Week 4: Review of Descriptive Statistics Flashcards
Descriptive Statistic
simply describes data collected
screen data and observe trends
Inferential Statistics
Use the sample to infer something about the population
Test whether a difference/relationship seen in the sample data is sufficiently large enough to accept it may be real in the population
Allows us to tests hypotheses and make decisions based on sample data
Measures of central tendency
Mean, Median, Mode
Mean
The average
Median
central point when all scores ranked from largest to smallest
Mode
highest frequently occurring score
Measures of variability
Sum of Squares Variances Standard Deviatoin Range Standard Error
Sum of Squares
the sum of the square of variation
Variance
Tells us the degree of spread in your data set.
The more spread the data, the larger the variance is in relation to the mean
Standard Deviation
average deviation from the mean
Range
the measure from the smallest measurement to the largest one
smallest minus largest
Standard Error
Indicates how different the population mean is likely to be from a sample mean
Shape of the Distribution
Modality, Skew, Kurtosis
Modality
Number of peaks.
Unimodal: scores vary around one central point
Bimodal: scores vary around two points
Skew
where data is centred
Kurtosis
How pointy or smooth the distribution is.
Leptokurtic: pointy
Platykurtic: flat ‘plateau’
Assumptions of normality
Unimodal distribution
Moderate peakedness
Symmetrical tails
Degrees of Freedom
the number of values in the final calculation of a statistic that are free to vary
Z scores
tells us how many SDs away from the Mean a particular score is
