Intro to Statistics

class: center, middle, inverse, title-slide

# Intro to Statistics
## Cohen Chapter 1 .small[EDUC/PSY 6600]

---

class: inverse, middle, center

# Background Information

---
background-image: url(figures/fig_scale_variable.png)
background-position: 50% 80%
background-size: 600px

# Scale vs. Variable

---
# Scale vs. Variable

.pull-left[
## MEASUREMENT SCALE

.large[
- .coral[Nominal] = named groupings, no meaningful order
- .dcoral[Ordinal] = groupings that do have natural order
- .nicegreen[Interval] = precise units that are equally spaced
- .bluer[Ratio]	= interval + true zero point
]]

.pull-right[
## VARIABLE TYPE

.large[
- .coral[Categorical] = finite, countable number of levels, no intermediate values possible	
- .nicegreen[Numeric] = infinite intermediate values are possible, at least in theory
]

*NOTE: due to limits on measurement precision, observed data may be discrete, even though the underlying construct is continuous*
]

---
background-image: url(figures/fig_obs_exp.jpg)
background-position: 50% 90%
background-size: 900px

# Observational vs. Experimental

---
# Rounding Numbers

### Rules

.large[
- If you want to round to N decimal places, look at the digit in the `$N + 1$` place…
    - If it is LESS than 5 -> do not change the digit in the Nth place
    - If it is MORE than 5 -> increase the digit in the Nth place by 1
    - If it is EQUAL to 5 AND there are no non-zero digits to the right, -> increase the digit in the Nth place by 1 ONLY IF the Nth digit is ODD (do not change it if it is EVEN)

In all cases, the last step is to drop the digit in the `$N+1$` place and other digits to the right
]

.center[.huge[.coral[Examples]]]

???

Round to two decimal places

- `$65.3 = 65.30$`
- `$8/3 = 2.67$`
- `$0.4255 = 0.43$`
- `$0.4358 = 0.44$`
- `$0.425 = 0.42$`
- `$0.435 = 0.44$`

---
background-image: url(figures/fig_summation_notation.png)
background-position: 50% 50%
background-size: 500px

# Summation Notation

.center[.Huge[.coral[Examples]]]

???
Some examples up on the board:

$$
\frac{1}{5}\sum_{i = 1}^5 x_i
$$

$$
\sum_{i = 1}^2 (x_i + y_i)
$$

$$
\sum_{i = 1}^n y_i
$$

$$
\sum_{i = 1}^2 (x_i \times y_i)
$$

---
# Summation Rules

.pull-left[
#### Number 1
$$
\sum (X_i + Y_i) = \sum X_i + \sum Y_i
$$
$$
\sum (X_i - Y_i) = \sum X_i - \sum Y_i
$$

#### Number 2
$$
\sum_{i=1}^n C = nC
$$

#### Number 3
$$
\sum CX_i = C \sum X_i
$$
]

.pull-right[
#### Number 4

$$
\sum (X_i \times Y_i) \neq \sum X_i \times \sum Y_i
$$
]

---
class: inverse, middle, center

# Intro to R

---
# Download `R` and `RStudio`

.huge[If `R` is like a car's engine, then `RStudio` is the steering wheel, the pedals, and the comfortable seat]

--
.pull-left[.huge[.center[
`R`

[www.r-project.org](https://cran.cnr.berkeley.edu/)
]]]

.pull-right[.huge[.center[
`RStudio`

[www.rstudio.com](https://www.rstudio.com/products/rstudio/download/)
]]]

---
# Focus on what is needed in `R`

.center[.Huge[
".dcoral[Success] is neither magical nor mysterious. Success is the natural consequence of consistently applying the .nicegreen[basic fundamentals]." --- Jim Rohn
]]

.footnote[https://www.brainyquote.com/quotes/jim_rohn_122132?src=t_fundamentals]

---
# Intro to `R`

.pull-left[.huge[
Why Use `R`?
]
.large[
- .coral[**Free**]
- Almost always up-to-date
- Best .bluer[data visualizations]
- .nicegreen[Syntax oriented] (easy to reproduce analyses)
- Gets updated regularly
- You can make your .gray1[own functionality] (e.g., `table1()`)
]]

.pull-right[
.huge[`table1()` produces 👇] 
 
![](figures/table1_fig.png)
]

---
count: false
# Intro to `R`

.pull-right[.huge[
Any Issues?
]
.large[
- Learning curve
- Too extensive (people often focus on too much)
- Advisor's sometimes don't use it

The pro's heavily outweight the con's *if* you are willing to use it. It can save you tons of time in the long-run.
]]

