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# WAA12

## データ解析基礎論 a weekly assignment A012

#### WAA12.1

```# data input
# plot
# figure1
interaction.plot(dat\$condition,
dat\$language,
dat\$score,
ylim = c(11,21),
pch = c(19,19),
col = c("skyblue","orange"),
type = "b",
ylab = "number of correctly recognized words",
xlab ="condition",
trace.label = "Language")
```

```# figure2
interaction.plot(dat\$language,
dat\$condition,
dat\$score,
ylim = c(11,21),
pch = c(15,15),
lty = c(1,1),
col = c("skyblue","orange"),
type = "b",
ylab = "number of correctly recognized words",
xlab ="language",
trace.label = "condition")
```

```# anova
dat.aov <- aov(score ~ condition*language,dat)
summary(dat.aov)
# 出力結果
Df Sum Sq Mean Sq F value   Pr(>F)
condition           1  220.9  220.90   23.91  2.1e-05 ***
language            1  176.4  176.40   19.09 0.000101 ***
condition:language  1  122.5  122.50   13.26 0.000846 ***
Residuals          36  332.6    9.24
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
```
```# simple main effect
source("http://peach.l.chiba-u.ac.jp/course_folder/tsme2017.R")
CRF.tsme(dat.aov,dat)
# 出力結果
simple main effect test for BETWEEEN subject factor1
ss df      ms       f         p
english    7.2  1   7.200  0.7793 3.832e-01
japanese 336.2  1 336.200 36.3897 6.291e-07
residual 332.6 36   9.239

Tukey HSD test - between subject factor @ language = japanese
control   exp
control   FALSE  TRUE
exp        TRUE FALSE

simple main effect test for BETWEEN subject factor2
ss df      ms       f         p
control    2.45  1   2.450  0.2652 6.097e-01
exp      296.45  1 296.450 32.0872 1.952e-06
residual 332.60 36   9.239

Tukey HSD test - within subject factor @ condition = exp
english japanese
english    FALSE     TRUE
japanese    TRUE    FALSE
```

#### WAA12.2

```# data input
# plot
interaction.plot(dat\$m.type,
dat\$language,
dat\$score,
ylim = c(11,21),
pch = c(19,19,19),
lty = c(2,2,1),
col = c("skyblue","orange","darkgreen"),
type = "b",
ylab = "number of correctly recognized words",
xlab ="Type of Music",
trace.label = "Language")
```

```# anova
dat.aov <- aov(score ~ m.type * language,dat)
summary(dat.aov)
# 出力結果
Df Sum Sq Mean Sq F value  Pr(>F)
m.type           2  149.5   74.74   7.024 0.00154 **
language         2  234.3  117.14  11.008 5.9e-05 ***
m.type:language  4  128.0   32.01   3.008 0.02286 *
Residuals       81  862.0   10.64
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

```
```# simple main effect
CRF.tsme(dat.aov,dat)
# 出力結果
simple main effect test for BETWEEEN subject factor1
ss df    ms     f        p
english  117.60  2 58.80 5.525 0.005631
hyoujun   82.07  2 41.03 3.856 0.025144
kansai    77.87  2 38.93 3.658 0.030120
residual 862.00 81 10.64

Tukey HSD test - between subject factor @ language = english
control douyou  enka
control   FALSE  FALSE  TRUE
douyou    FALSE  FALSE FALSE
enka       TRUE  FALSE FALSE

Tukey HSD test - between subject factor @ language = hyoujun
control douyou  enka
control   FALSE  FALSE FALSE
douyou    FALSE  FALSE  TRUE
enka      FALSE   TRUE FALSE

Tukey HSD test - between subject factor @ language = kansai
control douyou  enka
control   FALSE  FALSE FALSE
douyou    FALSE  FALSE  TRUE
enka      FALSE   TRUE FALSE

simple main effect test for BETWEEN subject factor2
ss df     ms      f         p
control   36.2  2  18.10  1.701 1.890e-01
douyou   224.5  2 112.23 10.546 8.499e-05
enka     101.7  2  50.83  4.777 1.094e-02
residual 862.0 81  10.64

Tukey HSD test - within subject factor @ m.type = douyou
english hyoujun kansai
english   FALSE    TRUE   TRUE
hyoujun    TRUE   FALSE  FALSE
kansai     TRUE   FALSE  FALSE

Tukey HSD test - within subject factor @ m.type = enka
english hyoujun kansai
english   FALSE    TRUE  FALSE
hyoujun    TRUE   FALSE  FALSE
kansai    FALSE   FALSE  FALSE
```