on specific BMI ranges. Thus, while the underlying data is continuous, its application in health assessments can be categorical.
It depends how we have computed %age. By and large, percentage is a summary statistic. Its a categorical variable (may be nominal or ordinal). That way its a discrete. In case of assay or yield computations it becomes a continuous variable. Naresh K Chawla nkchawla@gmail.com
It depends how we have computed %age. By and large, percentage is a summary statistic. Its a categorical variable (may be nominal or ordinal). That way its a discrete. In case of assay or yield computations it becomes a continuous variable. Naresh K Chawla nkchawla@gmail.com
Age is acontinuousvariable because it can bemeasured with numbers. A categorical variable deals with nominal variables example male or female, political view, etc
It can be used to describe continuous or discreet data but not categorical or ordered data, unless that data is also numercal which is very unlikely
Employment is typically considered a categorical variable rather than a continuous variable. It often involves discrete categories, such as employed, unemployed, or not in the labor force. While one could analyze aspects of employment, such as hours worked or income, those specific metrics are continuous variables, but the overall employment status itself remains categorical.