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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/7.06%3A_Chapter_Key_TermsBy definition, the mean for a sample (denoted by \(\overline x\)) is \(\overline x =\overline{x}=\frac{\text { Sum of all values in the sample }}{\text { Number of values in the sample }}\), and the m...By definition, the mean for a sample (denoted by \(\overline x\)) is \(\overline x =\overline{x}=\frac{\text { Sum of all values in the sample }}{\text { Number of values in the sample }}\), and the mean for a population (denoted by \(\mu\)) is \(\mu=\frac{\text { Sum of all values in the population }}{\text { Number of values in the population }}\).
- https://stats.libretexts.org/Courses/Saint_Mary's_College_Notre_Dame/BFE_1201_Statistical_Methods_for_Finance_(Kuter)/05%3A_Point_Estimates/5.07%3A_Chapter_Key_TermsBy definition, the mean for a sample (denoted by \(\overline x\)) is \(\overline x =\overline{x}=\frac{\text { Sum of all values in the sample }}{\text { Number of values in the sample }}\), and the m...By definition, the mean for a sample (denoted by \(\overline x\)) is \(\overline x =\overline{x}=\frac{\text { Sum of all values in the sample }}{\text { Number of values in the sample }}\), and the mean for a population (denoted by \(\mu\)) is \(\mu=\frac{\text { Sum of all values in the population }}{\text { Number of values in the population }}\).
- https://stats.libretexts.org/Courses/Fresno_City_College/Book%3A_Business_Statistics_Customized_(OpenStax)/07%3A_The_Central_Limit_Theorem/7.08%3A_Chapter_Key_TermsBy definition, the mean for a sample (denoted by \(\overline x\)) is \(\overline x =\overline{x}=\frac{\text { Sum of all values in the sample }}{\text { Number of values in the sample }}\), and the m...By definition, the mean for a sample (denoted by \(\overline x\)) is \(\overline x =\overline{x}=\frac{\text { Sum of all values in the sample }}{\text { Number of values in the sample }}\), and the mean for a population (denoted by \(\mu\)) is \(\mu=\frac{\text { Sum of all values in the population }}{\text { Number of values in the population }}\).
