Chapter 8 Review Cl

Chapter 8 Review Cl - Chapter 8 Confidence Intervals Some...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Chapter 8 : Confidence Intervals Some Important Concepts : Parameter It is a numerical summary of the population. Since, we generally do not have the population data, population parameters are almost always unknown In any statistical inference problem, the main task is to estimate the unknown parameter(s) as accurately as possible. Eg : The true proportion of adult Americans who believe that president Obama can fix the healthcare situation. Statistic It is a numerical summary of a sample Statistics are calculated using data from random samples obtained from the population. Statistics are often seen as reflections of population parameters on the sample. We use sample statistics to make statistical inferences about the unknown population parameters. Eg : Suppose you randomly select 10 adult Americans from every U.S state. Then the proportion of them who believe president Obama can fix the healthcare situation Statistical Inference It is the process of making decisions and predictions about one or more population parameters using one or sample statistics , obtained from a random and representative sample. Types of Statistical Inference : Point Estimation : Here we put forward a single estimate (our best guess) for the population parameter. Eg : The average GPA of your class is a point estimate of the average UF GPA. Interval Estimation : It is an estimation process by which we form a Confidence Interval of the population parameter. It is an interval containing the most plausible values of the parameters and within which the true parameter value is believed to lie. Eg : The interval (2.5, 4) is likely to contain the true average GPA of UF students.
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Interval estimates gives us an idea of precision – so they tell us more than the point estimates Significance Test (or Test of hypotheses ) : It is a process that yields a decision on whether a claim about the value of the parameter is supported by data observed from a random sample. An important concept that goes with the confidence interval is that of the Confidence level . Confidence Level : It is the probability that the confidence interval actually contains the true parameter value. It is chosen to be very close to 1, commonly .90, .95 or .99 . Thus, if we choose a confidence level, say, 0.99 for our C.I, then we can say that “ we are 99% confident that our C.I contains the true parameter value ”. C.I generally have the form :
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 10/19/2009 for the course STA 3024 taught by Professor Ta during the Spring '08 term at University of Florida.

Page1 / 8

Chapter 8 Review Cl - Chapter 8 Confidence Intervals Some...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online