# OMIS 2010 Chapter Notes -Descriptive Statistics, Level Of Measurement, Frequency Distribution

by OC214870

School

York UniversityDepartment

Operations Management and Information SystemCourse Code

OMIS 2010Professor

Alan MarshallThis

**preview**shows pages 1-2. to view the full**7 pages of the document.**Chapter 1: What is Statistics?

-Way to get info from data

-Descriptive statistics: deals with methods of organizing, summarizing and presenting data in convenient

and informative way (ie. graphing techniques)

-Use numerical techniques to summarize data; average

-Average is a measure of central location

-Range is measure of variability

-Inferential Statistics: methods used to draw conclusions/inferences about characteristics of population

based on sample data

-Exit polls: random sample of votes exit the polling booth and asked for whom they voted; sample proportion

of voters supported the candidates is computed

Key Statistical Concepts

-Population: group of all items of interest; very large; does not necessarily refer to group of people

-Parameter: descriptive measure of a population; mean # of soft drinks consumer by all students at the

university or proportion of 5 million who voted for Bush

-Sample: set of data drawn from the studied population

-Statistic: descriptive measure of a sample; used to make inferences about parameters

-Statistical Inference: process of making an estimate/prediction/decision about a population based on

sample data; measure of reliability

-Confidence level: proportion of times that an estimating procedure will be correct

-Significance level: measures how frequently conclusion will be wrong

-Hw pg 39, 47, 57-62, 69-72, 195, 197, 202, 204, 91-94, 100-104, 110-112, 118-125

Chapter 2: Graphical Descriptive Techniques 1

Types of Data and Information

-Variable: some characteristic of a population or sample (ie. prices of stocks varying daily)

-Values: possible observations of the variable; integers between 0 - 100 of statistics exam(100 marks)

-Data: observed values of a variable; midterm test marks of 10 students; datum refers to mark of one student

Interval data: real numbers; heights, weights, incomes, distances (quantitative or numerical)

Nominal data: values of nominal data are categories; responses to questions about marital

status (qualitative/categorical); only calculations based on frequencies or percentages of

occurrence are valid

Only pages 1-2 are available for preview. Some parts have been intentionally blurred.

Ordinal data: order of values has meaning; order of values of latter indicate higher rating;

calculations based on ordering process are valid

Interval/differences between values of interval data are consistent and meaningful

Calculation for Types of Data

Interval Data: all calculations permitted; set of interval data described by using the average

Nominal Data: calculations based on codes used to store this type of data are meaningless; compute

percentages of occurrences of each category

Ordinal Data: only permissible calculations should involve ranking process

Describing Set of Nominal Data

-Frequency distribution: presenting the categories and their counts; relative frequency distribution lsits

categories and proportions with which each occurs

-Bar graph shows frequencies, pie chart shows relative frequencies

-Bars in bar graph arrange in ascending/descending ordinal values; pie chart wedges arrange clockwise in

ascending/descending order for ordinal data

Describing relationship between 2 nominal variables

-Univariate: techniques applied to single sets of data

-Bivariate: methods that depict relationship between variables

-Cross-classification table: describes relationship between 2 nominal variables; lists frequency of each

combination of values of the 2 variables

-If two variables are unrelated, patterns exhibited in bar charts should approx.. be the same

Comparing 2 or more nominal data sets

-Consider the three occupations (newspaper example) as defining 3 populations; if differences exist

between columns of frequency distributions (or between bar charts), then differences exist among the

three populations

Chapter 3: Graphical Descriptive Techniques 2

Graphing techniques to describe set of interval data

-Create frequency distribution for interval data by counting number of observations that fall into each of a

series of intervals; called classes, covering range of observations

-Intervals should be equal; graphing and interpretation made easier

-Histogram: created by drawing rectangles whose bases are intervals and heights are frequencies

Determining number of class intervals

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