Lecture 4 Flashcards
What does the notation ‘n’ mean
Total number of scores/ participants
What does that notation ‘𝛴’ mean?
It means sum of all X
Define frequency distribution
Counts of values within categories of a variable. Can be shown in table form (tally chart) or in a bar chart
Define historgram
Bar chart for continuous variables to see the shape of a data distribution.
What does the peaks of a histogram tell you?
The highest peak = the mode
The number of peaks = the modality
What does the spread of data in a histogram tell you?
The variability/ variance
Define measures of central tendency
Numerical vaues referring to the centre of a distribution
When are the mean, median and mode all the same?
When the distribution is symetric and unimodal?
Evaluate the mode as a measure of central tendency
√ - Higher probability that randomly drawn value is the mode than the chances of it being another value
√ - applicable to nominal, ordinal, interval and ratio
X - May not represent central tendency at all, e.g. if distribution is skewed.
Evaluate the median as a measure of central tendency
√ - unaffected by extreme scores
X - not ideal as a basis for inferential statistics
Evaluate the mean as a measure of central tendency
√ - simple formula - most commonly used
√ - good estimator of population mean - forms the basis of inferential stats
X - requires at least interval level measurement
X - sensitive to extreme scores - distorted by outliers
Name one way of reducing outlier impact
Carrying out transformations
What are the 3 measures of central tendency?
Mean, median and mode
What are the 4 measures of variability?
The Range, the SD, the IQR and the Variance
Evaluate the range as a measure of variability
X - depends entirely on extreme values
X - Very sensitive to outliers
Evaluate the SD as a measure of variability
√ - easier to understand than variance
How do you calculate the SD?
Sqaure root of the variance
Evaluate the IQR as a measure of variability
X - discards data, which itself is arbitrary
How do you calculate the variance?
Take away each value from the mean and square it, then divide it by N-1
E.g. If the data is 3,6,9. To work out the variance you would do: (3-6)²+(6-6)²+(9-6)² / 2
Evaluate the variance as a measure of variability
√ - Very important in inferential stats
X - Quite hard to understand
