Exhaustive Lecture Summaries on Investigating Psychology 2 (PSY1119)
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Investigating Psychology 2 (PSY1119)
Instelling
Edge Hill University (EHU)
This sheet is a summary of the notes made for the PSY1119 - Investigating Psychology 2 module it includes notes on most, if not all the methods used in the first year. These include Descriptive Statistics, Parametric Tests and Non-Parametric Tests.
The document also provides a brief tutorial on ...
Summary Sheet
This sheet summarises the notes made for the PSY1119 - Investigating Psychology 2 module. It includes
notes on most, if not all, the methods used in the first year. These include Descriptive Statistics,
Parametric Tests and Non-Parametric Tests.
The document also provides a brief tutorial on carrying out these tests in IBM SPSS, which is the standard
in most BPS-accredited modules.
Although these notes provide a complete overview, I would advise you to use these alongside your texts.
As the summation of both will help you thoroughly understand the topic of experimental methods •ᴗ•
Contents
PRINCIPLES OF EXPERIMENTS IN PSYCHOLOGY -------------------------------------------------------------------------- 2
DESCRIPTIVE STATISTICS --------------------------------------------------------------------------------------------------------- 3
MEASURES OF CENTRAL TENDANCY (AVERAGE RESPONSE) ----------------------------------------------------- 3
MEASURES OF DISPERSION ---------------------------------------------------------------------------------------------------- 3
PARAMETRIC TESTS ----------------------------------------------------------------------------------------------------------------- 4
DEPENDENT T-TEST --------------------------------------------------------------------------------------------------------------- 4
INDEPENDENT T-TEST ----------------------------------------------------------------------------------------------------------- 4
LEVENE’S TEST --------------------------------------------------------------------------------------------------------------------- 5
KOLMOGROV-SMIRNOV TEST (K-S TEST) --------------------------------------------------------------------------------- 5
OUTLIERS IN SPSS ----------------------------------------------------------------------------------------------------------------- 6
NON-PARAMETRIC TESTS --------------------------------------------------------------------------------------------------------- 7
MANN WHITNEY TEST ----------------------------------------------------------------------------------------------------------- 7
WILCOXON SIGNED-RANK TEST --------------------------------------------------------------------------------------------- 8
APA FORMATTED TABLE ------------------------------------------------------------------------------------------------------- 9
GOODNESS OF FIT TEST -------------------------------------------------------------------------------------------------------- 10
2X2 CHI SQUARED ---------------------------------------------------------------------------------------------------------------- 11
CRONBACH ALPHA (Α) ---------------------------------------------------------------------------------------------------------- 12
PEARSONS R ------------------------------------------------------------------------------------------------------------------------ 13
1
, 2
PRINCIPLES OF EXPERIMENTS IN PSYCHOLOGY
THE PURPOSE OF A PSYCHOLOGY EXPERIMENT
❖ We use an experimental method that manipulates one factor (the IV) to examine if this
manipulation produces a change in another factor (DV) – establishing a cause & effect
relationship.
❖ The Independent Variable (IV) is the cause and is manipulated
❖ The Dependent Variable (DV) is the effect and is measured (controlled)
OPERATIONALISATION
❖ The specific steps or procedures required to translate abstract concepts into concrete, testable
variables and measures which are unambiguous
EXPERIMENT TYPE
Experiment Statistical
Description
Type Test
These are typically Lack of control – natural
carried out in a natural experiments have no control over the
setting environment & other extraneous
variables
t-test
Quasi/Natural Non-random
or
Experiment allocation of Not replicable – due to the
ANOVA
participants researcher’s lack of control, research
procedures cannot be repeated
Cofounding variables
are likely to be present
Manipulated IV Attempting to establish cause and
Random allocation of effect by having high experimental
t-test
participants validity
True Experiment or
ANOVA
Emphasis on internal Control of extraneous variables is
validity necessary
SAMPLING METHODS
Method Description
Random
Every member of a target population has an equal chance of being selected
Sampling
Systematic Uses a pretermitted system to select the participants, e.g. every fourth person in
Sampling a list
Stratified Researcher stratifies the target group into the section, each representing a key
Sampling group or characteristic (strata)
Opportunity Consists of researcher selecting anyone who is available and willing to take
Sampling part in the study
Volunteer
When participants self-select to become part of a study
Sampling
FACTORS AFFECTING EXPERIMENTS
Factor Description
The experimental effect is consistent and stable, and a different group of
Reliability
researchers could replicate it with the same findings
Validity How accurate is the causality of the behaviour?
Floor Effect The task should not be too difficult
Ceiling Effect The task should not be too easy
Extraneous Factors which may affect the DVs, in the same way, creating ‘noise’ in the data,
Variables making the measurement unclear
Confounding Something that affects the two IVs differently, leading to mistaken conclusions
Variables about what the DV was affected by
2
, 3
DESCRIPTIVE STATISTICS
MEASURES OF CENTRAL TENDANCY (AVERAGE RESPONSE)
One of the first things we might want to measure is what constitutes a typical value of a dataset (average/normal
response) which gives us an idea of how people behave/respond
MEAN
∑𝑛
𝑖=1 𝑥𝑖 𝑥1 +𝑥2 +𝑥3 +⋯+𝑥𝑛
❖ The average response, sample mean (x̄) is calculated by 𝑥̅ = 𝑁
= 𝑁
∑ = sum of all the numbers in the group
i = the starting position, we start at the first item therefore i=1
N = number of items in the sample
x = the item
MEDIAN
𝑛+1
❖ The middle value, calculated by 2
= 𝑛𝑡ℎ where n the number of all items and is even
𝑛−1 𝑛+1
( + )
▪ Use 2
2
2
= 𝑛𝑡ℎ if n is odd
MODE
❖ The most common response (occurs most frequently)
MEASURES OF DISPERSION
The larger the number, the greater the dispersion (variability), the lower, the more representative is our data
RANGE
❖ The difference between the highest number (max) and the lowest number (min)
DEVIANCE
❖ Deviance is the difference between each plot on a line chart and the mean line,
calculated by ∑(𝑥𝑖 − 𝑥̅ )
• Deviance in the above example would be (xi – 3.56)
SUM OF SQUARED ERRORS
❖ Sum of deviances (errors from the mean)
❖ Each error value must be squared before adding up to create a positive number
i.e. -2.562 = 6.5536
▪ ∑(𝑥𝑖 − 𝑥̅ )2
VARIANCE (SD2)
❖ Variance describes how far each value in the data set is from the mean
∑(𝑋− 𝑋̅)2
▪ 𝑜2 = 𝑁
STANDARD DEVIATION
❖ SD is the most common measure of variation, it is the square root of the variance
❖ Takes the variance2 and returns it to the original measure: 𝑆𝐷 = √𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒
3
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