---
.pull-left[
## .coral[Objects]

.large[.large[
Virtual objects are like physical objects (e.g., a car is good to travel in, a table not so much)

`R` uses virtual objects (`data.frame`, `vectors`)
]]

```r
x <- 5
```

```r
x = 5
```

]

.pull-right[
## .bluer[Vectors] and .nicegreen[Data Frames]

.large[.large[
- a `vector` is a single variable (can be numeric, character, or factor)
- a `data.frame` is a group of vectors (variables)
]]

```r
df
```

```
>   x y
> 1 5 1
> 2 3 1
> 3 4 0
> 4 1 0
```

]

---
# Functions

.huge[Its how we do stuff in `R`]

.pull-left[.large[

Generally looks like:

- `stuff(arg1, arg2)`
    - `stuff` is the function's name
    - `()` surround the arguments that go in the function
    -`arg1` etc. are the pieces of information we give a function
]]

.pull-right[
.large[Here's an example of the "mean" function:

- Using our `df` data.frame from before
    - we grab a single variable from `df` using `$`
- `mean()` wants a single variable and it provides the average
]

```r
## This is a comment
mean(df$x)
```

```
## [1] 3.25
```
]

---
# Important first steps in `R`

.large[.large[
1. Read in Data
2. Quickly assess the data
3. Clean the data
4. Analyze the data
]]

.large[We'll show each of these over the next few weeks starting with reading in, assessing and cleaning the data]

---
# Read in the data

.huge[Data comes in various files:]

.pull-left[.large[
- CSV
- tab-delimited
- SPSS
- Excel
]]
.pull-right[.large[
- SAS
- Stata
- Mplus
- etc.
]]

--
### `R` can read all types

.huge[Generally, it all works in a similar way]

---
# Read in data

- .large[If your data is called `my_data_file.csv`, then:]

```r
my_data <- rio::import("my_data_file.csv")
```

- .large[If your data is called `my_data_file.txt` (and is tab-delimited), then:]

```r
my_data <- rio::import("my_data_file.txt", sep="\t", header=TRUE)
```

- .large[If your data is an SPSS file, then:]

```r
my_data <- rio::import("my_data_file.sav")
```

---
background-image: url(figures/fig_inho_data_desc.png)
background-position: 50% 90%
background-size: 800px

# Let's use the data from the book

---
# Steps for .dcoral[Preparing] the Data for Analysis

.large[.large[
1. .coral[Get the data]
2. .nicegreen[Prep the data]
    - Variable Labels 	
    - Value Labels	
    - Missing Values
3. .bluer[Compute] new variables and values (fill in missing codes, recode scores, categorize/group values, combine)
4. Get .dcoral[descriptives] using `tableF()` and `table1()` from the `furniture` package to check what is going on
]]

