PPT-Hypothesis Testing: Minding your Ps and Qs and Error Rates

Bonnie HalpernFelsher PhD Hypothesis Testing Hypothesis testing is the key to our scientific inquiry In additional to research hypotheses need statistical hypotheses I nvolves the statement of a null hypothesis . Professor William Greene. Stern School of Business. IOMS Department. Department of Economics. Statistics and Data Analysis. Part . 13 . – Statistical . Tests: 1. Statistical Testing. STAT 250. Dr. Kari Lock Morgan. SECTION 4.3, 4.5. Type I and II errors (4.3). Statistical versus practical significance (4.5). Multiple testing (4.5). There are four possibilities:. Errors. Reject H. Hypothesis Testing. Test of hypothesis - Test whether a population parameter is less than, equal to, or greater than a specified value.. Remember an inference without a measure of reliability is little more than a guess.. VON CHRISTOPHER G. CHUA, LPT, MST. Affiliate, ESSU-Graduate School. MAED 602: STATISTICAL METHODS. Session Objectives. In this fraction of the course on Statistical Methods, graduate students enrolled in the subject are expected to do the following:. Ho - this hypothesis holds that if the data deviate from the norm in any way, that deviation is due strictly to chance.. Alternative hypothesis. Ha - the data show something important.. Doing decision = accept/reject Ho (the decision centers around null hypothesis). Inferential statistics. :. Based on laws of probability. Used to estimate population parameters from sample statistics . When different researchers apply inferential statistics to the same data resulting conclusions likely to be the same. Test of hypothesis - Test whether a population parameter is less than, equal to, or greater than a specified value.. Remember an inference without a measure of reliability is little more than a guess.. Writing a Hypothesis. Quick Questions. What do we remember about testable questions?. What is a hypothesis?. What do hypotheses have in common with testable questions?. How do we write a hypothesis?. Q. uestion. R. andom guess. Observation. Experiment. Your mom. A . hypothesis is:. A . tentative explanation . for an observation or a scientific problem that can be tested by further investigation. . Evaluating Differences and Changes. “Our overall customer satisfaction score increased from 92 percent 3 months ago to 93.5 percent today.” . Did customer satisfaction really increase? Should we celebrate?. A nuclear power plant adjacent to a residential area. STATISTICS FOR BUSINESS. (Hypothesis testing for a single population). A nuclear power plant. adjacent to a residential area. Two . local . residents die . Type I & II Error and Test of 1 &2 Tailed Hypothesis Khagendra Kumar Dept. of Education Patna University Decision Making on Accepting & Rejecting Hypotheses  To take decision for accepting or Frances Chumney, PhD CONTENT OUTLINE  Logic of Hypothesis Testing  Error & Alpha  Hypothesis Tests  Effect Size  Statistical Power HYPOTHESIS TESTING 2 HYPOTHESIS TESTING LOGIC OF HYPOT In . statistics. , a . Type I error.  is a false positive conclusion, while a . Type II error.  is a false negative conclusion.. The probability of making a Type I error is the significance level, or alpha (α), while the probability of making a Type II error is beta (β). These risks can be minimized through careful planning in your study design..