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QMS 230
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Quantitative Methods

QMS 230

Douglas Mc Kessock

Fall

Description

Chapter 1
Population: Consists of all of the members of a group about which you want to draw a conclusion
- Parameter: Numerical measure that describes a characteristic of a population
Sample: Portion of the population selected for analysis
- Statistic: Numerical measure that describes a characteristic of a sample
Discrete: When the data has a limit for example number of people on a bus, doesn’t go into decimals, and can’t be
made more accurate
Continuous: If it can go into decimals for example height, time, distance, area, volume, weight, money
Categorical (Qualitative) Data
Nominal – Its answers that have categories without order. Example:
Marital Status: Single, Married, Divorced or Widowed
Colors of cars: Red, Black, Blue, etc.
Ordinal – Its answers that have categories with order but with rankings Example:
Letter Grades: A+, A, A-, B+, etc.
st nd rd
Order in sports win: 1 , 2 , 3 , etc.
Professorial Rank: Lecturer, Assistant Professor, Professor, etc.
Numerical (Quantitative) Data Summary Table:
- A summary table indicates the frequency or percentage of
Interval – It can’t be Doubled
items in a set of categories so that you can see differences
Example:
between categories.
- A summary table lists the categories in one column and the
Temperature
frequency or percentage in a different column or columns.
Calendar
Summary Table of Primary Banking Institution By Student
Ratio – It can be Doubled
Cumulative
Example: Frequency Percent Valid Percent Percent
Valid Bank of Montreal 3 11.5 11.5 11.5
CIBC 8 30.8 30.8 42.3
Hourly Income Citizen Bank 1 3.8 3.8 46.2
National Bank 1 3.8 3.8 50.0
Weight Royal Bank 7 26.9 26.9 76.9
Scotia Bank 2 7.7 7.7 84.6
TD Bank 4 15.4 15.4 100.0
Chapter 2 Total 26 100.0 100.0
Ordered Array – a sequence of data ranked from smallest to largest
Frequency distribution: Bar Chart:
- A summary table in which data - Shows Each Category
are arranged into a numerically - to Compare %s in different Cats
ordered class groupings - Comparing 2 cats together
Pie Chart:
- To observe the portion of the whole
- Comparing 1 cat to another
Stem and Leaf:
- To organize a small amount of data in an
easy to understand diagram Range: Max-Min
Class Width: Range/7 Round
to a nice Number
Lowest Level Limit: Nice
value near Min
Frequency: # of Times it
appears
Relative Frequency: Histogram - Bar graph
Presentation of a Frequency Polygon – Line graph
Frequency/Total makes %
Cumulative Frequency: Distribution Presentation of a Frequency
- Frequency and normal point Distribution (%)
Frequency Added
Cumulative Relative - percentage histograms (rf) can - Frequency and Mid-points
be used when comparing - percentage histograms (rf) can
Frequency: % Added up
be used when comparing
Ogive
using a frequency distribution
needs crl
uses upper boundary for each class
When looking at calories per serving, when its less then do it normally, when its more than then
usually subtract by a hundred
For %s when its most, do it normally, but when it says least then subtract % by hundred and
then search
Weighted Mean: X= data w= Grouped Data Mean: If its in Median: If mean and median
weights (number of employees) frequency table, use midpoints as close, mean is the way to go
XW+XW+XW…/total weight data If mean and median are not close,
median is the way to go because

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