MGMT 2340 Section W01 Business Statistics I Instructor: E. Mark Leany contact via Blackboard online.uen.org alternately: [email protected] Data Distributed by Frequency Alphabetical from the Skew 67
166 Probabilities of Events Areas Under the Normal Curve 226 This chart is the same one as the 3rd page on your quiz (and on the test)
272 Sampling Distribution based on n Confidence Intervals 302
One-Sample Tests of Hypothesis Chapter 10 326 GOALS 1. Define a hypothesis and hypothesis testing . 2. Describe the five-step hypothesis-testing procedure. 3. Distinguish between a one-tailed and a two-tailed test of hypothesis . 4. Conduct a test of hypothesis about a population mean. 5. Conduct a test of hypothesis about a population proportion. 6. Define Type I and Type II errors . 7. Compute the probability of a Type II error. 326
Hypothesis, Hypothesis and Testing HYPOTHESIS A statement about the value of a population parameter developed for the purpose of testing. HYPOTHESIS TESTING A procedure based on sample evidence and probability theory to determine whether the hypothesis is a reasonable statement. 328 5 Steps in Testing a Hypothesis 1. State the Null Hypothesis and the Alternate ( or Alternative ) Hypothesis 2. Select a Level of Significance ( Į ) 3. Select the Test Statistic 4. Formulate the Decision Rule 5. (Calculate &) Make a Decision
Step 1: State the Null Hypothesis and the Alternate Hypothesis NULL HYPOTHESIS A statement about the value of a population parameter developed for the purpose of testing numerical evidence. ALTERNATE HYPOTHESIS A statement that is concluded if the sample data provide sufficient evidence that the null hypothesis is false. 329 Important Things to Remember about H 0 and H 1 z H 0 : null hypothesis and H 1 : alternate hypothesis z H 0 and H 1 are mutually exclusive and collectively exhaustive z H 0 is always presumed to be true z H 1 has the burden of proof z A random sample ( n ) is used to “ reject H 0 ” z If we conclude 'do not reject H 0 ', this does not necessarily mean that the null hypothesis is true, it only suggests that there is not sufficient evidence to reject H 0 ; rejecting the null hypothesis then, suggests that the alternative hypothesis may be true. z Equality is always part of H 0 (e.g. “=” , “ ¡ ” , “ ¢ ”). “ £ ” “<” and “>” always part of H 1 329
"Proving" using Hypothesis Tests z If you REJECT the NULL, you conclude that there is significant evidence that the ALTERNATE is true. z If you DO NOT REJECT the NULL, you conclude that there is NOT significant evidence that the ALTERNATE is true. – Technically, you never really accept the NULL, you just fail to reject it . – This is similar to court where a person is declared "NOT GUILTY" which is not the same as "INNOCENT". z Note that ALL these "proofs" have a level of possible error associated with them.