---
# Step 1: Get the data

```r
## Data is in .sav form (SPSS)
library(rio)
d <- rio::import("Data/Ihno_dataset.sav")
d
```

```
##     Sub_num Gender Major Reason Exp_cond Coffee Num_cups Phobia Prevmath
## 1         1      1     1      3        1      1        0      1        3
## 2         2      1     1      2        1      0        0      1        4
## 3         3      1     1      1        1      0        0      4        1
## 4         4      1     1      1        1      0        0      4        0
## 5         5      1     1      1        1      0        1     10        1
## 6         6      1     1      1        2      1        1      4        1
## 7         7      1     1      1        2      0        0      4        2
## 8         8      1     1      3        2      1        2      4        1
## 9         9      1     1      1        2      0        0      4        1
## 10       10      1     1      1        2      1        2      5        0
## 11       11      1     1      1        2      0        1      5        1
## 12       12      1     1      1        2      0        0      4        0
## 13       13      1     1      1        2      0        1      7        0
## 14       14      1     1      3        3      0        2      4        1
## 15       15      1     1      1        4      1        3      3        1
## 16       16      1     1      1        4      1        0      8        0
## 17       17      1     1      1        4      0        0      4        1
## 18       18      1     1      1        4      1        3      5        1
## 19       19      1     1      3        4      1        2      0        3
## 20       20      1     2      1        2      1        1      4        1
## 21       21      1     2      2        2      1        2      4        0
## 22       22      1     2      1        3      1        0      3        1
## 23       23      1     2      1        3      0        2      4        1
## 24       24      1     2      2        2      1        2      0        3
## 25       25      1     2      2        3      1        2      1        3
## 26       26      1     2      2        4      0        0      1        4
## 27       27      1     2      2        4      1        2      0        6
## 28       28      1     2      3        1      1        3      4        2
## 29       29      1     2      1        1      0        0      3        2
## 30       30      1     2      3        1      1        0      5        1
## 31       31      1     3      1        1      1        1      9        1
## 32       32      1     3      1        3      1        3      3        0
## 33       33      1     3      1        4      1        2      4        1
## 34       34      1     3      2        1      1        1      1        1
## 35       35      1     3      2        1      0        0      2        1
## 36       36      1     3      2        2      1        1      0        0
## 37       37      1     3      2        4      1        2      3        1
## 38       38      1     3      3        1      0        0      2        0
## 39       39      1     3      3        2      0        1      8        1
## 40       40      1     3      3        4      0        0      4        1
## 41       41      1     3      3        4      0        0      4        1
## 42       42      1     4      2        1      0        0      0        1
## 43       43      1     4      2        2      1        0      3        1
## 44       44      1     4      2        4      0        0      2        1
## 45       45      1     4      2        4      0        0      2        1
## 46       46      1     4      2        4      0        1      1        0
## 47       47      1     4      3        1      0        0      1        1
## 48       48      1     4      3        1      1        1      5        0
## 49       49      1     4      3        2      1        1      5        1
## 50       50      1     4      3        3      0        0      4        1
## 51       51      1     4      3        3      0        0      4        1
## 52       52      1     4      3        4      1        0     10        0
## 53       53      1     4      3        4      0        0      7        1
## 54       54      1     5      1        3      1        1      3        5
## 55       55      1     5      1        3      1        2      4        1
## 56       56      1     5      2        4      0        1      2        2
## 57       57      1     5      3        1      0        0      2        0
## 58       58      2     1      1        1      1        1      1        1
## 59       59      2     1      2        1      0        0      7        0
## 60       60      2     1      1        2      0        1      5        0
## 61       61      2     1      1        3      1        1      5        1
## 62       62      2     1      1        3      0        0      1        2
## 63       63      2     1      1        3      0        0      3        0
## 64       64      2     1      1        4      0        0      3        1
## 65       65      2     1      1        4      0        1      5        1
## 66       66      2     1      2        2      0        0      1        4
## 67       67      2     1      3        1      0        0      0        3
## 68       68      2     2      1        2      0        0      5        0
## 69       69      2     2      1        3      0        0      6        2
## 70       70      2     2      1        3      1        1      3        2
## 71       71      2     2      1        4      1        1      5        0
## 72       72      2     2      1        4      1        2      4        2
## 73       73      2     2      2        3      0        0      0        4
## 74       74      2     2      2        3      0        0      2        4
## 75       75      2     2      2        4      0        0      2        3
## 76       76      2     2      3        1      0        0      3        1
## 77       77      2     2      1        2      1        1      1        2
## 78       78      2     2      3        2      0        0      1        3
## 79       79      2     2      3        3      1        1      0        2
## 80       80      2     2      3        3      0        0      2        2
## 81       81      2     2      3        4      0        1     10        0
## 82       82      2     3      1        1      0        0      3        1
## 83       83      2     3      1        1      0        1      3        1
## 84       84      2     3      1        1      1        1      8        1
## 85       85      2     3      1        1      1        0      3        1
## 86       86      2     3      3        2      0        0      3        1
## 87       87      2     3      2        2      1        0      1        0
## 88       88      2     3      2        3      0        0      1        4
## 89       89      2     3      3        2      0        0      2        0
## 90       90      2     3      3        3      0        0      8        1
## 91       91      2     3      3        3      1        1      3        1
## 92       92      2     4      2        1      0        0      0        1
## 93       93      2     4      2        4      0        0      0        2
## 94       94      2     4      3        3      1        2      4        0
## 95       95      2     5      3        3      0        0      7        2
## 96       96      2     5      2        2      1        1      0        1
## 97       97      2     5      2        3      0        0      0        2
## 98       98      2     5      2        3      0        0      2        2
## 99       99      2     5      2        4      1        1      1        4
## 100     100      2     5      1        2      0        0      2        2
##     Mathquiz Statquiz Exp_sqz Hr_base Hr_pre Hr_post Anx_base Anx_pre
## 1         43        6       7      71     68      65       17      22
## 2         49        9      11      73     75      68       17      19
## 3         26        8       8      69     76      72       19      14
## 4         29        7       8      72     73      78       19      13
## 5         31        6       6      71     83      74       26      30
## 6         20        7       6      70     71      76       12      15
## 7         13        3       4      71     70      66       12      16
## 8         