'True parameter value' diaporamas de présentation

Power and Sample Size

Power and Sample Size. (Images taken from van Belle). Review of Type I & Type II Errors. When we conduct a test of any hypothesis regardless of the test used we make one of two possible decisions: Reject the null (H o ) in favor of the alternative (H a ) OR

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Chapter 6

Chapter 6. Introduction to Inference. Introduction. We use statistical inference to draw conclusions from data Our conclusions must account for the natural variability in the data To account for the variability, formal inference relies on probability to describe chance variation

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Chapter Eight Part 1 (Sections 8.1 to 8.3) Estimation

Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith Gloucester County College. Chapter Eight Part 1 (Sections 8.1 to 8.3) Estimation. Point Estimate. an estimate of a population parameter given by a single number. Examples of Point Estimates.

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Chapter 6

Chapter 6. Inferences Regarding Locations of Two Distributions. Comparing 2 Means - Independent Samples. Goal: Compare responses between 2 groups (populations, treatments, conditions)

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Sampling Distributions of Statistics Corresponds to Chapter 5 of Tamhaneand Dunlop

Sampling Distributions of Statistics Corresponds to Chapter 5 of Tamhaneand Dunlop. Slides prepared by Elizabeth Newton (MIT), with some slides by Jacqueline Telford (Johns Hopkins University) . Sampling Distributions . Definitions and Key Concepts

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Confidence Intervals

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Quant 3610

Quant 3610. Weber State University. Dr. Stephen Hays Russell. Part I Course Introduction. Course Introduction. Me You Approach in this course MINITAB The Syllabus No Stat Text required Definitions and refresher concepts.

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Topic 4

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Mean Squared Error and Maximum Likelihood

Mean Squared Error and Maximum Likelihood. Lecture XVIII. Mean Squared Error. As stated in our discussion on closeness, one potential measure for the goodness of an estimator is. In the preceding example, the mean square error of the estimate can be written as:

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Section 10.1 Estimating with Confidence

Section 10.1 Estimating with Confidence. AP Statistics www.toddfadoir.com/apstats. An introduction to statistical inference. Statistical Inference provides methods for drawing conclusions about a population from sample data.

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STA 291 Spring 2010

STA 291 Spring 2010. Lecture 13 Dustin Lueker. Statistical Inference: Estimation. Inferential statistical methods provide predictions about characteristics of a population, based on information in a sample from that population Quantitative variables Usually estimate the population mean

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Interval Estimation for Means

Interval Estimation for Means. Notes of STAT6205 by Dr. Fan. Overview. Sections 6.2 and 6.3 Introduction to interval estimation Confidence Intervals for One mean General construction of a confidence interval Confidence Intervals for difference of two means Pair Samples.

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Statistics

Christopher, Anna, and Casey. Statistics. What you should have learned: Math 1/ Math 2. Normal distributions Empirical Rule Mean, standard deviation Parameters and statistics. Confidence Intervals: Overview. A level C confidence interval for a parameter has 2 parts.

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8.1 Estimating ? when ? is Known

8.1 Estimating ? when ? is Known. Access for population data is either expensive or impossible to attain so we have to estimate the population parameters Assumptions : We have a Simple Random Sample (SRS) of size n from our population.

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10.3 Estimating a Population Proportion

10.3 Estimating a Population Proportion. Objectives: Given a sample proportion determine the standard error of . Construct a confidence interval for a population proportion.

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SAMPLING DISTRIBUTIONS. SAMPLING VARIABILITY

SAMPLING DISTRIBUTIONS. SAMPLING VARIABILITY. COMMON NEED : estimate population parameters: mean or proportion or spread EXAMPLE . Producers of clothing need to know average dimensions of human body and their variability. Food industry needs to know average consumption of different foods, etc.

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Intro to Confidence Intervals

Intro to Confidence Intervals. AP Statistics. Introduction Our goal in many statistical settings is to use a sample statistic to estimate a population parameter. Earlier we learned if we randomly select the sample, we should be able to generalize our results to the population of interest .

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