MATH 1P98 Lecture Notes - Lecture 6: Variance, Standard Deviation, Bias Of An Estimator

• School: Brock University
• Department: Mathematics and Statistics
• Course: MATH 1P98
• Professor: TBA

Document Summary

Instead of using values from the original population (which are practically unobtainable), we focus on values obtained from samples of our population. i. e. , sample proportion, sample mean. Consider the sample mean instead of taking just one sample of size n, take all possible samples of size n from the pop. (has mean ) and calculate the mean of each sample. Right in the middle of the histogram (bell-shaped) This is the sampling distribution of the mean. It is the distribution of all possible sample means when all possible samples of size n are taken from the same population. If the sampling distribution of the means (the mean of all sample means) has a value that is equal to the population mean, we say it is an unbiased estimation of the pop. Mean. i. e. , the statistic (cid:862)targets(cid:863) the parameter - the sample mean targets the population mean eg. consider the three instructors for ip98.