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

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School
Ryerson University
Department
Quantitative Methods
Course
QMS 102
Professor
all
Semester
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. • N
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