PPT-Hypothesis Tests One Sample Proportion

What is hypothesis testing A statistical hypothesis is an assumption about a population parameter This assumption may or may not be true The best way to determine whether a statistical hypothesis is true would be to examine the entire population Since that is often impractical researchers typically examine a random sample from the population . Introducing Hypothesis Tests. Review. A 99% confidence interval is . wider than a 95% confidence interval. . narrower than a 95% confidence interval. . the same width as a 95% confidence interval. . Inferential Statistics: . Using the sample statistics to infer . (to) . population parameters.. Modular Course 5. . Summary or Descriptive Statistics: . Numerical and graphical summaries of data.. Presented by :Dr. . Reshma.S. . Moderator : Dr. . Subodh. S Gupta. Why do we need sample size calculation?. When should we calculate sample size?. Basic principles for sample size calculation. Derivation of sample size formula. +. 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 . 2015-2016. Overview. L.C. O.L.. Sampling variability. Confidence intervals for population proportion.. Hypothesis testing using confidence intervals. L.C. H.L.. Normal distribution. Sampling variability. Section 5.4. Testing Hypotheses. about Proportions. 1. Example. Cellphone companies have discovered that college students, their biggest customers, have difficulty setting up all the features of their smart phones, so they have developed what they hope are simpler instructions.. STAT 101. Dr. Kari Lock Morgan. SECTION 4.1. Statistical test. . Null and alternative hypotheses. . Statistical significance. Review of Last Class. The standard error of a statistic is the standard deviation of the sample statistic, which can be estimated from a bootstrap distribution. 1. Contents:. Tests of significance for small samples. Student’s t- test. Properties of t-Distribution. The t- table. Application of the t-Distribution. To test the significance of . Mean of a random sample. 2/29/12. Single Proportion, . p. . Distribution. Intervals and tests. Difference in proportions, . p. 1. – p. 2. . One proportion or two?. Distribution. Intervals and tests. Section 6.1, 6.2, 6.3, 6.7, 6.8, 6.9. 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?”. Chapter 9 Tests of Hypotheses for a Single Sample Applied Statistics and Probability for Engineers Sixth Edition Douglas C. Montgomery George C. Runger Chapter 9 Title and Outline 9 Tests of Hypotheses for a Single Sample 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 Another dummy variable coding scheme. Contrasts. Multiple comparisons. Interactions. One. -factor . Analysis of variance. Categorical . Explanatory variable. Quantitative . Response variable. p. categories (groups). Tests of significance for small samples. Student’s t- test. Properties of t-Distribution. The t- table. Application of the t-Distribution. To test the significance of . Mean of a random sample. Means of two samples (independent).