Please solve this question. (Please do not make an indentation issue)

Write a function to calculate the Gaussian 1/x- m f(x) 1 exp 2as * (***)] for arbitrary mean value m and standard deviation s as parameters. Name it as you like such that you can use it in the following: Write a function 'myerror_function()' which takes four numbers as input in the order: lower integration limit, higher integration limit, mean value and standard deviation. Integrate the Gaussian function with the given parameters, something that can't be done analytically. Return the calculated integral value (including its error), noting that a manual return value using math.erf() or similar will be moderated to zero marks. This integral represents a special mathematical function, the Error function which you can look up and research for instance starting with the existing error function in the Python math module, math.erf(). It is important for anyone working with data. Answer: (penalty regime: 10, 20, ... %) TLU THU JLg 7 8 return math.exp(-x*x/2.0) / (math.sqrt(2.0*math.pi Write a function to calculate the Gaussian 1/x- m f(x) 1 exp 2as * (***)] for arbitrary mean value m and standard deviation s as parameters. Name it as you like such that you can use it in the following: Write a function 'myerror_function()' which takes four numbers as input in the order: lower integration limit, higher integration limit, mean value and standard deviation. Integrate the Gaussian function with the given parameters, something that can't be done analytically. Return the calculated integral value (including its error), noting that a manual return value using math.erf() or similar will be moderated to zero marks. This integral represents a special mathematical function, the Error function which you can look up and research for instance starting with the existing error function in the Python math module, math.erf(). It is important for anyone working with data. Answer: (penalty regime: 10, 20, ... %) TLU THU JLg 7 8 return math.exp(-x*x/2.0) / (math.sqrt(2.0*math.pi