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Ryerson University
Quantitative Methods
QMS 102
Douglas Mc Kessock

(Qualitative) Categorical data: The make of a car. (Quantitative) Numerical Data: km/h. # of seats. Rolling a die Nominal: No particular order or ranking. Do you have allergies? Interval: Data has a unit of measure. 0 is arbitrary. It can exist Marital Status. What sport you play. Eye color. Car brand. CountrTemperature. IQ. SAT score. Ordinal: There is a natural order to the data. 80%>70% Ratio: 0 means the absence of data. # of vacations you’ve taken Professor > Lecturer. Gold medal > silver. Excellent > poor serviDistance from home. Gas price. Size of house. $. Height. Weight (#of red race car: Nominal) (mt. Everest height above sea level: interval cont.)Continuous: Infinite Numbers. Speed of car. Height of person. (Height w/o shoes: ratio continuous) (year you graduated: intervalDiscrete: Limited values. # of sexes. # of seats. Rolling a die (In what "gate" was the number 7 horse in the 5th race: Ordinal) (highest lvl of education: HS, college/uni, master, PHD, technical: nominal) (rate overall health on a “5 point scale: ordinal) (shoe size: ratio discrete) (age on your last birthday: ratio discrete) (whats ur IQ: interval discrete) Mean (average) = Total of values / Total # of values Median (middle value): Find rank: n+1/2. Use that rank to find median in list. Mode (# that comes most) Frequency Distribution: 5-10 classes Class Width = Range/# of classes = (largest-smallest)/5 - Round to nice number Skew Left. No Skew. Skewed Right. Nice Numbers = 1 2 2.5 5 10 20 25 50 100 200 250 500 1000 Lower - Upper Freq. (# Relat. % Cumulative Limit
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