Publications by Winelyn Pelias
STAT 56 - FINAL EXAM
1. Describe two (2) research scenarios where cluster analysis may be used as the data analysis strategy. A company wants to launch a new product, and it first needs to identify its target market. By conducting a cluster analysis on its customer data (considering variables such as age, income, past purchasing behavior, geographical location, et...
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STAT 54 - FINAL EXAM
1. A researcher conducts a study to evaluate whether the distribution of the length of time it takes migraine patients to respond to a 100 mg. dose of an intravenously administered drug is normal, with a mean response time of 90 seconds and a standard deviation of 35 seconds (i.e., μ = 90 and σ = 35). The amount of time (in seconds) that ela...
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Canonical Correlation Analysis
CANONICAL CORRELATION ANALYSIS Example of canonical correlation analysis: A researcher has collected data on three psychological variables, four academic variables (standardized test scores) and gender for 600 college freshman. She is interested in how the set of psychological variables relates to the academic variables and gender. In particular...
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Multivariate Analysis of Variance (MANOVA)
MANOVA in R: Implementation As with most of the things in R, performing a MANOVA statistical test boils down to a single function call. But we’ll need a dataset first. The Iris dataset is well-known among the data science crowd, and it is built into R: It doesn’t matter if you use the same dataset as us, as long as one critical condition i...
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Friedman Test in R
Friedman Test in R Data Preparation We’ll use the self esteem score dataset measured over three time points. The data is available in the datarium package. Gather columns t1, t2 and t3 into long format. Convert id and time variables into factor (or grouping) variables: Summary Statistics Compute some summary statistics of the self-esteem...
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Discriminant Analysis
Cluster Analysis in R Getting Data mydata <- read.csv("D:/Stat 56/Data.txt", header=T) str(mydata) 'data.frame': 22 obs. of 9 variables: $ Company : chr "Arizona " "Boston " "Central " "Commonwealth" ... $ Fixed_charge: num 1.06 0.89 1.43 1.02 1.49 1.32 1.22 1.1 1.34 1.12 ... $ RoR : num 9.2 10.3 15.4 11.2 8.8 13.5 12.2 9....
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Cluster Analysis
Data Preparation The built-in R dataset USArrests is used: Murder Assault UrbanPop Rape Alabama 1.24256408 0.7828393 -0.5209066 -0.003416473 Alaska 0.50786248 1.1068225 -1.2117642 2.484202941 Arizona 0.07163341 1.4788032 0.9989801 1.042878388 Arkansas 0.23234938 0.2308680 -1.0735927 -0.184916602 Califo...
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Midterm Exam - Part 2
DATA 1. What is the socio- demographic profile of the respondents in terms of: 1.1 Age 1.2 Sex 1.3 Number of years 1.4 Socio-economic status 2. What is the psychological well-being of the students raised by single parents in terms of: a. Autonomy b. Environmental Mastery c. Personal growth d. Positive relations e. Purpose in life f....
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Midterm Exam - Stat56
DATA 1. Provide the output of the standardized data (just the first 10 rows). 2. Provide the correlation matrix of the standardized data. top incisor bottom incisor top cannine bot cannine top premol top incisor 1.00000000 -0.07181198 0.6001764 0.7431854 0.5065222 bottom incisor -0.07181198 1.00000000 0.501983...
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Additional Activity for Factor Analysis
DATA Describing the Data We look at the dataset before we run any analysis. We use the dim function to retrieve the dimension of the dataset. [1] 329 10 Cleaning Data In our data frame, we have a V10 variable in the last column. So, we can use -10 in the column index to remove the last column and save our data to a new object. V1 V2 ...
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