⭐ • Research Methods: Correlation, Measurement, Design & Hypothesises Flashcards

Question

What is an **Independent Groups** design?

Answer 1

When you have 2+ groups with different participants and you **compare them together** e.g 12A compared to 12B

Answer 2

* **+VE** = Practically, least time consuming * **+VE** = Less likely to get practice or **fatigue effects** as participants not repeating anything * **-VE** = No control over individual/ environmental differences

Answer 3

When you have 2+ groups with different participants and you compare them together BUT **both groups match people on individual differences** e.g. age, sex, etc... e.g. Raine matching his 2 groups by having same ammount of schizophrenic participants * Attempting to negate -VE of Independent Groups by pairing people very closely on individual differences

Answer 4

* **+VE** = Much more controlling, increased validity due to control over individual differences * **-VE** = Very time consuming due to requirement to exactly match participants

Answer 5

When you have only 1 group, but **each participant provides multiple (2+) data points**. A single group but repeating measurements for same individuals

Answer 6

* **+VE** = Controlled completely for individual differences as only one group * **-VE** = Participants suceptable to **practice** or **fatigue effects** (Participants could produce better results as they have done it so many times before OR due to same people repeadedly doing tests, results could become worse as participants would become more tired) - **Lowering Validity**

Answer 7

* **Practise effects** - When participants produce better results as they have done the test or experiment multiple times before * **Fatigue effects** - When the same people repeadedly do tests and as a result, results could become worse as participants would become more tired

Answer 8

**Something done to even out (average) order effects within a repeated measures design** Repeated measures has a problem of order effects, way to fix is to counterbalance e.g: * 1/2 participants recieve condition A first, followed by condition B * 1/2 participants recieve condition B first, followed by condition A This acts as a counterbalance as when people doing condition A last benefit from practice effects, an equal number of the people doing condition B last will **also** benefit from practice effects **- thus the effects cancel eachother out**

Answer 9

**Something that is done in relation to a independent groups design** * When using independent groups there is an issue with individual differences, one way to control differences between the 2 groups is to decided who gets put into each group randomly, so in theory they should be similar

Answer 10

* Nominal * Ordinal * Interval

Answer 11

The most basic level of measurement. It's used when data is put into **tally charts/ categories**. For this reason, its sometimes referred to as *category data*

Answer 12

* **+VE** = Very easy to analyse due to it being so basic, usually reliable * **-VE** = Gives very little information as it is basically a headc count, it only tells us how many people are in each group

Answer 13

This is used when data can be put into order e.g. 1st, 2nd, 3rd (ranking data). Although, it **cannot tell us the distance between rankings**/ units of measurements are not definable sizes e.g. between 1st and 5th, therefore can't tell us any relation between the numbers | ('Ranking' data - we used on self-reported levels of aggression)

Answer 14

* **+VE** = providing information about preferences, rankings, and degrees of something (e.g. degrees of aggression) * **-VE** = Usually based on opinion therefore it tends to be *subjective* rather than objective

Answer 15

The most complex level of measurement. There is an **equal** gap between each unit of measurement e.g. like in cm, where the gap between 2 and 3cm is identical to that of between 10 and 11cm (Having **interval scales**)

Answer 16

* **+VE** = Not subjective, completely objective as any person can get the same, standardised result * **-VE** = The **lack** of a **true zero**. In the interval scale, there is no “true” starting point. They do not start at 0 even though one value is labeled zero. This means that zero does not signify an absence in our dataset

Answer 17

A true zero refers to a scale where 0 indicates the absence of something. **An interval scale lacks a true zero**. Examples of scales without a true zero include temperature as 0° doesnt mean there is no temperature

Answer 18

Interval scales measure data with **equal distances between points**. This means that the difference between 10 and 20 is the same as the difference between 30 and 40

Answer 19

A statement of what you belive to be true

Answer 20

* H1 - Alternative Hypothesis * H0 - Null Hypothesis

Answer 21

A hypothesis that infers that the results gathered **will yield a significant result/ relationship/ correlation** e.g. **There will be** a significant relationshuip between X & Y

Answer 22

A hypothesis that infers that the results gathered **will not yield a significant result/ relationship/ correlation** e.g. There will **not** be a significant relationshuip between X & Y

Answer 23

That any relationship shown is purely due to chance

Answer 24

The **direction** of your hypothesis

Answer 25

* A hypothesis that states the **kind** of difference between the two conditions or two groups of participants e.g. higher or lower, faster or slower etc.. * It infers the expeirment will go **one way**

Answer 26

* A hypothesis that states that there **is** as difference between two conditions or groups of participants, but it doesnt explicitly state what said difference is * It infers the expeirment will go **either one way**