Publications by Mary Adepoju
Assignment 2
Flipped Assignment #3 The data used on this assignment is retrieved from a raw github file. The data contains the beats and temperature of males and females. In the data a ‘1’ in the gender column represents a male and a ‘2’ represents a female. Entries 1 through 65 are males and entries 66 through 130 are females dat<-read.csv("https://r...
2040 sym R (1547 sym/15 pcs) 5 img
Typesetting with RMarkdown
You can put chunks of R code by putting three backticks at the beginning and end of the chunk. You need to give each chunk a unique name in s the {} Echo The echo command tell R whether or not to print the code that generated the results. The default option is echo = TRUE. TRUE = code & results False = just results Here is an example with echo=F...
2402 sym R (1737 sym/9 pcs) 1 img
Flipped Assignment 5
Question 1: One method for assessing the bioavailability of a drug is to note its concentration in blood and/or urine samples at certain periods of time after the drug is given. Suppose we want to compare the concentrations of two types of aspirin (types A and B) in urine specimens taken from the same person 1 hour after he/ she has taken the dru...
2607 sym R (884 sym/4 pcs)
Flipped Assignment 6
Question 1 asprinA <- c(15,26,13,28,17,20,7,36,12,18) asprinB <- c(13,20,10,21,17,22,5,30,7,11) a. Alternate Hypothesis: \(H_o: \mu_1 = \mu2\) \(H_a: \mu_1\neq \mu_2\) \(mu_1\) = Aspirin A \(mu_2\) = Aspirin B b. Hypothesis Testing boxplot(asprinA, asprinB) t.test(asprinA, asprinB, alternative = "two.sided", paired =TRUE, var.equal= TRUE) ## ...
1157 sym R (1909 sym/11 pcs) 1 img
Homework 2
2.32 caliper1 <-c(0.265,0.265,0.266,0.267,0.267,0.265,0.267,0.267,0.265,0.268,0.268,0.265) caliper2 <-c(0.264,0.265,0.264,0.266,0.267,0.268,0.264,0.265,0.265,0.267,0.268,0.269) t.test(caliper1,caliper2,alternative = "two.sided", paired = FALSE) ## ## Welch Two Sample t-test ## ## data: caliper1 and caliper2 ## t = 0.40519, df = 19.559, ...
1417 sym R (2479 sym/13 pcs) 4 img
Homework 4
Question 3.7 mt1 <- c(3129, 3000, 2865, 2890) mt2 <- c(3200, 3300, 2975, 3150) mt3 <- c(2800, 2900, 2985, 3050) mt4 <- c(2600,2700,2600,2765) combinedGroups <- data.frame(cbind(mt1,mt2,mt3,mt4)) stackedGroups <- stack(combinedGroups) dat <- aov(values~ind, data = stackedGroups) #summary(dat) c. \[ LSD = t_{\frac{\alpha}{2},df} \sqrt{\fra...
1565 sym R (809 sym/20 pcs) 8 img
Homework 5- Week 6
Question 3.23 ft1 <- c(17.6, 18.9, 16.3, 17.4, 20.1, 21.6) ft2 <- c(16.9, 15.3, 18.6, 17.1, 19.5, 20.3) ft3 <- c(21.4, 23.6, 19.4, 18.5, 20.5, 22.3) ft4 <- c(19.3, 21.1, 16.9, 17.5, 18.3, 19.8) fluidType <- cbind(ft1,ft2,ft3,ft4) combinedGroups <- data.frame(fluidType) stackedGroups <- stack(combinedGroups) dat <- aov(values~ind, data = st...
2125 sym R (3096 sym/28 pcs) 18 img
Week 7 - Homework 6
4.3 : Chemical and Bolt Block Design Hypothesis: \(H_o: \tau_i = 0\) for all \(i\) \(H_a: \tau_i \neq 0\) for some \(i\) obs<-c(73,68,74,71,67, 73,67,75,72,70, 75,68,78,73,68, 73,71,75,75,69) chemical<-c(rep(1,5),rep(2,5),rep(3,5),rep(4,5)) bolt<-c(seq(1,5),seq(1,5),seq(1,5),seq(1,5)) bolt<-as.fixed(bolt) chemical<-a...
1135 sym R (1566 sym/6 pcs)
Week 10 - Homework
5.4: Feed Rate and Depth of Cut Block Experiment Hypothesis: \[ \\ H_o:\alpha_i = 0 \;\; H_a: \alpha_i \neq 0 \\ H_o:\beta_j = 0 \;\; H_a: \beta_j \neq 0 \\ H_o:\alpha\beta_{ij} = 0 \;\; H_a: \alpha\beta_{ij} \neq 0 \] ## Analysis of Variance Table ## ## Response: responses ## Df Sum Sq Mean Sq F value Pr(>F) ...
2016 sym R (4645 sym/5 pcs) 5 img
Week 12 Homework
7. 12 Tennis Block Factorial Design FactorR A: 10 ft = -1, 30 ft = 1 Factor B: Length of Putter mallet = 1, cavity-back = -1 Factor C: Type of Putter straight = -1, breaking = 1 Factor D: Break of Putter level = -1, downhill = 1 ## Analysis of Variance Table ## ## Response: distance ## Df Sum Sq Mean Sq F value Pr(>F) ...
473 sym R (4530 sym/3 pcs) 2 img