1. PRF is based on population data as a whole, SRF is based on Sample data 2. We can draw only one PRF line from a given population. But we can Draw one SRF for one sample from that population. 3. PRF may exist only in our conception and imagination. 4. PRF curve or line is the locus of the conditional mean/ expectation of the independent variable Y for the fixed variable X in a sample data. SRF shows the estimated relation between dependent variable Y and explanatory variable X in a sample.
If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.
The constant is the number; the variable is the letter.
The question is about an oxymoronic expression. A constant cannot be a variable and a variable cannot be a constant!
Constant variable
A sample of a population is a subset of the population. The average of the population is a statistical measure for some variable of the population.
1. PRF is based on population data as a whole, SRF is based on Sample data 2. We can draw only one PRF line from a given population. But we can Draw one SRF for one sample from that population. 3. PRF may exist only in our conception and imagination. 4. PRF curve or line is the locus of the conditional mean/ expectation of the independent variable Y for the fixed variable X in a sample data. SRF shows the estimated relation between dependent variable Y and explanatory variable X in a sample.
If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.
The constant is the number; the variable is the letter.
In general when you take a sample of values of a random variable you will find that those values lie around some central value that is characteristic of the total population for the random variable. A measure of central tendancy (such as a sample mean, sample mode or sample median) is a statistic which is intended to estimate the central value of the population using the values in the sample in some way.
The question is about an oxymoronic expression. A constant cannot be a variable and a variable cannot be a constant!
Constant variable
The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.The answer will depend on the population mean of what variable? Height?, length or is it simply weight. If it is weight, the estimated (not estimd) population mean is 3.01 units: the same as the sample mean. The standard deviation (not diviation) is irrelevant.
© The statistic describes a sample, whereas a parameter describes an entire population.© Example of statistic is, if we randomly poll voters in a particular election and determine that 55% of the population plans to vote for candidate A, then you have a statistic because we only asked a sample of the population who they are voting for, then we calculated what the population was likely to do based on the sample. Alternatively the example of parameter is, if we ask a class of third graders who likes vanilla ice cream, and 90% of them raise their hands, then we have a parameter because 90% of that class likes vanilla ice cream. We know this because you asked everyone in the population.© Statistic is a random variable. But parameter is constant, it is not a random variable.
A constant is not a variable at all, and none of its factors was a variable. It is constant.
The opposite of the word "constant" is "variable".
A constant is a variable that does not change. The correct term is constant variable.