points = 100
m1 = 10
v1 = 4
syms a b
[a, b] = solve( (a+b) == 2*m1,(b-a)^2 == 12 *v1)
r = a + (b-a).*rand(points, 1);freezer said:Homework Statement
Generate 100 data points from a continuous uniform distribution with mean = 10 and variance = 4
Homework Equations
u = (a+b)/2
var = (b-a)^2 / 12
r = a + (b-a).*rand(100,1);
The Attempt at a Solution
Code:points = 100 m1 = 10 v1 = 4 syms a b [a, b] = solve( (a+b) == 2*m1,(b-a)^2 == 12 *v1) r = a + (b-a).*rand(points, 1);
A continuous uniform distribution in Matlab is a statistical distribution that represents a continuous range of values with equal probability. It is commonly used to model random variables that are equally likely to take on any value within a specified range.
To generate random numbers from a continuous uniform distribution in Matlab, you can use the rand function with the uniform option. For example, rand(1,10,'uniform') will generate 10 random numbers between 0 and 1 with equal probability.
Yes, you can specify the range of values for a continuous uniform distribution in Matlab by using the rand function with the uniform option and specifying the desired minimum and maximum values. For example, rand(1,10,'uniform', 5, 10) will generate 10 random numbers between 5 and 10 with equal probability.
To plot a continuous uniform distribution in Matlab, you can use the plot function with the pdf option. For example, plot(pdf('uniform',x,0,1)) will plot the probability density function for a continuous uniform distribution with a range of 0 to 1.
Yes, there are several other functions in Matlab that can be used with a continuous uniform distribution, including cdf (cumulative distribution function), icdf (inverse cumulative distribution function), and fitdist (fitting a continuous distribution to data). These functions can be useful for statistical analysis and modeling with a continuous uniform distribution.