This preview shows page 1. Sign up to view the full content.
Unformatted text preview: we will discuss have the SMALLEST saying when ’s saying what we “want” to say when we should not (p. 323), SIGNIFICANCE Type I error £ In our lightbulb example, ¡ LEVEL of the test. ¢ Reject Ho £ Correct #$ . forms the basis for our decision. Make decision Compute value of TS Get data Do experiment depends on the choice of gives values of TS for which 4. Rejection Region : (RR) Then . 224 is REJECTED computed from the sample data using a formula 3. Test Statistic : (TS) 2. Alternative Hypothesis : 1. Null Hypothesis : Parts of a Statistical Test (p. 326) STA 2023 c D.Wackerly  Lecture 17 ¡ Accept Ho ¥ ¡ Ha true ¡ © £ Ho true ¢ © ¤ ¡ Decision © ¥ Reality ¢ ©
©
© ©
¤ ¤ ¢ ¢ ¢ ¢ #$ ¤ Errors: p. 325 ¢ 223 ) STA 2023 c D.Wackerly  Lecture 17 £ © © © © ¡ © If the value of the TS is NOT in the REJECTION REGION, we and If the value of the TS is in the REJECTION Decision : ¡ © . 225 because we usually do , what kind of error could we judgement Don’t want to accept usually that is really true , so we reserve depends on the value of the parameter in – What is the probability of a TYPE II error? make? – If we accept do so. ¡ not know the probability of making an error if we – We do not ACCEPT REGION, we DO NOT REJECT. ¡ ¡ : innocent Courtroom Analogy STA 2023 c D.Wackerly  Lecture 17 Proof “beyond a reasonable doub...
View Full
Document
 Spring '08
 Ripol
 Statistics, Standard Error

Click to edit the document details