STATS 250 Lecture Notes - Lecture 7: Statistic, Normal Distribution, Standard Deviation

• School: U of M
• Department: Statistics
• Course: STATS 250
• Professor: Brenda Gunderson

Document Summary

Parameter versus statistic e. g. population proportion p versus sample proportion p e. g. population mean versus sample mean x. Take r. s. compute corresponding sample statistic to estimate the parameter. The results from chapter 9 will be used to make conclusions about population parameters based on sample statistics. The two most common statistical inference procedures are confidence interval estimation and hypothesis testing. Confidence interval estimation: a confidence interval is a range of values that the researcher is fairly confident will cover the true, unknown value of the population parameter. In other words, we use a confidence interval to estimate the value of a population parameter. Hypothesis testing: hypothesis testing uses sample data to attempt to reject a hypothesis about the population. Usually researchers want to reject the notion that chance alone can explain the sample results. Hypothesis testing is applied to population parameters by specifying a null value for the parameter a value that would indicate that nothing of interest is happening.