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assignment 8 team 13 #38

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2 changes: 1 addition & 1 deletion Link for the presentation
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https://drive.google.com/open?id=1VyMeCv4LojqMLf1YIj3LbU3E3wNar5WC
https://youtu.be/WgXDINp60vE
173 changes: 173 additions & 0 deletions R code for assignment 8.Rmd
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---
title: "assignment 8"
output:
html_document: default
pdf_document: default
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r}
library(dplyr)
library(tidyverse)
library(tidyr)
library(GGally)
```

```{r}
library(ggplot2)
library(dplyr)
#The measured X and Y linear accelerations determine the position of the ball along the X and Y axes. The Z acceleration determines the height of the ball, as indicated by the ball radius and the square bracket (marked Z).
GH1 <- read.csv("~/Desktop/master fall/assignment8/gh 1- before.csv")
GH2 <- read.csv("~/Desktop/master fall/assignment8/gh2-after.csv")
ggplot(GH1, aes(x=time_tick)) + geom_line(aes(y=lac_X_value,color ="han ge x-axis"))+geom_line(aes(y=lac_Y_value,color ="han ge y-axis"))+geom_line(aes(y=lac_Z_value,color="han ge z-axis"))
ggplot(GH2, aes(x=time_tick)) + geom_line(aes(y=lac_X_value,color ="han ge x-axis"))+geom_line(aes(y=lac_Y_value,color ="han ge y-axis"))+geom_line(aes(y=lac_Z_value,color="han ge z-axis"))

```

```{r}
CWJ1 <- read.csv("~/Desktop/master fall/assignment8/cwj1.csv")
CWJ2 <- read.csv("~/Desktop/master fall/assignment8/cwj2.csv")
ggplot(CWJ1, aes(x=time_tick)) + geom_line(aes(y=lac_X_value,color ="CWJ x-axis"))+geom_line(aes(y=lac_Y_value,color ="CWJ y-axis"))+geom_line(aes(y=lac_Z_value,color="CWJ z-axis"))
ggplot(CWJ2, aes(x=time_tick)) + geom_line(aes(y=lac_X_value,color ="CWJ x-axis"))+geom_line(aes(y=lac_Y_value,color ="CWJ y-axis"))+geom_line(aes(y=lac_Z_value,color="CWJ z-axis"))
```

```{r}
YCH1 <- read.csv("~/Desktop/master fall/assignment8/ych - before.csv")
YCH2 <- read.csv("~/Desktop/master fall/assignment8/ych - after.csv")
ggplot(YCH1, aes(x=time_tick)) + geom_line(aes(y=lac_X_value,color ="YCH x-axis"))+geom_line(aes(y=lac_Y_value,color ="YCH y-axis"))+geom_line(aes(y=lac_Z_value,color="YCH z-axis"))
ggplot(YCH2, aes(x=time_tick)) + geom_line(aes(y=lac_X_value,color ="YCH x-axis"))+geom_line(aes(y=lac_Y_value,color ="YCH y-axis"))+geom_line(aes(y=lac_Z_value,color="YCH z-axis"))
```


```{r}
ERIC1 <- read.csv("~/Desktop/master fall/assignment8/eric before.csv")
ERIC2 <- read.csv("~/Desktop/master fall/assignment8/eric - after.csv")
ggplot(ERIC1, aes(x=time_tick)) + geom_line(aes(y=lac_X_value,color ="ERIC x-axis"))+geom_line(aes(y=lac_Y_value,color ="ERIC y-axis"))+geom_line(aes(y=lac_Z_value,color="ERIC z-axis"))
ggplot(ERIC2, aes(x=time_tick)) + geom_line(aes(y=lac_X_value,color ="ERIC x-axis"))+geom_line(aes(y=lac_Y_value,color ="ERIC y-axis"))+geom_line(aes(y=lac_Z_value,color="ERIC z-axis"))
```

```{R}
GH1 <- abs(GH1)
GH2 <- abs(GH2)
mean.gh1 <- c(mean(GH1$lac_X_value),mean(GH1$lac_Y_value),mean(GH1$lac_Z_value))
var.gh1 <- c(var(GH1$lac_X_value),var(GH1$lac_Y_value),var(GH1$lac_Z_value))
sd.gh1 <- sqrt(var.gh1)
mean.gh1
var.gh1
sd.gh1
mean.gh2 <- c(mean(GH2$lac_X_value),mean(GH2$lac_Y_value),mean(GH2$lac_Z_value))
var.gh2 <- c(var(GH2$lac_X_value),var(GH2$lac_Y_value),var(GH2$lac_Z_value))
sd.gh2 <- sqrt(var.gh2)
mean.gh2
var.gh2
sd.gh2
```

