Lecture5-2

Lecture5-2 - BUAD 310 Applied Business Statistics 2/10/10 A...

Info iconThis preview shows pages 1–11. Sign up to view the full content.

View Full Document Right Arrow Icon
BUAD 310 Applied Business Statistics 2/10/10
Background image of page 1

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

View Full DocumentRight Arrow Icon
A Quick Review Statistical inference: Estimation Point estimate: sample mean and sample proportion (Chapter 7) Interval estimate: confidence interval (CI) (Chapter 8) Hypothesis testing (Chapters 9, 10 and 12) 2
Background image of page 2
Hypothesis Testing Test of significance Common type of statistical inference: assess the evidence provided by the data in favor of some claim about the population A formal procedure for comparing observed data with a statement about the parameters in a population or model 3
Background image of page 3

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

View Full DocumentRight Arrow Icon
Null and Alternative Hypotheses Null hypothesis H 0 : the statement being tested in a test of significance Often H 0 is a statement of “no effect” or “no difference” H 0 will not be rejected unless there is convincing sample evidence that it is false Alternative hypothesis H a : the statement we suspect is true instead of H 0 The test of significance is designed to assess the strength of evidence against the null hypothesis H 0 and in favor of H a 4
Background image of page 4
One-Sided and Two-Sided One-sided alternative hypothesis H a : either claims that the true parameter value is greater than the value claimed in the null hypothesis or claims that the true value is less than that in the null hypothesis Two-sided alternative hypothesis H a : claims that the true parameter value is not equal to the value claimed in the null hypothesis 5 0 0 0 0 0 0 : : : : a a H H H H 0 0 0 : : a H H
Background image of page 5

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

View Full DocumentRight Arrow Icon
One-Sided or Two-Sided? When to use one or the other? Use a one-sided hypothesis only when you have some preconceived notion about the direction of the difference. Otherwise, use a two-sided hypothesis. 6
Background image of page 6
Examples Trash bag case: a marketer of trash bags uses hypothesis testing to support its claim that the mean breaking strength of its new trash bag is greater than 50 pounds. Payment time case: a consulting firm uses hypothesis testing to provide strong evidence that the new electronic billing system has reduced the mean payment time by more than 50 percent (i.e., the new mean is less than 39/2 = 19.5 days). Camshaft case: an automobile manufacturer uses hypothesis testing to study an important quality characteristic affecting V6 engine camshafts. It finds that the mean “hardness depth” significantly differs from its desired target value of 4.5mm. 7
Background image of page 7

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

View Full DocumentRight Arrow Icon
Examples 8 One-Sided, Less Than H 0 : = 19.5 H a : < 19.5 (Payment time ) One-Sided, Greater Than H 0 : = 50 H a : > 50 (Trash bag) Two-Sided, Not Equal To H 0 : = 4.5 H a :   4.5 (Camshaft)
Background image of page 8
9 Type I Error Rejecting H 0 when it is true Type II Error Failing to reject H 0 when it is false State of Nature Conclusion H 0 True H 0 False Reject H 0 Type I Error Correct Decision Do not Reject H 0 Correct Decision Type II Error
Background image of page 9

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

View Full DocumentRight Arrow Icon
Test Statistic 10 A significance test is based on a statistic that estimates the parameter in the hypothesis A test statistic measures compatibility between the null hypothesis and the data. It is a random variable with a simple distribution.
Background image of page 10
Image of page 11
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 09/05/2010 for the course BUAD 310 taught by Professor Lv during the Spring '07 term at USC.

Page1 / 35

Lecture5-2 - BUAD 310 Applied Business Statistics 2/10/10 A...

This preview shows document pages 1 - 11. Sign up to view the full document.

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