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General Psychology 1
General Psychology 1

Engineering Statistics Chapter 4 Hypothesis Testing
Engineering Statistics Chapter 4 Hypothesis Testing

Chapter 5 Slides
Chapter 5 Slides

... proportions is example of CLT (X=S1+…+Sn) • Any linear function of independent normal random variables is normal (use rules on means and variances to get parameters of distribution) • Generalizations of CLT apply to cases where random variables are correlated (to an extent) and ...
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Chapter 11

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Lecture 16: Chapter 10 Mastery/Test 3 Review

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Exploratory data analysis: numerical summaries

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Dep t - Practice Exercise - KEY

... 3. Using the Table of Critical Values of Student’s t Distribution – what would the t critical value (tcrit) be for dependent-samples t -test: With df = 44 – for a two-tailed test using α = .05, tCV = +2.021 We used df = 40 since there was not a df = 44 – to error on the side of being more conservati ...
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MATH 1342Summer 1 - HCC Learning Web

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+ The Sampling Distribution of a Difference Between Two Means

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Chapter 9

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AMS 315/576 Lecture Notes Chapter 5

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Chapter 9

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Quick links

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Comparing Two Population Parameters

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1 Reminder of Definitions 2 Unknown Population Standard

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Comparing Two Population Means

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Final Exam Review

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Session Slides/Handout

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Bio-Statistics Test of Hypotheses Exercises

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Lecture Notes for Week 13

< 1 ... 220 221 222 223 224 225 226 227 228 ... 280 >

Student's t-test

A t-test is any statistical hypothesis test in which the test statistic follows a Student's t-distribution if the null hypothesis is supported. It can be used to determine if two sets of data are significantly different from each other, and is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic were known. When the scaling term is unknown and is replaced by an estimate based on the data, the test statistic (under certain conditions) follows a Student's t distribution.
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