23        7       7      77     87      84       17      19
## 9         38        8       7      73     72      67       20      14
## 10        NA        7       6      78     76      74       20      24
## 11        29        8      10      74     72      73       21      25
## 12        32        8       7      73     74      74       32      35
## 13        18        1       3      73     76      78       19      23
## 14        NA        5       4      72     83      77       18      27
## 15        21        8       6      72     74      68       21      27
## 16        NA        3       1      76     76      79       14      18
## 17        37        8       7      68     67      74       15      19
## 18        37        7       4      77     78      73       39      39
## 19        32       10       9      74     74      75       20      12
## 20        NA        7       7      74     75      73       15      11
## 21        25        7       6      74     84      77       19      27
## 22        22        4       3      73     71      79       18      13
## 23        35        8       7      71     74      76       18      22
## 24        47        8       7      75     75      71       23      28
## 25        41        6       6      76     73      72       18      24
## 26        26        7       6      71     76      75       14      10
## 27        39        8       8      74     79      79       17      12
## 28        21        7       8      78     79      73       18      13
## 29        NA        7       9      70     63      66       18      12
## 30        22        4       7      73     78      69       21      14
## 31        21        8       8      75     83      73       18      21
## 32        NA        7       6      78     76      84       24      27
## 33        26        8       7      76     74      81       17      26
## 34        20        8       9      76     69      71       17      25
## 35        30        6       9      69     69      64       22      16
## 36        40        8       9      77     79      74       21      14
## 37        35        8       7      78     73      78       19      12
## 38        10        7       8      74     72      72       15      21
## 39        35        6       5      71     70      75       20      27
## 40        44        6       4      67     67      73       12      19
## 41        26        7       5      77     78      78       21      15
## 42        NA        9      11      71     72      67       20      23
## 43        15        3       4      76     79      71       19      21
## 44        42        7       7      69     70      64       13      24
## 45        33        8       7      72     64      68       20      14
## 46        29        6       6      72     79      76       22      27
## 47        39        7       8      71     63      66       15      21
## 48        38        8       8      71     82      79       20      26
## 49        NA        5       4      75     76      70       16      18
## 50        24        7       6      74     76      75       22      27
## 51        NA        7       5      74     74      69       30      36
## 52        26        5       2      78     80      80       19      24
## 53        14        5       3      68     78      73       20      29
## 54        45        9       9      76     79      75       15       8
## 55        28        8       8      73     78      77       19      13
## 56        31        8       7      74     78      82       27      21
## 57        NA        8       9      72     67      67       16      20
## 58        32        8      10      74     84      76       17      19
## 59        15        3       6      73     73      71       19      16
## 60        26        8       7      73     74      76       16      20
## 61        26        8       7      80     82      86       18      27
## 62        32        5       5      67     68      73       20      25
## 63        21        8       7      65     75      69       26      29
## 64        43        8       8      71     72      76       18      13
## 65        NA        8       5      72     75      68       21      26
## 66        34        9      11      70     73      65       11      19
## 67        33       10      11      72     67      68       16      25
## 68        30        7       7      69     70      74       18      15
## 69        46        8       6      68     74      71       16      10
## 70        NA        7       7      76     79      71       19      13
## 71        33        7       4      68     71      77       18      21
## 72        29        7       6      76     79      71       22      15
## 73        30        9      10      69     70      74       15      21
## 74        34        8       7      68     70      69       18      21
## 75        32        9       8      70     62      71       17      23
## 76        37        6       8      70     73      77       15      23
## 77        NA        8      10      69     67      64       14      17
## 78        31        7       8      64     74      70       22      25
## 79        30        8       8      68     72      71       10      13
## 80        28        5       5      71     74      67       15      17
## 81        14        6       3      69     78      76       20      25
## 82         9        7       8      71     69      76       13      10
## 83        11        4       7      72     83      73       14      16
## 84        30        6       7      76     78      71       15      18
## 85        15        5       7      76     67      71       18      12
## 86        32        3       5      72     70      67       15       9
## 87        22        5       4      74     78      72       20      27
## 88        NA        8       9      70     71      69       10      16
## 89        25        6       7      68     70      73       16      20
## 90        18        4       3      71     73      77       15      19
## 91        11        4       3      72     75      76       24      17
## 92        11        6       9      71     78      72       16      21
## 93        37        9       9      72     71      73       17      11
## 94        28        7       6      73     77      79       24      18
## 95        NA        8       6      69     70      71       23      28
## 96        33        7       9      74     73      71       17      18
## 97        28        8       9      70     66      65       17      12
## 98        38        9      10      65     65      69       18      14
## 99        41        8       8      72     68      73       17      11
## 100       39        7       7      70     70      64       17      11
##     Anx_post
## 1         20
## 2         16
## 3         15
## 4         16
## 5         25
## 6         19
## 7         17
## 8         22
## 9         17
## 10        19
## 11        22
## 12        33
## 13        20
## 14        28
## 15        22
## 16        21
## 17        18
## 18        40
## 19        18
## 20        20
## 21        23
## 22        19
## 23        25
## 24        24
## 25        26
## 26        18
## 27        16
## 28        16
## 29        14
## 30        17
## 31        23
## 32        25
## 33        15
## 34        19
## 35        18
## 36        19
## 37        17
## 38        16
## 39        22
## 40        17
## 41        15
## 42        21
## 43        17
## 44        22
## 45        22
## 46        24
## 47        13
## 48        26
## 49        23
## 50        23
## 51        32
## 52        24
## 53        30
## 54        17
## 55        18
## 56        24
## 57        22
## 58        14
## 59        16
## 60        17
## 61        20
## 62        24
## 63        23
## 64        16
## 65        27
## 66         9
## 67        15
## 68        15
## 69        17
## 70        15
## 71        19
## 72        20
## 73        17
## 74        19
## 75        19
## 76        14
## 77        15
## 78        19
## 79        15
## 80        17
## 81        23
## 82        13
## 83        15
## 84        17
## 85        17
## 86        13
## 87        18
## 88        14
## 89        19
## 90        21
## 91        21
## 92        15
## 93        17
## 94        20
## 95        24
## 96        17
## 97        13
## 98        19
## 99        18
## 100       14
```

