“Statistical Treatment” Communication Reasearch 1 S.Y. 2013- 2014 T.F 7:00am – 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
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Graham Hole‚ Research Skills 2012: page 1 APA format for statistical notation and other things: Statistical abbreviations: ANCOVA ANOVA α β Analysis of Covariance Analysis of Variance alpha‚ the probability of making a Type 1 error in hypothesis testing beta‚ the probability of making a Type 2 error in hypothesis testing CI d d’ df confidence interval Cohen’s measure of effect size d-prime (a measure of sensitivity‚ used in Signal Detection
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Statistical Analysis The analysis of the data from the study of Barnes & Noble stores is in two stages‚ the descriptive study and inferential statistical study. Initially‚ the Team will distribute and collect the questionnaires. The use of classification will summarize the data and express it in the tabular form for better understanding of the data. For example‚ if the questionnaires consist of information from males and females‚ the data is putinto two categories and expressed
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459-463 Copyright 1983 by the American Psychological Association‚ Inc. Statistical Significance‚ Power‚ and Effect Size: A Response to the Reexamination of Reviewer Bias Bruce E. Wampold Department of Educational Psychology University of Utah Michael J. Furlong and Donald R. Atkinson Graduate School of Education University of California‚ Santa Barbara In responding to our study of the influence that statistical significance has on reviewers ’ recommendations for the acceptance or rejection
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Critical-Value Approach to Hypothesis Testing We often use inferential statistics to make decisions or judgments about the value of a parameter‚ such as a population mean. For example‚ we might need to decide whether the mean weight‚ μ‚ of all bags of pretzels packaged by a particular company differs from the advertised weight of 454 grams (g)‚ or we might want to determine whether the mean age‚ μ‚ of all cars in use has increased from the year 2000 mean of 9.0 years. One of the most commonly
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Essay 3 This essay provides an analysis of the variables‚ statistical tests and methods used in the assigned research paper. The level of significance and the strengths and limitations of the data collection process were also reviewed. This study had several variables. One major independent variable is the qualitative questionnaire that was verbally given. In this scenario the dependent variable would be the measurement of the data that was collected. The process of a cause-effect relationship
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Hypothesis Testing and Nursing Hypothesis testing is a method of making decisions using data from scientific study. In statistics‚ a result is called statistically significant if it has been predicted as unlikely to have occurred by chance alone‚ according to pre-determined threshold probability‚ the significance level. Statistical hypothesis tests define a procedure that controls (fixes) the probability of incorrectly deciding that a default position (null hypothesis) is incorrect based on how
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A hypothesis is a claim Population mean The mean monthly cell phone bill in this city is μ = $42 Population proportion Example: The proportion of adults in this city with cell phones is π = 0.68 States the claim or assertion to be tested Is always about a population parameter‚ not about a sample statistic Is the opposite of the null hypothesis e.g.‚ The average diameter of a manufactured bolt is not equal to 30mm ( H1: μ ≠ 30 ) Challenges the status quo Alternative never contains
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“Accept” the Null Hypothesis by Keith M. Bower‚ M.S. and James A. Colton‚ M.S. Reprinted with permission from the American Society for Quality When performing statistical hypothesis tests such as a one-sample t-test or the AndersonDarling test for normality‚ an investigator will either reject or fail to reject the null hypothesis‚ based upon sampled data. Frequently‚ results in Six Sigma projects contain the verbiage “accept the null hypothesis‚” which implies that the null hypothesis has been proven
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Chapter-11 Testing of Hypothesis: (Non-parametric Tests) Chapter-11: Testing of Hypothesis - (Non-parametric Tests) 2 11.1. Chi - square ( χ )Test / Distribution 2 11.1.1. Meaning of Chi - square ( χ )Test 2 11.1.2. Characteristics of Chi - square ( χ )Test 2 11.2. Types of Chi - square ( χ )Test / Distribution 2 11.2.1. Chi - square ( χ )Test for Population Variance 2 11.2.2. Chi - square ( χ )Test for Goodness-of-Fit 2 11.2.3. Chi - square ( χ )Test or Independence
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