Publications by Mr. Hern
Homework 5.2 Key
Introduction In this homework we continue our exploration of ANOVA (short for ANalysis Of VAriance) testing. Four Treatments, No Waiting: Questions 1 - 6 An ANOVA has been carried out comparing four treatment conditions with 25 participants in each condition. Question 1 Fill in all the missing values in the source table below. Hint: start with df...
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Lesson Check 5.2 Key
Introduction In this lesson check we expand our array of tests and techniques to include ANOVA (short for ANalysis Of VAriance). ANOVA is most helpful when dealing with more than two independent groups, and we learn how to execute and assess a one-way (or single-factor) ANOVA in such a setting. Question 1 ANOVA is an appropriate statistical measur...
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R Homework 4 Key
In this R homework assignment, we use the KarloffU dataset to further explore the process of statistical inference and hypothesis testing. The two research questions will give us opportunities to stretch our understanding of the applicability of the one-sample t-test and to extend our R skills in handling a slightly more complex data scenario. Res...
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R Homework 3 Key
In this R homework assignment, we use the KarloffU dataset to further explore the use of z-scores and the attendant percentiles to analyze normally distributed variables. Research Question 1: Analyze follow-up visit temperatures for upperclassmen at KarloffU’s health clinic and determine the values at the 25th and 75th percentiles. Preparation ...
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R Homework 2 Key
In this R homework assignment, we use the KarloffU dataset to analyze various subsets of data and identify the distribution type for specific variables. Research Question 1 Analyze distribution characteristics of subsets of students at KarloffU’s health clinic by class and by gender. Preparation To kick things off, we simply import the KarloffU...
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R Homework 1 Key
In this R homework assignment, we use the KarloffU dataset to create subsets to enable basic quantitative queries. Preparation Our first step will be to import the KarloffU.csv and name it “ku.” All our subsequent analysis will use ku as a base. ku <- read.csv("/cloud/project/OnRamps Data/KarloffU.csv") #View(ku) Research Question Create simp...
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Level 2 Lab 5.1 Key
In this lab, we again use the BullRider dataset to continue to explore the process of statistical inference and hypothesis testing; specifically whether the point totals in 2014 for riders with 10+ years of experience differed from the point totals for riders with less than 10 years of experience. Since a rider cannot have both more than 10 years e...
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Lab 3.3 Key
In this lab, we use an interactive Shiny App simulation in RStudio to visualize the concepts brought forward in Lesson 3.3 regarding sampling distributions and the Central Limit Theorem. Lab Question How do sampling distributions compare to an original population distribution? The bulk of the work on this lab will involve the Lesson 3.3 Shiny App,...
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Homework 4.3 Key
Agoraphobia: Questions 1 - 8 We created an agoraphobia dataset mirroring that in the homework to enable the use of R to directly (instead of manually) calculate the requested values. to respond to the first 8 questions. agoraphobia <- read.csv("/cloud/project/HomeworkData/agoraphobia.csv") Question 1 What is the average difference score for this s...
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Level 2 Lab 5.1
In this lab, we again use the BullRider dataset to continue to explore the process of statistical inference and hypothesis testing; specifically whether the point totals in 2014 for riders with 10+ years of experience differed from the point totals for riders with less than 10 years of experience. Since a rider cannot have both more than 10 years e...
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