---
# Step 2: Prep the data

```r
## install.packages("tidyverse")
library(tidyverse)
d_clean <- d %>%
 mutate(Major = factor(Major, labels = c("Psychology", "Premed",
 "Biology", "Sociology",
 "Economics"))) %>%
 mutate(Coffee = factor(Coffee))
d_clean
```

```
##     Sub_num Gender      Major Reason Exp_cond Coffee Num_cups Phobia
## 1         1      1 Psychology      3        1      1        0      1
## 2         2      1 Psychology      2        1      0        0      1
## 3         3      1 Psychology      1        1      0        0      4
## 4         4      1 Psychology      1        1      0        0      4
## 5         5      1 Psychology      1        1      0        1     10
## 6         6      1 Psychology      1        2      1        1      4
## 7         7      1 Psychology      1        2      0        0      4
## 8         8      1 Psychology      3        2      1        2      4
## 9         9      1 Psychology      1        2      0        0      4
## 10       10      1 Psychology      1        2      1        2      5
## 11       11      1 Psychology      1        2      0        1      5
## 12       12      1 Psychology      1        2      0        0      4
## 13       13      1 Psychology      1        2      0        1      7
## 14       14      1 Psychology      3        3      0        2      4
## 15       15      1 Psychology      1        4      1        3      3
## 16       16      1 Psychology      1        4      1        0      8
## 17       17      1 Psychology      1        4      0        0      4
## 18       18      1 Psychology      1        4      1        3      5
## 19       19      1 Psychology      3        4      1        2      0
## 20       20      1     Premed      1        2      1        1      4
## 21       21      1     Premed      2        2      1        2      4
## 22       22      1     Premed      1        3      1        0      3
## 23       23      1     Premed      1        3      0        2      4
## 24       24      1     Premed      2        2      1        2      0
## 25       25      1     Premed      2        3      1        2      1
## 26       26      1     Premed      2        4      0        0      1
## 27       27      1     Premed      2        4      1        2      0
## 28       28      1     Premed      3        1      1        3      4
## 29       29      1     Premed      1        1      0        0      3
## 30       30      1     Premed      3        1      1        0      5
## 31       31      1    Biology      1        1      1        1      9
## 32       32      1    Biology      1        3      1        3      3
## 33       33      1    Biology      1        4      1        2      4
## 34       34      1    Biology      2        1      1        1      1
## 35       35      1    Biology      2        1      0        0      2
## 36       36      1    Biology      2        2      1        1      0
## 37       37      1    Biology      2        4      1        2      3
## 38       38      1    Biology      3        1      0        0      2
## 39       39      1    Biology      3        2      0        1      8
## 40       40      1    Biology      3        4      0        0      4
## 41       41      1    Biology      3        4      0        0      4
## 42       42      1  Sociology      2        1      0        0      0
## 43       43      1  Sociology      2        2      1        0      3
## 44       44      1  Sociology      2        4      0        0      2
## 45       45      1  Sociology      2        4      0        0      2
## 46       46      1  Sociology      2        4      0        1      1
## 47       47      1  Sociology      3        1      0        0      1
## 48       48      1  Sociology      3        1      1        1      5
## 49       49      1  Sociology      3        2      1        1      5
## 50       50      1  Sociology      3        3      0        0      4
## 51       51      1  Sociology      3        3      0        0      4
## 52       52      1  Sociology      3        4      1        0     10
## 53       53      1  Sociology      3        4      0        0      7
## 54       54      1  Economics      1        3      1        1      3
## 55       55      1  Economics      1        3      1        2      4
## 56       56      1  Economics      2        4      0        1      2
## 57       57      1  Economics      3        1      0        0      2
## 58       58      2 Psychology      1        1      1        1      1
## 59       59      2 Psychology      2        1      0        0      7
## 60       60      2 Psychology      1        2      0        1      5
## 61       61      2 Psychology      1        3      1        1      5
## 62       62      2 Psychology      1        3      0        0      1
## 63       63      2 Psychology      1        3      0        0      3
## 64       64      2 Psychology      1        4      0        0      3
## 65       65      2 Psychology      1        4      0        1      5
## 66       66      2 Psychology      2        2      0        0      1
## 67       67      2 Psychology      3        1      0        0      0
## 68       68      2     Premed      1        2      0        0      5
## 69       69      2     Premed      1        3      0        0      6
## 70       70      2     Premed      1        3      1        1      3
## 71       71      2     Premed      1        4      1        1      5
## 72       72      2     Premed      1        4      1        2      4
## 73       73      2     Premed      2        3      0        0      0
## 74       74      2     Premed      2        3      0        0      2
## 75       75      2     Premed      2        4      0        0      2
## 76       76      2     Premed      3        1      0        0      3
## 