3. Data Recording, Planning and Analysis Flashcards
Raw Data
Raw data is the data psychologists collect from each participant
Levels of Data: Nominal Data
When the data is split into categories as to how often they occur. This is the most basic type of data gathered.
Levels of Data: Ordinal Data
This type of data is the individual’s data, psychologists can then rank each person and put them in order of how well they did.
Levels of Data: Interval Data
Has equal intervals, this type of data ranks the participants.
Levels of Data: Quantitative Data
Quantitative data is numerical data.
S: Allows comparisons between participants or groups. Easily summarized and can use descriptive statistics.
W: Lacks ecological validity as it cannot reflect how we respond in everyday life, and has a limited amount of detail.
Levels of Data: Qualitative Data
Qualitative data consists of decorative words regarding how participants are feeling.
S: Provides rich, detailed information, thus making it more valid.
W: Can often be hard to summarize and quantify data.
Levels of Data: Primary Data
When information i collected directly from the participants.
S: Psychologists know that controls were in place, thus making the data more reliable.
W: Primary data can be difficult or expensive to collect and some data may have already been collected.
Levels of Data: Secondary Data
Data that has already been collected but is accessible for the psychologist.
S: sometimes data that cannot be collected firsthand or is too expensive to collect is accessible.
W: May be affected by extraneous variables and vital information may be excluded.
Descriptive Statistics: Measures of Central Tendency, Mean
Calculate the mean by adding all the values and dividing the total by the number of values. Can be used on both discrete and continuous data.
S: All the data is used to calculate an average.
W: Very large or small numbers can distort the result (outliers)
Descriptive Statistics: Measures of Central Tendency, Median
Calculated by finding the middle number when all the values are put in order.
S: Very big or small values cannot affect the result (outliers).
W: Takes a long time to calculate for a very large set of data, and doesn’t represent the whole data set.
Descriptive Statistics: Measures of Central Tendency, Mode
The data that occurs most frequently.
S: The only average we use when the data is not numerical.
W: There may be more than one mode, or no mode at all if none of the data is the same. It is also less likely to accurately represent the data.
Descriptive Statistics: Measures of Dispersion, Range
The highest value in the data set take away the lowest value in the data set.
Descriptive Statistics: Measures of Dispersion, Variance
A measure of how much values in a data set differ from the mean.
Descriptive Statistics: Measures of Dispersion, Standard Deviation
The standard deviation is how much the data is spread from the mean. The square root of variance is the SD.
Descriptive Statistics: Ratio
The measure of two or more variables and the rate at which they change together. Calculated by dividing the bigger number by the smaller one.
Descriptive Statistics: Frequency Tables (tally charts)
A simple way of presenting data is o show a tally of the behaviour using a frequency table (records how frequently the behaviour occurs)
Descriptive Statistics: Line Graphs
A line graph is most useful to show the profession/regression of behaviour over a period of time.
*Always label axis and include a title
Descriptive Statistics: Pie Charts
Pie charts are helpful to show behaviour statistics and percentages as a proportion of a total.
* Ensure to include a title and key for each section of the chart.
Descriptive Statistics: Bar Graph
A useful and meaningful way to represent data as it is simple.
*Label axis and include a title
Descriptive Statistics: Histograms
Used only for continuous data.
*Include labels and a title