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- https://stats.libretexts.org/Courses/Fresno_City_College/Introduction_to_Business_Statistics_-_OER_-_Spring_2023/07%3A_The_Central_Limit_Theorem/7.04%3A_The_Central_Limit_Theorem_for_ProportionsThe random variable is \(X =\) the number of successes and the parameter we wish to know is \(p\), the probability of drawing a success which is of course the proportion of successes in the population...The random variable is \(X =\) the number of successes and the parameter we wish to know is \(p\), the probability of drawing a success which is of course the proportion of successes in the population. Importantly, in the case of the analysis of the distribution of sample means, the Central Limit Theorem told us the expected value of the mean of the sample means in the sampling distribution, and the standard deviation of the sampling distribution.
- https://stats.libretexts.org/Courses/Fresno_City_College/Book%3A_Business_Statistics_Customized_(OpenStax)/07%3A_The_Central_Limit_Theorem/7.04%3A_The_Central_Limit_Theorem_for_ProportionsThe random variable is \(X =\) the number of successes and the parameter we wish to know is \(p\), the probability of drawing a success which is of course the proportion of successes in the population...The random variable is \(X =\) the number of successes and the parameter we wish to know is \(p\), the probability of drawing a success which is of course the proportion of successes in the population. Importantly, in the case of the analysis of the distribution of sample means, the Central Limit Theorem told us the expected value of the mean of the sample means in the sampling distribution, and the standard deviation of the sampling distribution.
- https://stats.libretexts.org/Courses/Saint_Mary's_College_Notre_Dame/BFE_1201_Statistical_Methods_for_Finance_(Kuter)/05%3A_Point_Estimates/5.04%3A_The_Central_Limit_Theorem_for_ProportionsThe random variable is \(X =\) the number of successes in the sample and the parameter we wish to know is \(p\), the probability of drawing a success which is of course the proportion of successes in ...The random variable is \(X =\) the number of successes in the sample and the parameter we wish to know is \(p\), the probability of drawing a success which is of course the proportion of successes in the population. Importantly, in the case of the analysis of the distribution of sample means, the Central Limit Theorem told us the expected value of the mean of the sample means in the sampling distribution, and the standard deviation of the sampling distribution.
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/05%3A_Continuous_Probability_Distributions/5.04%3A_The_Central_Limit_Theorem_for_ProportionsThe random variable is \(X =\) the number of successes in the sample and the parameter we wish to know is \(p\), the probability of drawing a success which is of course the proportion of successes in ...The random variable is \(X =\) the number of successes in the sample and the parameter we wish to know is \(p\), the probability of drawing a success which is of course the proportion of successes in the population. Importantly, in the case of the analysis of the distribution of sample means, the Central Limit Theorem told us the expected value of the mean of the sample means in the sampling distribution, and the standard deviation of the sampling distribution.