77       77      2     Premed      1        2      1        1      1
## 78       78      2     Premed      3        2      0        0      1
## 79       79      2     Premed      3        3      1        1      0
## 80       80      2     Premed      3        3      0        0      2
## 81       81      2     Premed      3        4      0        1     10
## 82       82      2    Biology      1        1      0        0      3
## 83       83      2    Biology      1        1      0        1      3
## 84       84      2    Biology      1        1      1        1      8
## 85       85      2    Biology      1        1      1        0      3
## 86       86      2    Biology      3        2      0        0      3
## 87       87      2    Biology      2        2      1        0      1
## 88       88      2    Biology      2        3      0        0      1
## 89       89      2    Biology      3        2      0        0      2
## 90       90      2    Biology      3        3      0        0      8
## 91       91      2    Biology      3        3      1        1      3
## 92       92      2  Sociology      2        1      0        0      0
## 93       93      2  Sociology      2        4      0        0      0
## 94       94      2  Sociology      3        3      1        2      4
## 95       95      2  Economics      3        3      0        0      7
## 96       96      2  Economics      2        2      1        1      0
## 97       97      2  Economics      2        3      0        0      0
## 98       98      2  Economics      2        3      0        0      2
## 99       99      2  Economics      2        4      1        1      1
## 100     100      2  Economics      1        2      0        0      2
##     Prevmath Mathquiz Statquiz Exp_sqz Hr_base Hr_pre Hr_post Anx_base
## 1          3       43        6       7      71     68      65       17
## 2          4       49        9      11      73     75      68       17
## 3          1       26        8       8      69     76      72       19
## 4          0       29        7       8      72     73      78       19
## 5          1       31        6       6      71     83      74       26
## 6          1       20        7       6      70     71      76       12
## 7          2       13        3       4      71     70      66       12
## 8          1       23        7       7      77     87      84       17
## 9          1       38        8       7      73     72      67       20
## 10         0       NA        7       6      78     76      74       20
## 11         1       29        8      10      74     72      73       21
## 12         0       32        8       7      73     74      74       32
## 13         0       18        1       3      73     76      78       19
## 14         1       NA        5       4      72     83      77       18
## 15         1       21        8       6      72     74      68       21
## 16         0       NA        3       1      76     76      79       14
## 17         1       37        8       7      68     67      74       15
## 18         1       37        7       4      77     78      73       39
## 19         3       32       10       9      74     74      75       20
## 20         1       NA        7       7      74     75      73       15
## 21         0       25        7       6      74     84      77       19
## 22         1       22        4       3      73     71      79       18
## 23         1       35        8       7      71     74      76       18
## 24         3       47        8       7      75     75      71       23
## 25         3       41        6       6      76     73      72       18
## 26         4       26        7       6      71     76      75       14
## 27         6       39        8       8      74     79      79       17
## 28         2       21        7       8      78     79      73       18
## 29         2       NA        7       9      70     63      66       18
## 30         1       22        4       7      73     78      69       21
## 31         1       21        8       8      75     83      73       18
## 32         0       NA        7       6      78     76      84       24
## 33         1       26        8       7      76     74      81       17
## 34         1       20        8       9      76     69      71       17
## 35         1       30        6       9      69     69      64       22
## 36         0       40        8       9      77     79      74       21
## 37         1       35        8       7      78     73      78       19
## 38         0       10        7       8      74     72      72       15
## 39         1       35        6       5      71     70      75       20
## 40         1       44        6       4      67     67      73       12
## 41         1       26        7       5      77     78      78       21
## 42         1       NA        9      11      71     72      67       20
## 43         1       15        3       4      76     79      71       19
## 44         1       42        7       7      69     70      64       13
## 45         1       33        8       7      72     64      68       20
## 46         0       29        6       6      72     79      76       22
## 47         1       39        7       8      71     63      66       15
## 48         0       38        8       8      71     82      79       20
## 49         1       NA        5       4      75     76      70       16
## 50         1       24        7       6      74     76      75       22
## 51         1       NA        7       5      74     74      69       30
## 52         0       26        5       2      78     80      80       19
## 53         1       14        5       3      68     78      73       20
## 54         5       45        9       9      76     79      75       15
## 55         1       