Programming Assignment 4

class: center, middle, inverse, title-slide

.title[
# Programming Assignment 4
]
.subtitle[
## Data Science
]
.author[
### Andrea Valeria Carbone
]
.date[
### 2025/03/25 (updated: 2025-03-31)
]

---

``` r
library(tidyverse)
```

```
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.0.4     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
```

``` r
library(dplyr)
library(ds4ling)
```

```
## 
##  ds4ling loaded
##  Happy coding!
```

``` r
library("here")
```

```
## here() starts at /Users/avaleriacarbone/Desktop/pa_4
```
---

``` r
data <- read.csv(here("data_raw", "fricatives", "fricatives.csv"))
```
---

``` r
#data tidying

data_tidy <- data |>
  pivot_longer(cols = c(s_cog, sh_cog),
               names_to = "phoneme",
               values_to = "cog")|>
pivot_longer(cols = c(s_skewness, sh_skewness),
             names_to = "phoneme_skewness",
             values_to = "skewness")|>
  select("phoneme", "cog", "skewness")|>
  mutate(phoneme = gsub("_cog", "", phoneme))
         
        
         
#table of descriptive statistics
         summary(data_tidy)
```

```
##    phoneme               cog          skewness    
##  Length:200         Min.   :2556   Min.   :2.102  
##  Class :character   1st Qu.:4017   1st Qu.:2.983  
##  Mode  :character   Median :4876   Median :3.458  
##                     Mean   :4847   Mean   :3.430  
##                     3rd Qu.:5761   3rd Qu.:3.865  
##                     Max.   :7095   Max.   :4.752
```

``` r
         print(summary(data_tidy))
```

``` r
         write.csv(data_tidy, "../data_tidy/data_tidy.csv")
```
---

``` r
 print(data_tidy)
```

```
## # A tibble: 200 × 3
##    phoneme   cog skewness
##    <chr>   <dbl>    <dbl>
##  1 s       3285.     2.72
##  2 s       3285.     2.31
##  3 sh      2556.     2.72
##  4 sh      2556.     2.31
##  5 s       3511.     3.09
##  6 s       3511.     2.47
##  7 sh      2781.     3.09
##  8 sh      2781.     2.47
##  9 s       4029.     3.33
## 10 s       4029.     2.48
## # ℹ 190 more rows
```
---
#Table of descriptive statistics

``` r
summary_table <- data_tidy|>
  group_by(phoneme)|>
  summarise(
    mean_skew = mean (skewness),
    mean_cog = mean (cog),
    mean_skew = median (skewness),
    mead_cog = median (cog)
    
  )
knitr::kable(summary_table)
```

|phoneme | mean_skew| mean_cog| mead_cog|
|:-------|---------:|--------:|--------:|
|s       |  3.457987| 5600.448| 5629.104|
|sh      |  3.457987| 4093.861| 4091.038|
---
#Tidy data

``` r
write.csv(data_tidy, "../data_tidy/data_tidy.csv")
```
---
#Boxpot of cog as a function of phoneme

``` r
data_tidy|>
  ggplot() +
  (aes(x = phoneme, y = cog, fill = phoneme)) +
  geom_boxplot() +
  labs(title = "cog",
       x = "phoneme", y = "cog")
```

![](index_files/figure-html/unnamed-chunk-7-1.png)

---
#skewness as a function of phoneme

``` r
ggplot(data_tidy,
       aes(x = phoneme, y = skewness, fill = phoneme)) +
  stat_summary(fun = mean) +
  labs(title = "skewness as a function of phoneme",
       x = "phoneme", y = "skewness")
```

```
## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_segment()`).
```

![](index_files/figure-html/unnamed-chunk-8-1.png)

#cog as a function of skewness for the s segments
---

``` r
data_s <- data_tidy |> 
  
  filter(phoneme == "s")

model <- lm(
  cog ~ skewness,
  data = data_s)

print(model)
```

```
## 
## Call:
## lm(formula = cog ~ skewness, data = data_s)
## 
## Coefficients:
## (Intercept)     skewness  
##      2322.4        955.8
```
---
#scatterplot

``` r
data_tidy |>
ggplot() +
  aes(x = cog, y = skewness) +
  geom_point() +
  geom_smooth(method = "lm") +
  labs(title = "gravity as a function of skewness",
      x = "cog", y = "skewness")
```

```
## `geom_smooth()` using formula = 'y ~ x'
```

![](index_files/figure-html/unnamed-chunk-10-1.png)

---
#Table model

``` r
knitr::kable(summary(model)$coef)
```

|            |  Estimate| Std. Error|  t value| Pr(>&#124;t&#124;)|
|:-----------|---------:|----------:|--------:|------------------:|
|(Intercept) | 2322.3856|   386.3135| 6.011660|                  0|
|skewness    |  955.8394|   111.1472| 8.599758|                  0|

---
#Model diagnostics

``` r
diagnosis(model)
```

![](index_files/figure-html/unnamed-chunk-12-1.png)
---
# report
There is a positive correlation between skewness and center of gravity, so as skewness increases, the center of gravity also shifts in the same direction, and the increase of COG is statistically significant with pi values around 0.

---

``` r
data_2 <- read_csv(here("data_raw", "fricatives", "assumptions.csv"))
```

```
## Rows: 142 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (2): x, y
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
```

``` r
data_2|>
  ggplot() +
  geom_point() +
  aes(x = x, y = y) +
  labs (x ="x", y ="y", tile = "Assumptions")
```

![](index_files/figure-html/unnamed-chunk-14-1.png)
---
#explanation

There is not real data, but a dinosaur.

---