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7.3: Characteristics of Estimators
https://stats.libretexts.org/Courses/Luther_College/Psyc_350%3ABehavioral_Statistics_(Toussaint)/07%3A_Estimation/7.03%3A_Characteristics_of_Estimators
This section discusses two important characteristics of statistics used as point estimates of parameters: bias and sampling variability. Bias refers to whether an estimator tends to either over or und...This section discusses two important characteristics of statistics used as point estimates of parameters: bias and sampling variability. Bias refers to whether an estimator tends to either over or underestimate the parameter. Sampling variability refers to how much the estimate varies from sample to sample.
1.4: Sampling Methods
https://stats.libretexts.org/Courses/Fort_Hays_State_University/Elements_of_Statistics/01%3A_Introduction_to_Statistics/1.04%3A_Sampling_Methods
Sampling is the means by which sample data is collected, and it plays a significant role in inferential statistics. There are many ways to sample; some are better than others.
10.3: Characteristics of Estimators
https://stats.libretexts.org/Bookshelves/Introductory_Statistics/Introductory_Statistics_(Lane)/10%3A_Estimation/10.03%3A_Characteristics_of_Estimators
This section discusses two important characteristics of statistics used as point estimates of parameters: bias and sampling variability. Bias refers to whether an estimator tends to either over or und...This section discusses two important characteristics of statistics used as point estimates of parameters: bias and sampling variability. Bias refers to whether an estimator tends to either over or underestimate the parameter. Sampling variability refers to how much the estimate varies from sample to sample.

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