28        8       8      73     78      77       19
## 56         2       31        8       7      74     78      82       27
## 57         0       NA        8       9      72     67      67       16
## 58         1       32        8      10      74     84      76       17
## 59         0       15        3       6      73     73      71       19
## 60         0       26        8       7      73     74      76       16
## 61         1       26        8       7      80     82      86       18
## 62         2       32        5       5      67     68      73       20
## 63         0       21        8       7      65     75      69       26
## 64         1       43        8       8      71     72      76       18
## 65         1       NA        8       5      72     75      68       21
## 66         4       34        9      11      70     73      65       11
## 67         3       33       10      11      72     67      68       16
## 68         0       30        7       7      69     70      74       18
## 69         2       46        8       6      68     74      71       16
## 70         2       NA        7       7      76     79      71       19
## 71         0       33        7       4      68     71      77       18
## 72         2       29        7       6      76     79      71       22
## 73         4       30        9      10      69     70      74       15
## 74         4       34        8       7      68     70      69       18
## 75         3       32        9       8      70     62      71       17
## 76         1       37        6       8      70     73      77       15
## 77         2       NA        8      10      69     67      64       14
## 78         3       31        7       8      64     74      70       22
## 79         2       30        8       8      68     72      71       10
## 80         2       28        5       5      71     74      67       15
## 81         0       14        6       3      69     78      76       20
## 82         1        9        7       8      71     69      76       13
## 83         1       11        4       7      72     83      73       14
## 84         1       30        6       7      76     78      71       15
## 85         1       15        5       7      76     67      71       18
## 86         1       32        3       5      72     70      67       15
## 87         0       22        5       4      74     78      72       20
## 88         4       NA        8       9      70     71      69       10
## 89         0       25        6       7      68     70      73       16
## 90         1       18        4       3      71     73      77       15
## 91         1       11        4       3      72     75      76       24
## 92         1       11        6       9      71     78      72       16
## 93         2       37        9       9      72     71      73       17
## 94         0       28        7       6      73     77      79       24
## 95         2       NA        8       6      69     70      71       23
## 96         1       33        7       9      74     73      71       17
## 97         2       28        8       9      70     66      65       17
## 98         2       38        9      10      65     65      69       18
## 99         4       41        8       8      72     68      73       17
## 100        2       39        7       7      70     70      64       17
##     Anx_pre Anx_post
## 1        22       20
## 2        19       16
## 3        14       15
## 4        13       16
## 5        30       25
## 6        15       19
## 7        16       17
## 8        19       22
## 9        14       17
## 10       24       19
## 11       25       22
## 12       35       33
## 13       23       20
## 14       27       28
## 15       27       22
## 16       18       21
## 17       19       18
## 18       39       40
## 19       12       18
## 20       11       20
## 21       27       23
## 22       13       19
## 23       22       25
## 24       28       24
## 25       24       26
## 26       10       18
## 27       12       16
## 28       13       16
## 29       12       14
## 30       14       17
## 31       21       23
## 32       27       25
## 33       26       15
## 34       25       19
## 35       16       18
## 36       14       19
## 37       12       17
## 38       21       16
## 39       27       22
## 40       19       17
## 41       15       15
## 42       23       21
## 43       21       17
## 44       24       22
## 45       14       22
## 46       27       24
## 47       21       13
## 48       26       26
## 49       18       23
## 50       27       23
## 51       36       32
## 52       24       24
## 53       29       30
## 54        8       17
## 55       13       18
## 56       21       24
## 57       20       22
## 58       19       14
## 59       16       16
## 60       20       17
## 61       27       20
## 62       25       24
## 63       29       23
## 64       13       16
## 65       26       27
## 66       19        9
## 67       25       15
## 68       15       15
## 69       10       17
## 70       13       15
## 71       21       19
## 72       15       20
## 73       21       17
## 74       21       19
## 75       23       19
## 76       23       14
## 77       17       15
## 78       25       19
## 79       13       15
## 80       17       17
## 81       25       23
## 82       10       13
## 83       16       15
## 84       18       17
## 85       12       17
## 86        9       13
## 87       27       18
## 88       16       14
## 89       20       19
## 90       19       21
## 91       17       21
## 92       21       15
## 93       11       17
## 94       18       20
## 95       28       24
## 96       18       17
## 97       12       13
## 98       14       19
## 99       11       18
## 100      11       14
```

