PPT-Statistics and Hypothesis Testing in Science

Allen Mincer New York University July 2019 1 BNL June 2019 On Statistics Mark Twain popularized the saying see end of quote in Chapters from My Autobiography published in the North American Review in 1906 Figures often beguile me he wrote particularly when I have the arranging of them myself in which case the remark attributed to Disraeli would often apply with justice and force There are three kinds of lies lies damned lies and statistics . 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. . **You’re not really Dummies**. Before Starting. Disclaimer: . We can’t teach a whole quarter of statistics, but we can teach you how to study. Studying . for statistics requires reading the book!. Dr. Surej P John. Definition of Variables. A variable is an attribute of a person or an object that varies.. Measurement are rules for assigning numbers to objects to represent quantities of attributes.. +. Probability. Seminar 6. A difficult mock question for mid-term. Plot . the following graph. People . who use Facebook only (but not Twitter) are generally happier than those who use Twitter only (but not Facebook). This . STAT 250. Dr. Kari Lock Morgan. SECTION 4.1. Hypothesis test. . Null and alternative hypotheses. . Statistical significance. Tea and the Immune System. L-. theanine. is an amino acid found in tea. 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). 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.. Hypothesis Testing. A statement has been made. We must decide whether to . 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)?. 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?. 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 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.. Dr David Butler. Maths Learning Centre. University of Adelaide. Semester 1 2022. Research and Critical Appraisal. You NEED statistics because things VARY. You want to:. d. escribe how things vary. figure out what is usual.