Answer :
The necessary condition to meet in order to use a normal distribution to model the sampling distribution of p^ is n×p and n×(1-p).
As per the question we have to determine the necessary condition that must be met in order to use a normal distribution to model the sampling distribution of p^.
In probability theory and statistics, the Normal Distribution, also called the Gaussian Distribution.
A large number of random variables are either nearly or exactly represented by the normal distribution.
The Normal Distribution is defined by the probability density function for a continuous random variable in a system.
Let us say, f(x) is the probability density function and X is the random variable.
Hence, it defines a function which is integrated between the range or interval (x to x + dx), giving the probability of random variable X, by considering the values between x and x+dx.
From the given information,
The required necessary condition is,
Both n×p and n×(1-p) to be at least 10.
Where, n is sample size and p is the probability of success.
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