Hypothesis Testing The sole purpose of hypothesis testing is to determine whether or not research that has been collected is proved or disproved; usually allowing up to a 5% error factor. By using this 5% margin of error a researcher can consider the question of research being conducted is proven. There are five steps to be followed in doing hypotheses testing. The steps are: developing the research question‚ specifying between null and alternative hypotheses‚ calculating the statistic‚ computing
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procedure. • Distinguish between a one-tailed and a two-tailed test of hypothesis. • Conduct a test of hypothesis about a population mean. • Conduct a test of hypothesis about a population proportion. • Define Type I and Type II errors. • Compute the probability of a Type II error. Hypothesis‚ Hypothesis and Testing HYPOTHESIS A statement about the value of a population parameter developed for the purpose of testing. HYPOTHESIS TESTING A procedure based on sample evidence and probability
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ECONOMICS 140 Professor Glenn Woroch 2/3/09 Lecture 5 ASUC Lecture Notes Online is the only authorized note-taking service at UC Berkeley. Do not share‚ copy or illegally distribute (electronically or otherwise) these notes. Our student-run program depends on your individual subscription for its continued existence. These notes are copyrighted by the University of California and are for your personal use only. ANNOUNCEMENTS First problem set is due this Thursday Feb. 5th in lecture
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Hypothesis Testing Hypothesis Testing In today’s world of statistical research there is a multitude of ways to make new discoveries and formulate new ideas; one way to accomplish this is for researchers to have inquiring minds that need to have their questions answered. To do this they must develop their hypothesis. Then researchers can develop a verbal and numerical hypothesis in which they will be able to test this hypothesis. In patients with Attention Deficit Hyperactivity Disorder (ADHD)
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are the automatically computed results of your exam. Grades for essay questions‚ and comments from your instructor‚ are in the "Details" section below. Date Taken: 6/11/2012 Time Spent: 01 min ‚ 13 secs Points Received: 21 / 60 (35%) Question Type: # Of Questions: # Correct: Multiple Choice 13 9 Short 5 N/A Grade Details Page: 1 2 1. Question : (TCO 11) Define point estimate. Student Answer: Approximation of a single quantity or a single numerical value‚ instead of that of a
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analyzed by partial correlation: What is the effect of job satisfaction on salary‚ type of education‚ gender‚ and smoker‚ factoring out age? Is there an affect of electrical appliances on contraceptive use‚ removing the effect of education? Is there an effect on prep hours and SAT scores‚ factoring the effect of GPA? 3. Variables From the research questions above‚ the first one has IVs to be salary‚ type of education‚ gender‚ and smoker‚ and the dependent variable DV is job satisfaction.
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– 8:30am MCS June 21‚ 2013 ILARIA L. PANDOLFI PROFESSOR ROSALIE CERVANTES I. Objectives: The learners are expected to: a. Determine what statistical treatment is all about. b. Choose their own right statistics in analysing their data. c. Follow the steps involving statistical treatment. d. Interpret the data involving tabulation. e. Provide answers to the drills. II. Outline of Content: A. Statistical treatment of data. B. Treatment of Data and Distribution
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observation and derive and write and formulized hypothesis (Formalized Hypotheses example: If skin cancer is related to ultraviolet light ‚ then people with a high exposure to uv light will have a higher frequency of skin cancer). There are three types of scientific statements: there are Hypothesis‚ Law and Theory. A hypothesis will give a plausible explanation that will be tested. It can also explain future phenomenon that will need to be tested. Once a hypothesis has been widely accepted‚ it is
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alternative may be stated in terms of a confidence level (denoted X%). The confidence level is often specified before a test is conducted as part of a sample size calculation. We view the confidence level as equaling one minus the Type I error rate (α). A Type I error is committed when the null hypothesis is incorrectly rejected. An α value of 0.05 is typically used‚ corresponding to 95% confidence levels. The p-value is used to determine if enough evidence exists to reject the null hypothesis
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TRADE-OFFS The concept of trade-offs is a basic principle in economics that arises from the idea that resources are scarce. As a general principle‚ trade-off analysis shows that for a given set of resources and technology‚ to obtain more of a desirable outcome of a system‚ less of another desirable outcome is obtained (Stoorvogel et al.‚ 2004a). Although there can be win–win outcomes in two dimensions‚ even such a win–win must come at the expense of some other desired attribute. This concept is
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