By the y variable - whatever that may be. It may be a dependent variable or another independent variable.
in any graph on horizontal axis we keep the independent variable and on vertical axis the dependent variable. similarly in stress strain diagram the strain is independent variable and stress is dependent variable so due to this reason strain is kept on x-axis and stress is kept on y-axis.
The horizontal axis is reserved for the independent variable in a function. Time is always an independent variable in time-based functions. However, duration can be dependent. It depends on what's being plotted.
The probability that it attains any particular value is not affected by the values taken by any other variables in the study.
5 Km equals 3.10 miles. one kilometer equals 0.621 miles, therefor multiply the number of miles you wish to convert by 0.621 to get the answer in kilometers
sampling time is the number of samples per second taken from a continuous signal to make it discrete and holding time is the time between two samples..
Sampling rate or sampling frequency defines the number of samples per second (or per other unit) taken from a continuous signal to make a discrete or digital signal.
For discrete distributions, suppose the variable X takes the specific value x with probability P(X=x) Then add together x * P(X = x) for all possible values of x. For continuous distributions, suppose the probability distribution function of the variable X is f(x). Then the mean is the integral of x*f(x) with respect to x, taken over all possible values of x.
The largest value minus the smallest value. In statistics, a distribution is the set of all possible values for terms that represent defined events. There are two major types of statistical distributions. The first type has a discrete random variable. This means that every term has a precise, isolated numerical value. An example of a distribution with a discrete random variable is the set of results for a test taken by a class in school. The second major type of distribution has a continuous random variable. In this situation, a term can acquire any value within an unbroken interval or span. Such a distribution is called a probability density function. This is the sort of function that might, for example, be used by a computer in an attempt to forecast the path of a weather system.
Dependant variable: the variable you measure in an experiment. It changes due to external factors affecting it. It can be time taken, or distance traveled... ect. Independant variable: the variable you change in an experiment. It can be the amount of time, or concentration of a substance... ect. Generally continuous variables, though not always.
malinga
This variable is called a "switch".
By the y variable - whatever that may be. It may be a dependent variable or another independent variable.
Discrete - Each recorded data has a particular whole value e.g. Number of pencils in pencil cases, Number of correct answers in a test Continuous - The recorded data can have any value in a given range e.g. Height of students, Time taken to run 100m
Techniques such as southern blot or polymerase chain reaction can be used to screen for randomly dispersed repeats.DNA polymorphism is used in forensic science to make connections between the sample collected from the crime scene and the sample taken from the suspect.Single nucleotide polymorphism, Variable number of random repeats are some examples of DNA polymorphism.
In a scientific experiment there are different variables. Variables being the factors that you can alter to obtain your results. The independent variable is the factor that you directly alter and the dependent variable is the one that is affected by this. E.g. You pull a cart over 1m and measure the time taken. The force you exert is the independent variable as you are controlling it and time is the dependent variable because it is the variable that is affected by the force you exert. Like if you pulled it really hard the time taken would be really short, and if you pulled it gently the time taken would be really long, etc.
independant variable