Ch4 Estimating with Uncertainty PDF

Preview

Summary

Professor Esmael Jafari Haddadian...

Description

Chapter 4: Estimating with Uncertainty ● μ is the true population mean ● � is the true population SD ● p is the population proportion 4.1 The sampling distribution of an estimate ● Probability distribution of all values for an estimate that you might have obtained when you sample a population ○ Imaginary population of values for an estimate ● Spread of sampling distribution depends on sample size ○ Larger sampling size → narrower sampling distribution → greater precision ● If sampling distribution is centered around true population mean → unbiased 4.2 Measuring the uncertainty of an estimate ● Standard error: SD of the sampling distribution of an estimate ○ Smaller standard error → higher precision ● Every estimate has a sampling distribution with a standard error ● Indicates uncertainty of an estimate 4.3 Confidence intervals ● Another way to quantify uncertainty ● Range of values surrounding the sample estimate that is likely to contain the population parameter ● Indicates “confidence” but not “probability” ● 2SE rule of thumb: Approximation to the 95% confidence interval can be calculated as the sample mean plus and minus 2 standard errors 4.4 Error bars ● Graphic representations of standard errors or confidence intervals ● Indicate uncertainty about the population parameter, not variability in the data...