Research Methods- Distributions Flashcards
Histogram:
Displays the frequency of continuous numerical data. The frequency is placed on the Y-axis, and the continuous variable (e.g. test scores, age group, time scales, weight, height, income level) is on the X-axis.
Normal distribution:
When recording the frequency distribution of certain variables (e.g. IQ, height, weight), the graph forms a naturally occurring symmetrical bell-shaped distribution curve. More participants are in the middle, with few participants on either side
Characteristics of normal distributions - Measures of central tendency
Mode: Highest/midpoint. The highest point in a histogram is the most frequent score
Median: Highest/midpoint. An equal number of scores on either side (symmetrical)
Mean: Highest/midpoint. An equal number of outlier scores on either
Characteristics of normal distributions - Standard deviations (SD):
When data is normally distributed, 68% of scores in the data set fall within one standard deviation of the mean, and 95% of scores are within two standard deviations of the mean.
Statistical infrequency:
How far someone’s score is from the mean score (measured in SD) is one way of defining abnormal behaviour.
One of the criteria for a diagnosis of Intellectual disability (ID) is an IQ 2 SD below the mean, an IQ of 70.
Skewed distribution:
The distribution of scores is asymmetric. Most of the scores are on one side, with long skews (tails) on the opposite side to the majority of scores
Positive skew
More scores at the lower end of the graph, outliers at the higher end.
Negative skew:
More scores at the higher end of the graph, outliers at the lower end.
Characteristics of skewed distributions - Measures of central tendency
Mode: As the mode is the most frequent score, it remains at the highest point.
Median: At the point where 50% of the graph is either side (between mode & mean)
Mean: Shifted towards the outlier scores in the long tail (skew)
