The T-TEST 1.0 INTRODUCTION The t-test was developed by W. S. Gossett‚ a statistician employed at the Guinness brewery. However‚ because the brewery did not allow employees to publish their research‚ Gossett’s work on the t-test appears under the name "Student". The t-test is sometimes referred to as "Student’s t-test." Gossett was a chemist and was responsible for developing procedures for ensuring the similarity of batches of Guinness. The t-test was developed as a way of measuring how closely
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40 hours per week. (mean=45.63‚ SD=10.63). The difference was significant (t=20.48‚ p<.001)The 95% confidence interval of the difference was between 5.09 and 6.17. Group Statistics Respondent’s sex N Mean Std. Deviation Std. Error Mean Hours per day watching TV Male 382 3.01 2.648 .135 Female 524 3.00 2.497 .109 Independent Samples Test Levene’s Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval
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Assessing T-tests To clearly identify what a t-test accomplishes in descriptive statistics it is imperative to understand what a t-test represents. A “t-test is a parametric statistical test for comparing the means of two independent samples” (Plichta & Kelvin‚ 2013‚ p. 464). Gosset developed the t-test for use in quality control at the Guinness Brewery and published his works under the pen name “Student” (Plichta & Kelvin‚ 2013). T-tests use assumptions related to the underlying
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STUDY FINDINGS Before comparing the group means‚ assumptions for the paired sample t-test were evaluated and no violations were noted. Results from the paired sample t-test revealed statistically significant differences (p <= .05) in student competency self-assessment between the pretest and the posttest‚ and the posttest and the retrospective test on all 19 competencies (Table 2). Cohen’s effect size values ranging from 0.51 to 2.30 suggested moderate or high practical significance. These findings
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T-test for Two Independent Samples * This test is used when only two unrelated groups are being compared and the measurements are either interval or ratio. The two groups may or may not have the same number of samples. * The t-test for two independent groups involves testing whether or not there is a significant difference between the population means of the two groups. Consider a study wherein the effectiveness of banana leaves as an organic wrapper was compared to that of aluminum foil
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The T-Distribution and T-Test “In probability and statistics‚ Student ’s t-distribution (or simply the t-distribution) is a continuous probability distribution that arises when estimating the mean of a normally distributed population in situations where the sample size is small” (Narasimhan ‚ 1996). Similar to the normal distribution‚ the t-distribution is symmetric and bell-shaped‚ but has heavier tails‚ meaning that it is more likely to produce values far from its mean. This makes the t-distribution
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Two-Sample t-Tests Connie Tyrone Walden University August 24‚ 2013 Two Sample t-Tests With this assignment‚ we are told about Martha. Martha wants to see if her relaxing technique which involves visualization will be able to assist people suffering with mild insomnia to fall asleep faster. She randomly selects 20 insomnia patients to participate in her research. She assigns 10 from the group to participate in visualization therapy and 10 from the group receives no treatment. Martha then
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Z –Test: a statistical test used for inference (inference – is the act or process of deriving logical conclusions from evidence‚ statements‚ ideas‚ etc. known or assumed to be true) which determines if the difference between a sample mean and the population mean is large enough to be statistically significant‚ that is‚ if it is unlikely to have occurred by chance. The Z – test is used primarily with its standardized testing to determine if the test scores of a particular sample of test takers are
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Group Statistics | | Gender | N | Mean | Std. Deviation | Std. Error Mean | Emotional Score | Boys | 175 | 10.9829 | 3.97329 | .30035 | | Girls | 120 | 13.9750 | 5.18152 | .47301 | Independent Samples Test | | Levene’s Test for Equality of Variances | t-test for Equality of Means | | F | Sig. | t | df | Sig. (2-tailed) | Mean Difference | Std. Error Difference | 95% Confidence Interval of the Difference | | | | | | | | | Lower | Upper | Emotional Score | Equal variances
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CHAPTER 10: TWO-SAMPLE TESTS WITH NUMERICAL DATA 1. The t test for the difference between the means of 2 independent populations assumes that the respective a) sample sizes are equal. b) sample variances are equal. c) populations are approximately normal. d) all of the above ANSWER: c TYPE: MC DIFFICULTY: Moderate KEYWORDS: pooled-variance t test‚ assumption 2. The t test for the mean difference between 2 related populations
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