Psychological Research Skills Notes.
Introduction to Statistics.
Research questions require sufficient data to significantly back up information provided.
DATA needs to be summarised (DESCRIPTIVE STATISTICS) and interpreted in systematic/ standardised way
(INFERENTIAL STATSTICS).
DESCRIPTIVE STATISTICS- Methods used to describe, summarise, and display data in order.
VISUALISE DATA- Graphs- Summarise data numerically/ using tables.
DIFFERENT TYPES OF DATA
CATEGORICAL- Discrete groups/ categories.
CONTINUOUS- Numbers that take any value on measurement scale.
(NORMINAL, ORDINAL, INTERVAL and RATIO).
1. NORMINAL- Named discrete categories.
2. ORDINAL- Vary along some continuum. (Scale etc, 1 st 2nd 3rd place). Difference between numbers not
important.
3. INTERVAL- Varies along some continuum. Difference between number is important. (EG,
Temperature). NO TRUE ZERO POINT.
4. RATIO DATA- Varies along some continuum. Difference between numbers is important/ equal. (EG.
Time, Weight). TRUE ZERO POINT.
EG. “Is it morally wrong? Yes/No” OR “How morally wrong is it? Scale 1-7”. (RATING SCALE).
Can only change data levels EMPIRICAL DATA= Info gained
downwards. from observation/
HIGHER LEVELS= MORE INFORMATION. experimentation.
DESCRIPTIVE STATISTICS
2 types of data: DESCRIPTIVE STATISTICS USED TO
CATEGORICAL ORGANISE AND DESCRIBE DATA.
CONTINUOUS
CONDUCTING AN EXPERIMENT-
How many people we ask? EG. Ask 10 people (N=10). We summarise the responses with descriptive statistics.
FREQUENCY DISTRIBUTION-
The simplest way to organise data is to plot them in a graphical form- FIRST STEP, Plot a frequency distribution
of data.
We determine the SMALLEST SCORE and the BIGGEST SCORE in data. Then for these scores and everyone in
between we count how many times it is present.
FREQUENCY DISTRIBUTION
HISTOGRAM: Can be used for ordinal, interval, and ratio data only.
BAR CHART: Used for nominal data only.
GROUPING: When the range (difference between maximum and minimum scores) is large, we group scores
together into larger chucks.
CHARACTERISTICS- PEAK
Shape TAIL
Central tendency TAIL
Variability
SHAPE-
Clear peak in the centre and the associated frequencies drop off on the tails. This is called UNI-MODAL (Uni
means ones, Mode means peak). If data has too clear peaks it is BI-MODAL (Bi means two, Mode means peak).
Introduction to Statistics.
Research questions require sufficient data to significantly back up information provided.
DATA needs to be summarised (DESCRIPTIVE STATISTICS) and interpreted in systematic/ standardised way
(INFERENTIAL STATSTICS).
DESCRIPTIVE STATISTICS- Methods used to describe, summarise, and display data in order.
VISUALISE DATA- Graphs- Summarise data numerically/ using tables.
DIFFERENT TYPES OF DATA
CATEGORICAL- Discrete groups/ categories.
CONTINUOUS- Numbers that take any value on measurement scale.
(NORMINAL, ORDINAL, INTERVAL and RATIO).
1. NORMINAL- Named discrete categories.
2. ORDINAL- Vary along some continuum. (Scale etc, 1 st 2nd 3rd place). Difference between numbers not
important.
3. INTERVAL- Varies along some continuum. Difference between number is important. (EG,
Temperature). NO TRUE ZERO POINT.
4. RATIO DATA- Varies along some continuum. Difference between numbers is important/ equal. (EG.
Time, Weight). TRUE ZERO POINT.
EG. “Is it morally wrong? Yes/No” OR “How morally wrong is it? Scale 1-7”. (RATING SCALE).
Can only change data levels EMPIRICAL DATA= Info gained
downwards. from observation/
HIGHER LEVELS= MORE INFORMATION. experimentation.
DESCRIPTIVE STATISTICS
2 types of data: DESCRIPTIVE STATISTICS USED TO
CATEGORICAL ORGANISE AND DESCRIBE DATA.
CONTINUOUS
CONDUCTING AN EXPERIMENT-
How many people we ask? EG. Ask 10 people (N=10). We summarise the responses with descriptive statistics.
FREQUENCY DISTRIBUTION-
The simplest way to organise data is to plot them in a graphical form- FIRST STEP, Plot a frequency distribution
of data.
We determine the SMALLEST SCORE and the BIGGEST SCORE in data. Then for these scores and everyone in
between we count how many times it is present.
FREQUENCY DISTRIBUTION
HISTOGRAM: Can be used for ordinal, interval, and ratio data only.
BAR CHART: Used for nominal data only.
GROUPING: When the range (difference between maximum and minimum scores) is large, we group scores
together into larger chucks.
CHARACTERISTICS- PEAK
Shape TAIL
Central tendency TAIL
Variability
SHAPE-
Clear peak in the centre and the associated frequencies drop off on the tails. This is called UNI-MODAL (Uni
means ones, Mode means peak). If data has too clear peaks it is BI-MODAL (Bi means two, Mode means peak).
