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- https://math.libretexts.org/Courses/Cosumnes_River_College/STAT_300%3A_Introduction_to_Probability_and_Statistics_(Nam_Lam)/06%3A_The_Normal_Distribution/6.04%3A_The_Sample_ProportionOften sampling is done in order to estimate the proportion of a population that has a specific characteristic.
- https://math.libretexts.org/Courses/Western_Technical_College/PrePALS_Math_with_Business_Apps/08%3A_Statistics/8.03%3A_The_Normal_DistributionWhen graphing the data from each of the examples in the introduction, the distributions from each of these situations would be mound-shaped and mostly symmetric. A normal distribution is a perfectly s...When graphing the data from each of the examples in the introduction, the distributions from each of these situations would be mound-shaped and mostly symmetric. A normal distribution is a perfectly symmetric, mound-shaped distribution. It is commonly referred to the as a normal curve, or bell curve. Because so many real data sets closely approximate a normal distribution, we can use the idealized normal curve to learn a great deal about such data.
- https://math.libretexts.org/Courses/University_of_St._Thomas/Math_101%3A_Finite_Mathematics/03%3A_Probability_Distributions_and_Statistics/3.07%3A_Exercises/3.7.02%3A_Continuous_Random_Variableshese are homework exercises to accompany the Textmap created for "Introductory Statistics" by Shafer and Zhang.
- https://math.libretexts.org/Courses/University_of_St._Thomas/Math_101%3A_Finite_Mathematics/03%3A_Probability_Distributions_and_Statistics/3.02%3A_Probability_Distributions_for_Discrete_Random_VariablesThe probability distribution of a discrete random variable X is a list of each possible value of X together with the probability that X takes that value in one trial of the experiment. The proba...The probability distribution of a discrete random variable X is a list of each possible value of X together with the probability that X takes that value in one trial of the experiment. The probabilities in the probability distribution of a random variable X must satisfy the following two conditions: Each probability P(x) must be between 0 and 1 and the sum of all the probabilities is 1 .
- https://math.libretexts.org/Courses/University_of_St._Thomas/Math_101%3A_Finite_Mathematics/03%3A_Probability_Distributions_and_Statistics/3.01%3A_Random_VariablesA random variable is a number generated by a random experiment. A random variable is called discrete if its possible values form a finite or countable set. A random variable is called continuous if ...A random variable is a number generated by a random experiment. A random variable is called discrete if its possible values form a finite or countable set. A random variable is called continuous if its possible values contain a whole interval of numbers.
- https://math.libretexts.org/Courses/University_of_St._Thomas/Math_101%3A_Finite_Mathematics/03%3A_Probability_Distributions_and_Statistics/3.05%3A_The_Standard_Normal_DistributionA standard normal random variable Z is a normally distributed random variable with mean μ=0 and standard deviation σ=1.
- https://math.libretexts.org/Courses/Fullerton_College/Math_100%3A_Liberal_Arts_Math_(Claassen_and_Ikeda)/09%3A_Normal_Distribution/9.02%3A_The_Standard_Normal_DistributionA standard normal random variable Z is a normally distributed random variable with mean μ=0 and standard deviation σ=1.
- https://math.libretexts.org/Courses/Fullerton_College/Math_100%3A_Liberal_Arts_Math_(Claassen_and_Ikeda)/09%3A_Normal_Distribution/9.03%3A_Probability_Computations_for_General_Normal_DistributionsProbabilities for a general normal random variable are computed after converting x-values to z-scores.
- https://math.libretexts.org/Courses/University_of_St._Thomas/Math_101%3A_Finite_Mathematics/03%3A_Probability_Distributions_and_Statistics/3.06%3A_Probability_Computations_for_General_Normal_Random_VariablesProbabilities for a general normal random variable are computed after converting x-values to z-scores.
- https://math.libretexts.org/Courses/Cosumnes_River_College/STAT_300%3A_Introduction_to_Probability_and_Statistics_(Nam_Lam)/03%3A_Numerical_Summaries_of_Data/3.04%3A_The_Empirical_Rule_and_Chebyshev's_TheoremThe Empirical Rule is an approximation that applies only to data sets with a bell-shaped relative frequency histogram. It estimates the proportion of the measurements that lie within one, two, and thr...The Empirical Rule is an approximation that applies only to data sets with a bell-shaped relative frequency histogram. It estimates the proportion of the measurements that lie within one, two, and three standard deviations of the mean. Chebyshev’s Theorem is a fact that applies to all possible data sets. It describes the minimum proportion of the measurements that lie must within one, two, or more standard deviations of the mean.
- https://math.libretexts.org/Courses/Fullerton_College/Math_100%3A_Liberal_Arts_Math_(Claassen_and_Ikeda)/09%3A_Normal_Distribution/9.01%3A_The_Normal_DistributionWhen graphing the data from each of the examples in the introduction, the distributions from each of these situations would be mound-shaped and mostly symmetric. A normal distribution is a perfectly s...When graphing the data from each of the examples in the introduction, the distributions from each of these situations would be mound-shaped and mostly symmetric. A normal distribution is a perfectly symmetric, mound-shaped distribution. It is commonly referred to the as a normal curve, or bell curve. Because so many real data sets closely approximate a normal distribution, we can use the idealized normal curve to learn a great deal about such data.
