Quantitative Lecture 6 Flashcards
Probability and Distribution
What must we observe when we have a large set of data?
The distribution of the data.
What are the key features of a normal distribution?
Peak in the middle, tails off symmetrically at either side of the peak, bell shaped curve.
What are some examples of normal distribution?
IQ, height, weight, shoe size, exam grades.
Why is normal distribution important?
Many statistical tests make assumptions about how your data is distributed.
What does skewness indicate?
The extent to which your frequency histogram is lopsided rather than symmetrical.
What characterizes a positively skewed distribution?
The peak is shifted to the left, towards the low numbers, and the tail extends to the right.
What characterizes a negatively skewed distribution?
The peak is shifted to the right, towards the high numbers, and the tail extends to the left.
What is a bimodal distribution?
A distribution with 2 peaks.
What is kurtosis?
A measure of peak and flatness, or steep and shallowness.
What does a leptokurtic distribution indicate?
Higher kurtosis/ very peaked distribution.
What does a platykurtic distribution indicate?
Lower kurtosis/ flat distribution.
What is the ceiling effect?
When a measure produces most values near the top end of a scale.
What is the floor effect?
When a measure produces most values near the bottom end of a scale.
How does standard deviation affect the normal distribution?
Different curve shapes depending on different standard deviations.
How can normality be assessed?
Using histogram for visual inspection and skew and kurtosis values.
