PPT-Hypothesis Testing · Remember

significant meant a result didnt happen by chance One of the most common questions in statistics is whether or not results are significant To see if a result is significant. Hypothesis. testing. The process of making judgments about a large group (population) on the basis of a small subset of that group (sample) is known as statistical inference.. Hypothesis testing, one of two fields in statistical inference, allows us to objectively assess the probability that statements about a population are true. . Statistics. Terms. Null hypothesis. – The claim being assessed in a hypothesis test is called the null hypothesis. . Usually, the null hypothesis is a statement of “no change from the traditional value,” “no effect,” “no difference,” or “no relationship.” . 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:. STAT 250. Dr. Kari Lock Morgan. SECTION 4.3. Significance level (4.3). Statistical conclusions (4.3). p-value and H. 0. If the p-value is small, then a statistic as extreme as that observed would be unlikely if the null hypothesis were true, providing significant evidence against H. b. elieve it (or not). Our belief decision must ultimately stand on three legs:. What does our general background knowledge and experience tell us (for example, what is the reputation of the speaker)?. 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. Review . Finish these analogies:. Natives are to the Europeans as ___________. a. re to _______________.. Europeans are to the Natives as___________. a. re to________________. . Analyze . and Synthesize. nd. type of formal statistical inference. Our goal is to assess the evidence provided by data from a sample about some claim concerning the population.. Remember: We are asking ourselves “What would happen if we repeated the sample or the experiment many times?”. 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. . 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. . Sample. , shape, location, and spread. Sample = make sure it's random, handle missing data (mcar, mar, nmar), imputation . methods. NMAR!. . Shape = Is the data skewed, normal, or flat? If normal then we can use statistical analysis for normal . 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 . 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