---
# Step 3: Compute new variables/values

```r
d_clean <- d_clean %>%
 mutate(newVar = Mathquiz/2)
```
*Note that I removed the other variables just to show you but in reality all the variables are still there

```
## # A tibble: 100 x 2
## Mathquiz newVar
## <dbl> <dbl>
## 1 43 21.5
## 2 49 24.5
## 3 26 13 
## 4 29 14.5
## 5 31 15.5
## 6 20 10 
## 7 13 6.5
## 8 23 11.5
## 9 38 19 
## 10 NA NA 
## # … with 90 more rows
```

---
# Step 4: Get descriptives

.pull-left[

```r
library(furniture)
tableF(d_clean, Major)
```

```
## 
## ─────────────────────────────────────────
##  Major      Freq CumFreq Percent CumPerc
##  Psychology 29   29      29.00%  29.00% 
##  Premed     25   54      25.00%  54.00% 
##  Biology    21   75      21.00%  75.00% 
##  Sociology  15   90      15.00%  90.00% 
##  Economics  10   100     10.00%  100.00%
## ─────────────────────────────────────────
```
]

.pull-right[

```r
tableF(d_clean, Phobia)
```

```
## 
## ─────────────────────────────────────
##  Phobia Freq CumFreq Percent CumPerc
##  0      12   12      12.00%  12.00% 
##  1      15   27      15.00%  27.00% 
##  2      12   39      12.00%  39.00% 
##  3      16   55      16.00%  55.00% 
##  4      21   76      21.00%  76.00% 
##  5      11   87      11.00%  87.00% 
##  6      1    88      1.00%   88.00% 
##  7      4    92      4.00%   92.00% 
##  8      4    96      4.00%   96.00% 
##  9      1    97      1.00%   97.00% 
##  10     3    100     3.00%   100.00%
## ─────────────────────────────────────
```
]

---
# Step 4: Get descriptives

```r
library(furniture)
library(dplyr)
d_clean %>% 
  dplyr::group_by(Major) %>% 
  table1(Mathquiz, Phobia, Coffee)
```

```
## Using dplyr::group_by() groups: Major
```

```
## 
## ───────────────────────────────────────────────────────────────────
##                                   Major 
##           Psychology Premed     Biology     Sociology   Economics 
##           n = 25     n = 21     n = 19      n = 12      n = 8     
##  Mathquiz                                                         
##           29.6 (8.9) 31.0 (8.2) 24.2 (10.4) 28.0 (10.4) 35.4 (6.3)
##  Phobia                                                           
##           3.6 (2.4)  3.0 (2.5)  3.7 (2.6)   3.2 (3.0)   1.8 (1.4) 
##  Coffee                                                           
##     0     17 (68%)   11 (52.4%) 10 (52.6%)  8 (66.7%)   4 (50%)   
##     1     8 (32%)    10 (47.6%) 9 (47.4%)   4 (33.3%)   4 (50%)   
## ───────────────────────────────────────────────────────────────────
```

---
class: inverse, center, middle

# Questions?

---
class: inverse, center, middle

# Next Topics

### More Data Manipulation
### Understanding Data via Figures