Answer:
For a scaler variable, the Gaussian distribution has a probability density function of
p(x |µ, σ² ) = N(x; µ, σ² ) = 1 / 2π×
The term will have a maximum value at the top of the slope of the 1-D Gaussian distribution curve that is when exp(0) =1 or when x = µ
Step-by-step explanation:
Gaussian distributions have similar shape, with the mean controlling the location and the variance controls the dispersion
From the graph of the probability distribution function it is seen that the the peak is the point at which the slope = 0, where µ = 0 and σ² = 1 then solution for the peak = exponential function = 0 or x = µ
Answer:
Step-by-step explanation:
No. Starting out, Maria walks away from home at a constant speed (which we recognize because the graph is at first a straight line). Then she stops for a little while, turns around and heads for home at the same speed as before (positively sloped graph), level graph, negatively sloped graph).
Answer:
See explanation
Step-by-step explanation:
A. P(top)=top outcomes/all kinds of outcomes=4/30=2/15=13.33333333333...%
P(bottom)=bottom outcomes/ all kinds of outcomes=1/30=3.33333333....%
P(side)=25/30=5/6=83.33333333333...%
B. No. If were equally likely, the probabilities for A would have been roughly the same. It seems like the side event is more probable.
The answer is going to be 1/9
Theres about a 7,200,000 difference between household dogs vs household cats
