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Yes, it is possible for the sample mean to be exactly equal to 135 minutes. This is because the sample mean is calculated by dividing the sum of all the observations by the number of observations. Therefore, if the sum of all the observations is exactly equal to 2700 minutes (135 times 20), the sample mean would be 135 minutes. However, this is highly unlikely to happen.
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Is hair color a discrete or continuous variable?
Hair color is considered a discrete variable because it falls into distinct categories such as blonde, brown, black, red, etc. Each category is separate and distinct from the others, with no intermediate shades. In contrast, a continuous variable would have an infinite number of possible values within a range, which is not the case with hair color.
If a variable has possible values -2 6 and 17 then this variable is?
If a variable has possible values -2 6 and 17 then this variable is an Integer.
What would -2 standard deviation below the mean be?
It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.
What is the difference among non-orderable discrete orderable discrete continuous variables?
A non-orderable discrete variable is usually one for which the information that is recorded can only have a finite number of qualitative outcomes and that there is no relevant ordering of these outcomes. One example might be favourite fruit. Although the responses can be ordered alphabetically, or by mass of typical specimen, these are not relevant ordering schemes. An orderable discrete variable is one in which there is a relevant basis for ordering the outcomes. An example might be shoe sizes which, in the UK, go ... 6.5, 7, 7.5, 8, 8.5, 9, ... .The ordering reflects how large the shoe is. A continuous variable is one which can take any possible value in the permitted range. A typical example is a person's height. Even though in recording the variable becomes discretised (eg 5ft 10" or 176 cm), the underlying variable is continuous.
What is a continuous random variable?
In the simplest setting, a continuous random variable is one that can assume any value on some interval of the real numbers. For example, a uniform random variable is often defined on the unit interval [0,1], which means that this random variable could assume any value between 0 and 1, including 0 and 1. Some possibilities would be 1/3, 0.3214, pi/4, e/5, and so on ... in other words, any of the numbers in that interval. As another example, a normal random variable can assume any value between -infinity and +infinity (another interval). Most of these values would be extremely unlikely to occur but they would be possible. The random variable could assume values of 3, -10000, pi, 1000*pi, e*e, ... any possible value in the real numbers. It is also possible to define continue random variables that assume values on the entire (x,y) plane, or just on the circumference of a circle, or anywhere that you can imagine that is essentially equivalent (in some sense) to pieces of a real line.
