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# QMS 102 Quiz: QMS102 Quiz: Ch 1, 3

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Ryerson University

Quantitative Methods

QMS 102

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Winter

Description

QMS Chapter 1
Qualitative data
• Also known as numerical data.
• Numeric data resulting from measuring
• Aset of data can either be continuous or discrete quantitative data
o Continuous: numerical responses that arise from a MEASURING process. Ex: time, the amount of rainfall, weight, age
o Discrete: numerical responses that arise from a COUNTING process. Ex: the amount of courses one is enrolled in, number
of items purchased at a store
Quantitative data
• Consists of data values that describe the characteristics or features of an item. Ex: rating an instructors teaching skills as “excellent”,
“good”, “poor” gathers qualitative data because the answers are non-numeric values. (However, qualitative data can involve
numbers. Ex: area codes, bank accounts)
Measurement Scales
Ratio: Quantitative
• Highest level of scale
• 0 means “nothing”
• Discrete examples: number of DVDs you own, number of vacations you’ve taken), age
• Continuous examples: distance (km), gas prices
Interval: Quantitative
• Data that has units of measurement
• Must be numeric, either discrete or continuous quantitative
• Intervals between data all have a meaning, 0 does not mean “nothing”. Example: data on temperature (0 does not mean there is no
heat), calendar scales
Ordinal: Qualitative
• There is a natural order to the categories involved and that one category is better than another
• Numeric or non-numeric, but still qualitative (bar, pie charts)
• Example: letter grades (A+, A, A-, B+, B, B- … etc), rating a service “excellent, good, average, poor, very poor”, tv ratings
Nominal: Qualitative
• Lowest level of scale
• Data that has no particular order or ranking in their categories (alphabetical order is not a consideration)
• Numeric or non numeric
• Example: marital status 1 = single 2 = marries 3 = widowed. Even though the data is recorded as numerical, it is still qualitative
• Calculations can only be based on the amount of responses in each category (bar and pie charts)
• Ex. Postal codes, car brand, eye colour, check out lanes
Differentiate between interval and ratio scales
• Using 0:
o For interval scale, 0 is a reference point. 0 degree does not mean “no temperature”
o For ratio scale, 0 is meaningful where 0 means “absence of the characteristic”. Ex. 0 textbooks mean no textbooks
• Comparing two values
o Interval scale has meaningful difference between two values. If locationAis 10 degrees and location B is 5 degrees,
locationAis not twice as hot as B – but there is a difference of 5%.
o Ratio scale has meaningful division of two values. If employeeAearns $20 per hour while employee B earns $10, we can
say that employeeAmakes twice the amount as B. QMS Chapter 3 – Graphical Presentation of Quantitative Data
Stem and leaf plot
• Summarizes the distribution or shape of a set of quantitative data
• Finds min, max and the mode
Rules to construct stem
• Must have 6-13 stems
• Stem values should be consecutive or repeated numbers. Numbers can only be repeated twice or 5 times
• Must be one leaf associated with the first and last stem
Rules to construct leaf
• Leaf for each data value is the next single digit after the stem
• When the stems are repeated twice, the leaves values 0-4 go to the first stem and 5-9 go to the second stem.
• When the stems are repeated five times, the leaves values 0-1 go to the first stem 2-3 go to the second, 4-5 go to the third and so on.
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