mgcr 271

# mgcr 271 - McGill University BCom Program Statistics...

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McGill University BCom Program Statistics MGCR-271 Sept. 2011 Session 1

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Introduction Instructor Course Outline/Textbook Notes/slides Assignments (5) Midterm Exam (Friday, October 14 th . 12noon – 2pm.) Final Examination
Information from Course Outline Introduction/Chapter 1 (Sept 1/2011) Descriptive Statistics Read: The Practice of Business Statistics Moore, McCabe, Duckworth, Alwan, 3rd edition Chapter 1 (sections 1.1 & 1.2) Note: Assignment 1 will be posted on the WebCT site (Individual submission)

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Summaries and graphic displays of the data are used Graphic displays such as: Pie Chart ……. proportion of the whole Bar graph used for categorical data Stem-and-leaf ……. medium sized data sets (Stemplots) used for quantitative data Histograms and ……. large data sets Polygons used for quantitative data (Special Case: Time Plots – Longitudinal Study) Study of the Cross-Sectional Aspects of the Data
Types of variables Quantitative Variable: o Takes numerical values for which we can do arithmetic o Ex: age, credit card balance, number of employees, time until customer is served Categorical Variable: o Places a case into one of several groups or categories o Ex: gender, brand of credit card, own a home (yes/no)

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Important Terms Cases: The objects described by a set of data. o Ex: customers, cities, patients, cars Variable: A characteristic of a case. o Ex: profit, duration of a service call, number of customers, gender o Different cases can have different values for the variables. Distribution of a variable: the values the variable takes and how often it takes them.
To better understand a data set, ask: Who? o What cases do the data describe? o How many cases? What? o How many variables? o What is the exact definition of each variable? o What is the unit of measurement for each variable? Why? o What is the purpose of the data? o What questions are being asked? o Are the variables suitable?

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Displaying categorical data Purpose: o Summarize the data so the reader can grasp the distribution quickly Process: o List the categories o Give either the count or the percent of cases that fall into each category Methods: o Tables, Pie Charts, Bar Graphs
Survey Question: Marital status Marital status Females 15 and up Data summarized in table form Marital status Count (Millions) Married 116 Never married 44 Divorced 19 Widowed 16 Total 195

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data Because the variable is categorical, the data in the graph can be ordered any way we want (alphabetical, by increasing value, by year, by personal preference, etc.). Bar graphs
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## mgcr 271 - McGill University BCom Program Statistics...

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