Types of Data (RM P2) Flashcards
What is Qualitative Data?
Non-numerical data expressed in words (e.g diary extracts)
Pros and cons of qualitative data
+ rich in detail (more meaningful)
- difficult to analyse
What is Quantitive Data?
Numerical data (e.g reaction time in milliseconds)
Pros and cons of quantitative data
+ easier to analyse and identify data
- less detail
What is primary data?
‘First hand’ data collected for the purpose of the investigation
Pros and cons of Primary Data
+ Directly relevant data, more valid
- Requires more time and effort. Ethical considerations need to be taken into account
What is Secondary Data?
Collected by someone other than the person conducting the research e.g the work of other psychologists or government statistic
Pros and cons of Secondary Data
+ Minimal effort, therefore inexpensive and less time consuming
- Unknown quality or relevance, less valid
What is Nominal Data?
Qualitative values, usually tallied, frequencies (not able to rank)
e.g Nominal Data
- Gender
- Weather
- Ethnicity
- Marital status
What is Ordinal Data?
Scaled or ranked data (ordered), will be subjective ratings, often seen as a score
e.g Ordinal Data
1-5 on Likert Scale (can’t do division/multiplication
What is Interval Data?
Ranked with equal measurement intervals/standardised measurements and units, objective with arbitrary zero (uses pre-existing measurement scales)
e.g Interval Data
- Time
- Temperature
- Bank balance
(Increments are an equal distance apart)
What is Ratio Data?
Same as Interval, but includes an absolute zero
e.g Ratio Data
- Cash
- Distance
- Weight
adv and disadv mean
+ Takes account of all values to calculate the average
- Very small or very large values can affect the mean
adv and disadv mode
+ only average that can be used if the data set is not in numbers (e.g colours of cars in a car park)
- Can be more than one mode: not always representative of the data
adv and disadv median
+ Not affected by very large or very small values
- Median value may not actually be a number in the original data set
adv and disadv range
+ Simple and easy to understand way to assess the spread of data
- Can be sensitive to extreme values and may not be a robust measure in the presence of outliers
adv and disadv standard deviation
+ Based on all observations and is amenable for further mathematical treatment
- Cannot be exactly calculated for distribution with open-ended classes (e.g >100)
What is a measure of Central Tendency?
- Measure of the central point in a set of values
- Most common measure of central tendency are:
mean —> interval
median —> ordinal
mode —> nominal
What is a measure of Dispersion?
- Describes the spread of data
- Most common measures of dispersion are:
range, standard deviation (average spread of values around the mean)
What is a bar chart used for?
- Nominal data only (separated bars)
- Height of bars represent frequencies
What is a histogram used for?
- Continuous data: ordinal, interval, ratio (no gaps between bars)
- Shows frequency of data in successive numerical intervals
- IV plotted along x-axis, DV plotted along y-axis
What is a contingency table used for?
- Raw scores displayed in columns and rows
- Often asks you to draw conclusions from the data
What is a scatter graph/scattergram used for?
- Gives good visual picture of relationship between 2 varliables
- Aids interpretation of correlation coefficient
Negatively skewed distribution
- Mean: pulled towards lower end (left) due to extreme low scores
- Median: middle value when all scores are arranged in order, falls between mode and mean
- Mode: highest point (most frequent) located to the right
- Mean<median<mode
Positively skewed distribution
- Mean: pulled towards higher end (right) due to extreme high scores in the tail
- Median: middle value when scores are ordered, falls between mode and mean
- Mode: highest point of the distribution (most frequent), located to the left
- Mode< median< mean
