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Study Guide

School

Ryerson UniversityDepartment

Quantitative MethodsCourse Code

QMS 102Professor

Marzieh MehrjooStudy Guide

FinalThis

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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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