Introduction

class: center, middle, inverse, title-slide

# Introduction
## Research Methods and Skills
### 13/10/2020

---

# Who are we?

.pull-left[
| Dr Matt Craddock |
|------------------------------|
| ![A photograph of Dr Matt Craddock](images/01/matt.jpg) |
|Sarah Swift Building Room 2226|
|mcraddock@lincoln.ac.uk       |
]
.pull-right[
| Dr Tochukwu Onwuegbusi |
|------------------------------|
| ![A photograph of Dr Tochukwu Onwuegbusi](images/01/tochs.jpg) |
|Sarah Swift Building Room 2211|
|tonwuegbusi@lincoln.ac.uk       |
]

---
class: center, middle, inverse
# Replicability and reproducibility

---
background-image: url(images/01/headlines-repro.png)

---
background-image: url(images/01/F1.large.jpg)
background-size: contain

[Open Science Collaboration, 2015](dx.doi.org/10.1126/science.aac4716)

---

# Scenario A
.large[
You've just started work in a psychology lab. You're asked to help analyse some old data. There is reaction time data from 50 participants. Each participant's data is stored in a separate text file.

- How do you combine the data from each participant together to be able to analyse the data?

- It turns out some of the participants only completed part of the experiment - which ones, and what should you do with their data?

- What steps should you take to select and perform appropriate statistical analysis?
]

---

# Scenario B

.large[
You've been asked to design, implement, and evaluate a new treatment regime across several psychiatric institutes. Several colleagues are skeptical that it can deliver the kind of improvements in outcomes indicated in a publication describing the method.

- How do you interpret the strength of the previously published evidence?

- How do you design a rigorous test of the treatment efficacy?

- How do you evaluate and report on the outcomes of your trial?
]

---
# Research Methods and Skills

--
.pull-left[
![A cat standing on top of a statistics book](images/01/catistics-small.jpg)
]

--
.pull-right[
![A dog wearing a tie, sat at a computer, with the caption "How do I program"](images/01/dog-gramming.jpg)
]

---
# Course outline
.pull-left[
### Weeks 1-5
- Introduction to R
- Basic R programming
- Plotting with ggplot2
- Data import, selection and manipulation
- Describing and summarising your data
]

.pull-right[
### Weeks 5, 7-10
- Hypothesis testing and estimation
- *t*-tests and comparing two groups
- Correlation and linear regression
- One-way ANOVA
- Factorial ANOVA
]

### Weeks 11-13

- Qualitative methods

---
# Course outline

.pull-left[
### Weeks 1-5
![A dog wearing a tie, sat at a computer, with the caption "How do I program"](images/01/dog-gramming.jpg)
]

.pull-right[
### Weeks 5, 7-10
![A cat standing on top of a statistics book](images/01/catistics-small.jpg)
]

---

# Course outline

.pull-left[
### Weeks 1-5
![:scale 45%](images/01/R4DS.png)
]

.pull-right[
### Weeks 5-10
![Discovering Statistics Using R](images/01/DiscoverR.jpg)
]

---
# How it's going to work

.large[Each week you'll be provided with a set of pre-recorded videos introducing several core topics.

You'll be provided with some statistical exercises to work on. More detail on that later!

Timetabled sessions are:

1) **Optional**

2) **For Q & A and support**

Come along to the timetabled sessions and work on the exercises, or come prepared with questions.

If you get stuck **ask us**!]

---
class: inverse, center, middle
# Introduction to R and RStudio

---
background-image: url(https://www.r-project.org/Rlogo.png)
background-position: 80% 10%

# What is R?
.large[
R is a statistical, mathematical programming language

* Created in 1993

* Designed from the ground up to support many statistical tasks

* Covers all aspects of data analysis from import through to production of reports

* Free, open source
    * Can be downloaded from the [R-project](https://r-project.org) website

* Continually evolving
    * R has over 12,000 *packages* that add additional functions
]

---
class: inverse, center, middle

# But WHY?

---
# What can you do with R?

.center[![:scale 45%](images/01/whatyoucando_collage.png)]
[Source: N. D. Phillips](https://ndphillips.github.io/IntroductionR_Course/presentations/Day_0_pres.html#4)
---
background-image: url(images/01/Rcompanies.png)
background-size: contain

---
background-image: url(images/01/spss_usage.png)

# Still not convinced?

---
class: inverse, center, middle

# Getting started

---
background-image: url(images/01/RStudio-logo.png)
background-size: 30%
background-position: 80% 5%
# What is RStudio?

