# Stats for Research Methods

### Link to PDF slides

Fair warning: These might not make sense outside of the context of the course since some of these slides refer to material distributed during the course.

Nobody even cracked a smile when I showed this slide, which tells you just how stressed people were about this course. Photo courtesy of Bhawna

In my third semester at IDC, I was a teaching assistant for the Design Research Methods (DRM) course. Students were expected to have prior knowledge of some statistical concepts, but a lot of students hadn’t studied math or statistics in a few years and found the class hard to follow. I taught a supplementary class that started with an intuitive (I hoped) understanding of some of these basic ideas.

# Index of terms

## Types of Research

- Qualitative
- Quantitative

## Types of Research Methods

- Observational - observe and record
- Correlational - relationship b/w 2 variables
- Experimental - consuct a lab experiment

### Research question

A question about an area of interest. Eg. Is the proportion of women in design higher than in engineering?

### Hypothesis

A statement about the relationship between 2 variables. Eg. There is no difference between proportion of women in engineering and design.

## Experiment Design

An experiment is conducted to find the effect of one variable on another.

For eg.

- The number of hours of sleep the night before an exam, and the marks scored.
- Two different designs of a chair, and the average rating on a scale of 1 to 10 when people were asked to rank comfort.

### Independent variable (or Manipulated variable)

The variable we can control. Eg. hours of sleep, design of chair.

### Dependent Variable (or Response variable)

The variable that varies because we changed the independent variable. Eg. marks in test, comfort rating

### Control Variable

Circumstance not under investigation that is kept constant while testing.

### Random variable

Circumstance not under investigation that is allowed to vary randomly.

### Confounding variable

Circumstance not under investigation that has impact on the dependent variable.

So we can say that experiment is conducted to find the effect of changing *independent variable* on *dependent variable*, but we might get a fake result because of the *confounding variable* also impacts the dependent variable.

### Levels of a variable

The number of possible states of a variable are called the levels of the variable.

For eg. in our experiment we can have 3, 5, 7, 9 hours of sleep, so hours of sleep variable will have 4 levels.

### Between subjects

- A is given design 1. They rank it 5/10.
- B is given design 2. They rank it 6/10.

We can say that B is better, but it’s possible that B was just more generous with the rating and would have given design 1 a 6 as well.

### Within subjects

- Subject A is given design 1. They rank it 5/10.
- Subject A is given design 2. They rank it 6/10.

### Order effects within subjects

Design 1 and 2 share some elements. If you learn to use 1, 2 is easier to use. Therefore if you use 1 first or 2 first will impact the ranking.

Therefore, we give half of the people design 1 first and the other half design 2 first.