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- https://biz.libretexts.org/Courses/Gettysburg_College/MGT_235%3A_Introductory_Business_Statistics_(2nd_edition)/01%3A_Sampling_and_Data/1.02%3A_Definitions_of_Statistics_Probability_and_Key_TermsThe idea of sampling is to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. For example, if we consider one math clas...The idea of sampling is to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. For example, if we consider one math class to be a sample of the population of all math classes, then the average number of points earned by students in that one math class at the end of the term is an example of a statistic.
- https://biz.libretexts.org/Workbench/MGT_235/06%3A_Confidence_Intervals/6.01%3A_IntroductionThe empirical rule, which applies to the normal distribution, says that in approximately 95% of the samples, the sample mean, \(\overline x\), will be within two standard deviations of the population ...The empirical rule, which applies to the normal distribution, says that in approximately 95% of the samples, the sample mean, \(\overline x\), will be within two standard deviations of the population mean \mu. Where \(\overline x\) is the sample mean. \(Z_{\alpha}\) is determined by the level of confidence desired by the analyst, and \(\sigma / \sqrt{n}\) is the standard deviation of the sampling distribution for means given to us by the Central Limit Theorem.
- https://biz.libretexts.org/Courses/Gettysburg_College/MGT_235%3A_Introductory_Business_Statistics_(2nd_edition)/06%3A_Confidence_Intervals/6.01%3A_IntroductionThe empirical rule, which applies to the normal distribution, says that in approximately 95% of the samples, the sample mean, \(\overline x\), will be within two standard deviations of the population ...The empirical rule, which applies to the normal distribution, says that in approximately 95% of the samples, the sample mean, \(\overline x\), will be within two standard deviations of the population mean \(\mu\). Where \(\overline x\) is the sample mean. \(z_\frac{\alpha}{2}\) is determined by the level of confidence (1-\(\alpha\)) desired by the analyst, and \(s / \sqrt{n}\) is the standard deviation of the sampling distribution for means given to us by the Central Limit Theorem.
- https://biz.libretexts.org/Workbench/MGT_235/01%3A_Sampling_and_Data/1.02%3A_Definitions_of_Statistics_Probability_and_Key_TermsThe idea of sampling is to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. For example, if we consider one math clas...The idea of sampling is to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. For example, if we consider one math class to be a sample of the population of all math classes, then the average number of points earned by students in that one math class at the end of the term is an example of a statistic.