.large[
- An **Integrated Development Environment (IDE)**

- An interface for R that makes your life much, much easier

- Makes many things explicit that you would otherwise have to guess
]

![:scale 50%](images/01/rstudio-basic.png)
---
background-image: url(images/01/rstudiocloud_page.png)
background-size: 50%
background-position: 50% 90%

# Getting started
.large[
1. Open up a web browser

2. Go to https://rstudio.cloud

3. Sign up! Use your REAL NAME, and your University of Lincoln email address.
]

---
background-image: url(images/01/RStudioCloud.png)
background-size: contain
class: inverse

---
background-image: url(images/01/RStudioCloud_proj_circ.png)
background-size: contain
class: inverse

---
background-image: url(images/01/default_project.png)
background-size: contain
class: inverse

---
background-image: url(images/01/cloud-tools.png)
background-size: contain
class: inverse

---
background-image: url(images/01/cloud-appear.png)
background-size: contain
class: inverse

---
class: inverse, center, middle

# How it works!

---
background-image: url(images/01/proj_console.png)
background-size: contain
class: inverse

---
background-image: url(images/01/proj_console_repl.png)
background-size: contain
class: inverse

---

# How to use R

* The R Console

* REPL: Read/Evaluate/Print/Loop
    
    * Type stuff in, it tries to do it

When you see the **>** symbol -

```r
*>
```

... R is waiting for your input.

```r
> 5 
[1] 5
```

---

# Warming up

Try using R like a calculator!

### Basic arithmetic operators

|Symbol |Operation      |
|:------|:--------------|
|+      |addition       |
|-      |subtraction    |
|*      |multiplication |
|/      |division       |
|^      |exponentiation |
|%%     |modulo         |

---

# Warming up

You can break up long maths expressions over multiple lines:

```r
2 + 4 + 5 + 
  5 + 6 + 7 + 8 +
  10
```

```
## [1] 47
```

Note that when you do that, the ">" symbol changes to a "+"

```r
> 5 +
*+ 5
[1] 10
```

---

# Remember!

.large[**>** means R is waiting for input.]

```r
>
```

.large[**+** means R is waiting for you to finish your command.]

```r
+
```

Either finish your command, or press the **Esc** key to cancel it.

---

# Text input

R can also accept text strings as input.

```r
"hello world!"
[1] "hello world!"
```

You need to use quotation marks ("") to tell R that this is text:

```r
hello world!
```

```
## Error: <text>:1:7: unexpected symbol
## 1: hello world
##           ^
```

Otherwise, you'll receive an error like the one above.

---
# Why is there an error?

In R, you can assign values to an **object** for subsequent use. **Objects** have names that are written as text.

The assignment operator is the two-character symbol:

```r
*<-
```

You assign values to objects by putting the **<-** sign between the name of the object and the value you want to give it:

```r
example <- 5
example
```

```
## [1] 5
```

Note that R does not immediately provide output when you assign the output to an object.

---
# The assignment operator

.large[Think of **<-** as meaning "is now". i.e.

```r
example <- 5
```
can be read as

```r
The object "example" is now 5
```
]

---

# Working with objects

Once an object is assigned, the name that you gave it *stands in* for the *value* that you assigned to it, and can be used as if it were that value:

```r
example
```

```
## [1] 5
```

```r
example + 10 
```

```
## [1] 15
```

```r
example + 13 - 1 * 2 %% 4
```

```
## [1] 16
```

---
background-image: url(images/01/cloud_environ.png)
background-size: contain
class: inverse

---
background-image: url(images/01/cloud_environ2.png)
background-size: contain
class: inverse

---
background-image: url(images/01/cloud-history.png)
background-size: contain
class: inverse

---
class: inverse, center, middle

# Try it out!

---
# Try a few things out!

