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. Note:. In Chapter 8 we used methods of estimating the value of a parameter.. In this chapter, we are drawing inferences about the parameter by making decisions concerning the value of the parameter. Two 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.. 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?. 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 Correspondence concerning this article should be addressed to: Dieter Rasch, PhD, University of Life Sciences Vienna; email: renate-rasch@t-online.de Hypothesis testing and the error of the third kin 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 I. Terms, Concepts. A. In general, we do not know the true value of population parameters - they must be estimated. However, we do have hypotheses about what the true values are. B. The major Are the Results Convincing?. We keep talking about . statistical significance. .. Now that we know the standard deviation of a proportion, . we’re . really in business.. If a statistic we observe is more than 2 standard deviations from the proportion we expect, we are ready to say we have a statistically significant difference.. Inferential Statistics: Making inferences about populations based on samples. Chapter Outline. Hypothesis-Testing. One-Tailed and Two-Tailed Hypothesis Tests. Decision Errors. Decision Errors. When the right procedures lead to the wrong decisions. Quantitative techniques for Economic . Analysis . II. Preetha. Rachel George. Department of Statistics. Module IV. Testing of hypothesis. Statistical test of a hypothesis is a rule or procedure which makes one to decide about the acceptance or rejection of the hypothesis.. 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..