```{R}
CWJ1 <- abs(CWJ1)
CWJ2 <- abs(CWJ2)
mean.CWJ1 <- c(mean(CWJ1$lac_X_value),mean(CWJ1$lac_Y_value),mean(CWJ1$lac_Z_value))
var.CWJ1 <- c(var(CWJ1$lac_X_value),var(CWJ1$lac_Y_value),var(CWJ1$lac_Z_value))
sd.CWJ1 <- sqrt(var.CWJ1)
mean.CWJ1
var.CWJ1
sd.CWJ1
mean.CWJ2 <- c(mean(CWJ2$lac_X_value),mean(CWJ2$lac_Y_value),mean(CWJ2$lac_Z_value))
var.CWJ2 <- c(var(CWJ2$lac_X_value),var(CWJ2$lac_Y_value),var(CWJ2$lac_Z_value))
sd.CWJ2 <- sqrt(var.CWJ2)
mean.CWJ2
var.CWJ2
sd.CWJ2
```

```{R}
YCH1 <- abs(YCH1)
YCH2 <- abs(YCH2)
mean.YCH1 <- c(mean(YCH1$lac_X_value),mean(YCH1$lac_Y_value),mean(YCH1$lac_Z_value))
var.YCH1 <- c(var(YCH1$lac_X_value),var(YCH1$lac_Y_value),var(YCH1$lac_Z_value))
sd.YCH1 <- sqrt(var.YCH1)
mean.YCH1
var.YCH1
sd.YCH1
mean.YCH2 <- c(mean(YCH2$lac_X_value),mean(YCH2$lac_Y_value),mean(YCH2$lac_Z_value))
var.YCH2 <- c(var(YCH2$lac_X_value),var(YCH2$lac_Y_value),var(YCH2$lac_Z_value))
sd.YCH2 <- sqrt(var.YCH2)
mean.YCH2
var.YCH2
sd.YCH2
```

```{R}
ERIC1 <- abs(ERIC1)
ERIC2 <- abs(ERIC2)
mean.ERIC1 <- c(mean(ERIC1$lac_X_value),mean(ERIC1$lac_Y_value),mean(ERIC1$lac_Z_value))
var.ERIC1 <- c(var(ERIC1$lac_X_value),var(ERIC1$lac_Y_value),var(ERIC1$lac_Z_value))
sd.ERIC1 <- sqrt(var.ERIC1)
mean.ERIC1
var.ERIC1
sd.ERIC1
mean.ERIC2 <- c(mean(ERIC2$lac_X_value),mean(ERIC2$lac_Y_value),mean(ERIC2$lac_Z_value))
var.ERIC2 <- c(var(ERIC2$lac_X_value),var(ERIC2$lac_Y_value),var(ERIC2$lac_Z_value))
sd.ERIC2 <- sqrt(var.ERIC2)
mean.ERIC2
var.ERIC2
sd.ERIC2
```

```{r}
CB1 <- rbind(GH1,CWJ1,YCH1,ERIC1)
CB2 <- rbind(GH2,CWJ2,YCH2,ERIC2)
group <- c(1)
CB1 <- cbind(CB1,group)
group <- c(2)
CB2 <- cbind(CB2,group)
CB <- rbind(CB1,CB2)
str(CB)

res1 <- t.test(CB1$lac_X_value,CB2$lac_X_value)
res1
res2 <- t.test(CB1$lac_Y_value,CB2$lac_Y_value)
res2
res3 <- t.test(CB1$lac_Z_value,CB2$lac_Z_value)
res3
#z-axis has no significant difference

library(lattice)
CB1 <- data.frame(CB1)
CB2 <- data.frame(CB2)
cloud(CB1$lac_Z_value~CB1$lac_X_value*CB1$lac_Y_value,data = CB1,color = "red")
cloud(CB2$lac_Z_value~CB2$lac_X_value*CB2$lac_Y_value,data = CB2)
```
```{r}
time1<-c(10.754328-1.659422,10.10797-2.003494,12.410064-2.118693,8.82169-0.515078)
time2<-c(8.452365-0.890054,10.01876-2.752813,14.771162-7.462382,11.44068-3.715343)
time1
time2
height <- c(183,180,183,173)
weight<- c(95,80,80,48)
gender <-c('male','male','male','female')
group <- c(1)
D1 <- cbind(time1,height,weight,gender,group)
group <- c(2)
D2 <- cbind(time2,height,weight,gender,group)
D3 <- rbind(D1,D2)
D3 <- as.data.frame(D3)
D3$time1 <- as.character(D3$time1)
D3$height <-as.numeric(D3$height)
D3$weight <- as.numeric(D3$weight)
D3$group <- as.numeric(D3$group)
D3$group[which(D3$group == 1)] <- "before"
D3$group[which(D3$group == 2)] <- "after"
lm1 <- lm(formula =time1~height+weight+gender+group,data = D3)
summary(lm1)
options(contrasts = c("contr.sum", "contr.poly"))
lm2 <- lm(formula =time1~group,data = D3)
summary(lm2)
lm3 <- lm(formula =time1~1,data = D3)
summary(lm3)
anova(lm2,lm3)
```

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4 changes: 4 additions & 0 deletions assignment 8 video link.R
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videolink:
https://youtu.be/WgXDINp60vE
our ppt link:
https://docs.google.com/presentation/d/17O89ctwJV_uOaGYrjEWzEFYL502ydfJG8yTFRL-fwzU/edit?usp=sharing
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