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Study Guide

QMS 102- Final Exam Guide - Comprehensive Notes for the exam ( 23 pages long!)


Department
Quantitative Methods
Course Code
QMS 102
Professor
Marzieh Mehrjoo
Study Guide
Final

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Ryerson
QMS 102
Final EXAM
STUDY GUIDE

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QMS 102 - Chapter Notes
Chapter 1
Statistics: the science of conducting studies to collect, organize, summarize, analyze,
and draw conclusions from data in order to make effective decisions. (transforming
data into useful information for decision makers)
Helps transform numbers into useful information for decision makers
Helps quantify & identify the risks in a business decision
Helps you understand and reduce the variation in a decision making
process
Descriptive Statistics: Collecting, summarizing, visualizing, presenting and analyzing
data
Collect data
Summarize, visualize, present data
Analyze data
Inferential Statistics: Using data collected from a small group to draw conclusions about
a larger group
Estimation
Hypothesis testing
Variable: a characteristic or attribute of an object contained in a set of data
Random Variable: a variable whose values are determined by chance
Data: values (measurements or observations) that variables assume
Collection of data values is a data set
Data List: unorganized data
Data Array: orderly presentation of data (Ascending od descending)
o Order Array: sequence of data (shows range, identifies outliers)
Quantitative data (numerical data): numeric data that can be ordered, ranked or
measured.
Discrete data: data that can be counted
Continuous data: data that are measurable and can assume any infinite number
of values (decimals or fractions can always get more specific)
Interval: data is ranked in order and precise differences between units of measure
can be determined. No meaningful zero starting point (temperature)
Ratio: data is ranked in order and precise differences between units of measure
can be determined. Meaningful zero starting point (height, weight, time)
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Qualitative data (categorical data): non-numeric data that can be categorized according
to a characteristic or attribute
Nominal: data classified into mutually exclusive categories without order or rank
(Bar, Pie and Pareto Charts)
Ordinal: classified into categories that can be ranked in order (Bar and Pie
charts)
Population: all subjects under study
Measured by Parameter: numerical measure that describes a characteristic of a
population
Sample: subset of a population
Measured by Statistic: numerical measure that describes a characteristic of a
sample
Process for Examining and concluding from data: DCOVA
Define the variables
Collect the data
Organize the data (develop tables)
Visualize the data (develop charts)
Analyze the data (examine tables and charts)
Sources of Data:
Data distributed by an organization or an individual
A designed experiment
A survey
An observational study
Chapter 2
Categorical Data
Tallying Data
o One Categorical Variable
Summary Table: indicates the frequency, amount or percentage
of items in a set of categories so that you can see differences
between categories (Bar, Pie or Pareto Chart)
o Two Categorical Variables
Contingency Table: used to study patterns that may exist between
the responses of two or more categorical variables (Side-by-side
bar chart)
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