Lecture 2 Flashcards
Summary statistics (6)
- Number of observations
- Measures of central tendency
- Skewness
- Kurtosis
- Minimum & Maximum
- Variance and Std. deviation
Measures of central tendency
- Mean
- Mode
- Median
Which measure of tendency to use? Nominal data
Mode
Which measure of tendency to use? Ordinal data
Median
Which measure of tendency to use? Interval/ ratio, not skewed
Mean
Which measure of tendency to use? Interval/ratio skewed
Median
Skweness
Says something about the shape of the distribution, symmetry of the distribution compared to normal.
left tail - negatively skewed
right tail - positively skewed
Kurtosis
Says something about the shape of the distribution, the degree to which scores cluster at the tails.
Leptokurtic - pointy >3
Platykurtic - round <3
Variance
Measures how far the dataset is spread out. The higher the variance, the more the variables are spread out.
Sum of squares
Sum of all squared deviations
Deviation form the mean
Value of the observation minus the mean
Standard deviation
Square root of variance, tells something about the heterogeneity of your sample
Standard deviation calculation
- Deviation from the mean
- Sum of squares
- Variance
- Standard deviation
The directionality problem
The existence of a correlation tells us nothing about the direction of the correlation
P-value
The probability that such an extreme outcome occurs, assuming that the null hypothesis is true. “sig” value in statistics. If P is less than your confidence level, reject H0
