--%>

Discrete and continuous data

Distinguish between discrete and continuous data in brief.

E

Expert

Verified

Discrete data are whole numbers. They take on particular values and no values in between. Data like the number of homes one has could be one or two as an example of discrete data as one could not own one and a half homes.

Continuous data is a random variable and can take on any value on a range. An example of temperature could be 30.23 degrees.

   Related Questions in Advanced Statistics

  • Q : Non-parametric test what is the

    what is the appropriate non-parametric counterpart for the independent sample t test?

  • Q : Problem on utility funtion probability

    Suppose that your utility, U, is a function only of wealth, Y, and that U(Y) is as drawn below. In this graph, note that U(Y) increases linearly between points a and b.  Suppose further that you do not know whether or not you

  • Q : Use the law of iterated expectation to

    Suppose we have a stick of length L. We break it once at some point X _

    Q : Problem on consumers marginal utility

    Consider a consumer with probability p of becoming sick.  Let Is be the consumer’s income if he becomes sick, and let Ins be his income if he does not become sick, with Is < Ins. Suppo

  • Q : Probability Distributions and Data

    1. A popular resort hotel has 300 rooms and is usually fully booked. About 4% of the time a reservation is canceled before 6:00 p.m. deadline with no penalty. What is the probability that at least 280 rooms will be occupied? Use binomial distribution to find the exact value and the normal approxi

  • Q : How you would use randomization in

    The design of instrument controls affects how easily people can use them. An investigator used 25 students who were right-handed to determine whether right-handed subjects preferred right-handed threaded knobs. He had two machines that differed only in that one had a

  • Q : Bayesian Point Estimation What are the

    What are the Bayesian Point of estimation and what are the process of inference in Bayesian statistics?

  • Q : Components of time series Name and

    Name and elaborate the four components of time series in brief.

  • Q : Random variables Random variables with

    Random variables with zero correlation are not necessarily independent. Give a simple example.    

  • Q : Probability of signaling Quality

    Quality control: when the output of a production process is stable at an acceptable standard, it is said to be "in control?. Suppose that a production process has been in control for some time and that the proportion of defectives has been 0.5. as a means of monitorin