PDF-Topic 2: Confidence Intervals and Hypothesis Tests

Module 22 Confidence Intervals for Two Parameters Lecture 224 Confidence Intervals as Hypothesis Tests The foregoing section shows that the computaprovide computational procedures forces of means. Remember we saw The sample proportion will differ from the population proportion by more than the margin of error less than 5 of the time The Margin of Error for a sample of size n is 1 n Suppose we wanted to estimate a Population Mean rather than a Robin H. Lock, Burry Professor of Statistics. Patti Frazer Lock, Cummings Professor of Mathematics. St. Lawrence University. Joint Mathematics Meetings. New Orleans, January 2011. Intro Stat at St. Lawrence. Using Lock5. Statistics: Unlocking the Power of Data. Patti Frazer Lock. Chapter 1: Collecting Data. Why is this first?. Comes first in actual analysis. More interesting than histograms and mean/median!. GrowingKnowing.com © 2011. 1. GrowingKnowing.com © 2011. Estimates. We are often asked to predict the future!. When will you complete your team project?. When will you make your first million dollars?. Samples vs. Populations. Population. All of the objects that belong to a class (e.g. all Darl projectile points, all Americans, all pollen grains). A theoretical distribution. Sample. Some of the objects in a class. Chapter 23. Inference About Means . Getting Started. Now that we know how to create confidence intervals and test hypotheses about proportions, . it would . be nice to be able to do the same for means. Section 8.1. Confidence Intervals: The Basics. After this section, you should be able to…. INTERPRET a confidence level. INTERPRET a confidence interval in context. DESCRIBE how a confidence interval gives a range of plausible values for the parameter. John Krickl. Glenbrook North High School. Northbrook, IL. jkrickl@glenbrook225.org. DUALITY STICKS. Motivation. “. Using the same sample, a two-tailed hypothesis test with significance level α will . Zero In on the Null. To . perform a hypothesis test, the null must be a statement about the value of a parameter for a model. . We then use this value to compute the probability that the . observed. sample statistic—or something even farther from the null value—might occur.. Robin Lock. Burry Professor of Statistics. St. Lawrence University. AMATYC Webinar. December 6, 2016. The Lock. 5. Team. Patti & Robin. St. Lawrence. Kari. Harvard. Penn State. Eric. North Carolina. Chapter 6 Confidence Intervals Sections 6-1 and 6-2 Confidence Intervals for Large and Small Samples   VOCABULARY: Point Estimate – A single value estimate for a population parameter. Introductory Statistics. Robin H. Lock, Burry Professor of Statistics. St. Lawrence University. Breakout Panel. USCOTS 2011 - Raleigh, NC. Intro Stat (Math 113) at St. Lawrence. 26-29 students per section. Lecture Outline. 1. Simple Regression:. . Predictor variables Standard Errors. Evaluating Significance of Predictors . Hypothesis Testing. How well do we know . ?. How well do we know . ?. Multiple Linear Regression: . Special Topics. A 95% Confidence Interval. Now, in plain English…. What this is saying is that a 95% confidence interval is an interval created to estimate what (where) the true parameter might be..