Publications by April Mae Tabonda
PLP_11 site
Site vs. Count ANOVA rm(list=ls()) setwd("C:/Users/April Mae Tabonda/Documents/MS Marine Science/Biostat/PLP/RMDs/PLP_11 Project") getwd() ## [1] "C:/Users/April Mae Tabonda/Documents/MS Marine Science/Biostat/PLP/RMDs/PLP_11 Project" sample.data<-read.csv("count.csv", header=TRUE, sep=";") str(sample.data) ## 'data.frame': 213 obs. of 6 va...
35 sym R (21429 sym/27 pcs) 10 img
PLP_11 depth
Table of Contents PLP No.1: Class Expectations, Joy of Statistics, History of Statistics————————— 1 PLP No.2: Research Design———————————————————————— 3 PLP No.3: Critique of Journal Article———————————————————— 6 PLP No.4: Intro to R and R...
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PLP_11 coral vs count
rm(list=ls()) setwd("C:/Users/April Mae Tabonda/Documents/MS Marine Science/Biostat/PLP/RMDs/PLP_11 Project") getwd() ## [1] "C:/Users/April Mae Tabonda/Documents/MS Marine Science/Biostat/PLP/RMDs/PLP_11 Project" sample.data<-read.csv("coral.csv", header=TRUE, sep=";") str(sample.data) ## 'data.frame': 81 obs. of 7 variables: ## $ ï..DAT...
11 sym R (11187 sym/24 pcs) 9 img
PLP_4 Intro to R and R Markdown
Intro to R R is a project by Ross Ihaka and Robert Gentleman during 1990s. It is simply a text file containing a set of commands and comments, which can be saved and used for re-execution, as well as modification and editing of commands that is interpreted by the computer (https://www.oreilly.com/library/view/hands-on-programming-with/97814493590...
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PLP_1 Class Expectations
Class Expectations During our first meeting in Biostat course, each one of us was required to answer the following questions given by our professor in order to assess our understanding and knowledge regarding statistics on a 1/2 sheet of pad paper. Some of the questions were about our understanding of what statistics is, whether we have taken it ...
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PLP_12 Reflection
The first thing that came to my mind when I enroll in Biostat course was to deal with lots of computations, numbers, complex formulas, and etc. However, as we tackle on the different lessons on Biostat, I learned to appreciate it, and I was able to get lots of techniques and ideas which I can apply in my own research topic. Especially when we did...
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PLP_9 Correlation
For this exercise, the data from the survey obtained from MS398 (Biostatistics) students from 2010 and 2016 shall be used. First, we clean up the R environment to ensure that we will be running the correct dataset in our downstream analysis. rm(list=ls()) Step 1: Open data file and create the data project We will then set our work directory. This...
2757 sym R (6582 sym/46 pcs) 13 img
PLP_10 Simple linear regression
Simple Linear Regression Linear regression models are used to show or predict the relationship between two variables or factors which are the dependent variable and independent variable. Simple Linear Regression Analysis is the simplest form of regression analysis which uses one dependent variable and independent variable, and a straight line app...
3117 sym R (91185 sym/132 pcs)
PLP_8 ANOVA
Single factor ANOVA with Tukey’s test Reset R’s memory using the code below. rm(list=ls()) The codes below helps in telling the R where to look for the data that will be used in this activity. setwd("C:/Users/April Mae Tabonda/Documents/MS Marine Science/Biostat/PLP/RMDs/PLP_8 ANOVA") getwd() ## [1] "C:/Users/April Mae Tabonda/Documents/MS M...
2674 sym R (5456 sym/31 pcs) 9 img
PLP_7 T-test Example: Non-Parametric
Sokal and Rohlf (1997) presented a dataset comprising the lengths of cheliceral bases (in um) from two samples of chigger (Trombicula lipovskyi) nymphs. These data were used to illustrate two equivalent tests (Mann-Whitney U-test and Wilcoxon two-sample test) of location equality (Box 13.7 of Sokal and Rohlf (1997)). Reset R’s memory rm(list=ls...
1256 sym R (1641 sym/17 pcs) 1 img