Exploded code

# Exploded code
## Using flipbookr and xaringan
### Me

---

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---

```r
*library(tidyverse)
```
]
 
.panel2-base-auto[

]

---
count: false

```r
library(tidyverse)

*single_trial_prob <- .5
```
]
 
.panel2-base-auto[

]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

*num_trials <- 10
```
]
 
.panel2-base-auto[

]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

*0:num_trials
```
]
 
.panel2-base-auto[

```
 [1]  0  1  2  3  4  5  6  7  8  9 10
```
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
* possible_outcomes
```
]
 
.panel2-base-auto[

]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

*dbinom(x = possible_outcomes,
*      size = 10,
*      prob = single_trial_prob)
```
]
 
.panel2-base-auto[

```
 [1] 0.0009765625 0.0097656250 0.0439453125 0.1171875000 0.2050781250 0.2460937500 0.2050781250 0.1171875000 0.0439453125 0.0097656250 0.0009765625
```
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
* probs
```
]
 
.panel2-base-auto[

]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

*tibble(possible_outcomes, probs)
```
]
 
.panel2-base-auto[

```
# A tibble: 11 × 2
   possible_outcomes    probs
               <int>    <dbl>
 1                 0 0.000977
 2                 1 0.00977 
 3                 2 0.0439  
 4                 3 0.117   
 5                 4 0.205   
 6                 5 0.246   
 7                 6 0.205   
 8                 7 0.117   
 9                 8 0.0439  
10                 9 0.00977 
11                10 0.000977
```
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
* ggplot()
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_09_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
* aes(x = possible_outcomes)
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_10_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
  aes(x = possible_outcomes) +
* scale_x_continuous(breaks = possible_outcomes)
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_11_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
  aes(x = possible_outcomes) +
  scale_x_continuous(breaks = possible_outcomes) +
* aes(y = probs)
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_12_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
  aes(x = possible_outcomes) +
  scale_x_continuous(breaks = possible_outcomes) +
  aes(y = probs) +
* geom_point()
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_13_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
  aes(x = possible_outcomes) +
  scale_x_continuous(breaks = possible_outcomes) +
  aes(y = probs) +
  geom_point() +
* aes(xend = possible_outcomes,
*     yend = 0)
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_14_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
  aes(x = possible_outcomes) +
  scale_x_continuous(breaks = possible_outcomes) +
  aes(y = probs) +
  geom_point() +
  aes(xend = possible_outcomes,
      yend = 0) +
* geom_segment(lty = "dotted")
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_15_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
  aes(x = possible_outcomes) +
  scale_x_continuous(breaks = possible_outcomes) +
  aes(y = probs) +
  geom_point() +
  aes(xend = possible_outcomes,
      yend = 0) +
  geom_segment(lty = "dotted") +
* labs(title = "Binomial Distribution of for ten events where probability of success for each event is .5  (success/failure probability is independent)" %>%
*        str_wrap())
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_16_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
  aes(x = possible_outcomes) +
  scale_x_continuous(breaks = possible_outcomes) +
  aes(y = probs) +
  geom_point() +
  aes(xend = possible_outcomes,
      yend = 0) +
  geom_segment(lty = "dotted") +
  labs(title = "Binomial Distribution of for ten events where probability of success for each event is .5  (success/failure probability is independent)" %>%
         str_wrap()) +
* geom_text(aes(label = probs %>% round(4)),
*           nudge_y = .01)
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_17_output-1.png)
]

---
count: false

```r
library(tidyverse)

single_trial_prob <- .5

num_trials <- 10

0:num_trials ->
  possible_outcomes

dbinom(x = possible_outcomes,
       size = 10,
       prob = single_trial_prob) ->
  probs

tibble(possible_outcomes, probs) %>%
  ggplot() +
  aes(x = possible_outcomes) +
  scale_x_continuous(breaks = possible_outcomes) +
  aes(y = probs) +
  geom_point() +
  aes(xend = possible_outcomes,
      yend = 0) +
  geom_segment(lty = "dotted") +
  labs(title = "Binomial Distribution of for ten events where probability of success for each event is .5  (success/failure probability is independent)" %>%
         str_wrap()) +
  geom_text(aes(label = probs %>% round(4)),
            nudge_y = .01) +
* annotate(geom = "text",
*          x = 1.5,
*          y = .2,
*          label = "P(n==k) == {Pi}",
*          parse = TRUE,
*          size = 5)
```
]
 
.panel2-base-auto[
![](dbinom_dgeom_flipbook_files/figure-html/base_auto_18_output-1.png)
]

---

```r
# what is the probability of at least eight successes in ten trials
# when each trial is chance event with probability of .8
*8:10
```
]
 
.panel2-more-auto[

```
[1]  8  9 10
```
]

---
count: false

```r
# what is the probability of at least eight successes in ten trials
# when each trial is chance event with probability of .8
8:10 %>%
* dbinom(x = .,
*        size = 10,
*        prob = .8)
```
]
 
.panel2-more-auto[

```
[1] 0.3019899 0.2684355 0.1073742
```
]

---
count: false

```r
# what is the probability of at least eight successes in ten trials
# when each trial is chance event with probability of .8
8:10 %>%
  dbinom(x = .,
         size = 10,
         prob = .8) %>%
* sum()
```
]
 
.panel2-more-auto[

```
[1] 0.6777995
```
]

---
count: false

```r
# what is the probability of at least eight successes in ten trials
# when each trial is chance event with probability of .8
8:10 %>%
  dbinom(x = .,
         size = 10,
         prob = .8) %>%
  sum()

# or
*dbinom(8, 10, .8)
```
]
 
.panel2-more-auto[

```
[1] 0.6777995
```

```
[1] 0.3019899
```
]

---
count: false

# or
dbinom(8, 10, .8) +
* dbinom(9, 10, .8)
```
]
 
.panel2-more-auto[

```
[1] 0.6777995
```

```
[1] 0.5704253
```
]

---
count: false

# or
dbinom(8, 10, .8) +
  dbinom(9, 10, .8) +
* dbinom(10, 10, .8)
```
]
 
.panel2-more-auto[

```
[1] 0.6777995
```

```
[1] 0.6777995
```
]

---

```r
# what is the probability of exactly 5 successes in 10 trials
# when each trial is chance event with probility .5 success
*dbinom(5, 10, .5)
```
]
 
.panel2-more2-auto[

```
[1] 0.2460938
```
]

---
count: false

```r
# what is the probability of exactly 5 successes in 10 trials
# when each trial is chance event with probility .5 success
dbinom(5, 10, .5)
```
]
 
.panel2-more2-auto[

```
[1] 0.2460938
```
]