1. Assign some values to objects using the assignment operator (**<-**)

2. Try using arithmetic operations (e.g. *, /, %%) on those objects

3. Try using arithmetic operations to combine multiple numerical objects

4. Try using arithmetic operations on text

---
# Combining multiple things

Sometimes you want to allocate more than one value to an object. You can use the **c()** function to do this.

```r
c(8, 5, 10)
```

```
## [1]  8  5 10
```

```r
example <- c(8, 5, 10)
example
```

```
## [1]  8  5 10
```

```r
c("hello", "how", "are", "you")
```

```
## [1] "hello" "how"   "are"   "you"
```

## IMPORTANT: BRACKETS () AFTER A WORD MEAN THAT THIS IS A **FUNCTION**

---
# Vectors

The function **c()** is creating **vectors**.

Vectors are simply a one-dimensional collection of things that all have the same *type* (we will cover data types next week!).

Note that mixing, for example, text and numbers, will yield a *character* vector.

```r
c(5, "five", 2)
```

```
## [1] "5"    "five" "2"
```

---
# Functions

Functions are commands that operate on **objects**.

For example, to calculate the *mean* of several numbers, you can use the function **mean()**. The output of functions can also be assigned to **objects** using **<-**.

```r
mean(c(8, 5, 10))
```

```
## [1] 7.666667
```

```r
example <- c(8, 5, 10)
mean(example)
```

```
## [1] 7.666667
```

```r
example_mean <- mean(example)
example_mean
```

```
## [1] 7.666667
```

---
# Try it out!

1. Use **c()** to create a vector of numbers.

2. Use **c()** to create a vector of strings.

3. Calculate the **mean()** of a vector of numbers.

4. Try guessing some other simple statistics (e.g. other types of *average*) that you can use.

---
background-image: url(images/01/cloud-help.png)
background-size: 40%
background-position: 50% 75%
# Getting help

If you don't know how to use a function, R has built-in help!

There are several ways you can access it:

```r
help("mean")
?mean
??mean
```

---
# Packages

Packages are the key to R's versatility. Over 12000 are currently available from the **Comprehensive R Archive Network** - [CRAN](https::https://cran.r-project.org/). The **install.packages()** function can be used to install packages.

Let's install the "cowsay" package. **cowsay** is an extraordinarily useful package, as you'll see.

One way to install the package is using the console:

```r
install.packages("cowsay")
```

Once it's installed, use the **library()** function to load the package!

```r
library(cowsay)
```

But **another** way to install is using the GUI!

---
background-image: url(images/01/cloud-packages.png)
background-size: contain
class: inverse

---
background-image: url(images/01/cloud-cowsay.png)
background-size: contain
class: inverse

---
background-image: url(images/01/cloud-help.png)
background-position: 90% 85%
background-size: 40%
# Try out the **cowsay** package

**cowsay** adds a function called **say()**. Load the function in as follows, and look at the help for **say()**.

```r
library(cowsay)
?say()
```

.left-pull[
Remember that help appears in the bottom right window!

Look at **Usage** and **Arguments**

**Usage** is how to use the function.

**Arguments** are what the functions expect and understand.
]

---

```r
say(what = "Feed me, human.", by = "cat")
```

```
## 
##  -------------- 
## Feed me, human. 
##  --------------
##     \
##       \
##         \
##             |\___/|
##           ==) ^Y^ (==
##             \  ^  /
##              )=*=(
##             /     \
##             |     |
##            /| | | |\
##            \| | |_|/\
##       jgs  //_// ___/
##                \_)
## 
```

---
# Try out the say() function

1. Try a few different animals by changing the **by** argument

2. Change what the animals say by changing the **what** argument.

3. Assign the output to an object using the **<-** operator.

4. Print out the value that you assigned to the object.

---

# Additional resources

.pull-left[
![:scale 45%](images/01/R4DS.png)
]

.pull-right[
![Discovering Statistics Using R](images/01/DiscoverR.jpg)
]

There are copies of both these books in the library.

R for Data Science is available freely online at http://r4ds.had.co.nz/

---
background-image:url(images/01/hopr-cover.png)
background-size: 25%
background-position: 85%, 25%
# An additional recommendation...

## Hands-on Programming with R

Basic R programming book, also available for free online

https://rstudio-education.github.io/hopr/index.html

---
# This week's goals

1. Make sure you're signed up for [RStudio.cloud](https://rstudio.cloud)

2. Read through Chapter 1 of [R for Data Science](https://r4ds.had.co.nz/introduction.html)

3. Try out some of the introductory things mentioned in the slides, just to get a feel for using RStudio!