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  • https://stats.libretexts.org/Courses/Cerritos_College/Introduction_to_Statistics_with_R/08%3A_Estimating_Unknown_Quantities_from_a_Sample/8.04%3A_Estimating_Population_Parameters
    knitr::kable(data.frame(stringsAsFactors=FALSE, Symbol = c("$s$", "$\\sigma$", "$\\hat{\\sigma}$", "$s^2$", "$\\sigma^2$", "$\\hat{\\sigma}^2$"), What.is.it = c("Sample standard deviation", "Populatio...knitr::kable(data.frame(stringsAsFactors=FALSE, Symbol = c("$s$", "$\\sigma$", "$\\hat{\\sigma}$", "$s^2$", "$\\sigma^2$", "$\\hat{\\sigma}^2$"), What.is.it = c("Sample standard deviation", "Population standard deviation", "Estimate of the population standard deviation", "Sample variance", "Population variance", "Estimate of the population variance"), Do.we.know.what.it.is = c("Yes - calculated from the raw data", "Almost never known for sure", "Yes - but not the same as the sample standard dev…
  • https://stats.libretexts.org/Workbench/PSYC_2200%3A_Elementary_Statistics_for_Behavioral_and_Social_Science_(Oja)_WITHOUT_UNITS/08%3A_One_Sample_t-test/8.01%3A_Predicting_a_Population_Mean
    Let's start inferring!
  • https://stats.libretexts.org/Courses/Taft_College/PSYC_2200%3A_Elementary_Statistics_for_Behavioral_and_Social_Sciences_(Oja)/02%3A_Mean_Differences/08%3A_One_Sample_t-test/8.01%3A_Predicting_a_Population_Mean
    Let's start inferring!
  • https://stats.libretexts.org/Workbench/Learning_Statistics_with_SPSS_-_A_Tutorial_for_Psychology_Students_and_Other_Beginners/07%3A_Estimating_Unknown_Quantities_from_a_Sample/7.04%3A_Estimating_Population_Parameters
    However, in simple random samples, the estimate of the population mean is identical to the sample mean: if I observe a sample mean of \(\bar{X}\) = 98.5, then my estimate of the population mean is als...However, in simple random samples, the estimate of the population mean is identical to the sample mean: if I observe a sample mean of \(\bar{X}\) = 98.5, then my estimate of the population mean is also \(\hat{\mu}\)=98.5. Figure 7.12: An illustration of the fact that the sample mean is an unbiased estimator of the population mean (panel a), but the sample standard deviation is a biased estimator of the population standard deviation (panel b).

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