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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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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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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Conducting a z-Test Psychological Statistics Module 2: Assignment 2 Argosy University Gemini Dickerson 3/12/14 A film was shown to 36 students to see if the attitudes of students toward the mentally ill would change. The results of the class of 36 that watched the film had a score of 70. The results of the class that did not watch the film had a score of 75. The standard deviation is 12. When the alpha is set to 0.05. .05 is a mid-probability. It means we’re using to reduce the likelihood
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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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When to use each test? What is the sig value? Whether or not it is significant? Read output and tell you what that value means (significant or not) One sample: given population value and compare your sample to that population Know if its significant: analyze compare means‚ one sample t-test Independent sample t-test: lab one against lab five Two independent groups (compare their means) Significance use twotail Define the correct groups: Paired sample: only care about one lab and you look at before
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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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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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Statistics in modern business environment Due to advanced communication network‚ rapid changes in consumer behaviour‚ varied expectations of variety of consumers and new market openings‚ modern managers have a difficult task of making quick and appropriate decisions. Therefore‚ there is a need for them to depend more upon quantitative techniques like
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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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