Study Guides (380,000)

CA (150,000)

Ryerson (10,000)

QMS (100)

QMS 102 (90)

Nursel Ruzgar (10)

Study Guide

School

Ryerson UniversityDepartment

Quantitative MethodsCourse Code

QMS 102Professor

Nursel RuzgarStudy Guide

FinalThis

**preview**shows pages 1-3. to view the full**29 pages of the document.**Ryerson

QMS 102

FINAL EXAM

STUDY GUIDE

Only pages 1-3 are available for preview. Some parts have been intentionally blurred.

Only pages 1-3 are available for preview. Some parts have been intentionally blurred.

QMS102 111- Business Statistics I: Lecture 01

What is Statistic?

• Statistics is a way to get information from data

Data: Facts, especially numerical facts, collected together for references or info.

Information: knowledge communicated concerning some particular fact.

Example

A student is somewhat apprehensive about the statistics course because the student

believes the myth that the course is difficult. The professor provides last term’s

marks to the student. What information can the student obtain from this list?

List of last term’s marks.

Population, Parameter, Sample, Statistics, Variable

• Population: group of all items of interest to the statistics practitioner

➢ All the members of Ryerson University

• Parameter: A descriptive measure of a population

➢ Mean number of soft drinks sold at Ryerson every week.

• Sample: A set of items drawn from the population.

➢ 500 students surveyed.

• Statistic: A descriptive measure of a sample.

➢ Average number of soft drinks these students buy per week.

• Variable: a characteristic of population or sample that is of interest for us.

➢ Number of soft drinks a student buys every week.

Key Statistical Concepts

Population:

• A population is the entire set of all items under study

• Frequently very large. E.g. all 5 million Florida voters

Statistics

Information

95

89

70

65

78

57

New info about stats

class.

E.g. Median of all marks,

Typical mark, i.e.

average.

find more resources at oneclass.com

find more resources at oneclass.com

###### You're Reading a Preview

Unlock to view full version

Only pages 1-3 are available for preview. Some parts have been intentionally blurred.

Sample:

• A sample is a set of data drawn from the population.

• Potentially very large, but less than the population.

E.g. a sample of 700 voters exit polls on election day.

Parameter:

• A descriptive measure of a population

• In most applications of inferential statistics, the parameter represents the

info we need.

E.g. the proportion of the 5 million Florida voters who voted for Obama.

Statistic:

• A descriptive measure of a sample.

E.g. The proportion of the sample of 700 Floridians who voted for Obama.

Types Of Statistics

• Descriptive Statistics: involves the arrangement, summary, and

presentation of data, to enable meaningful interpretation, and to support

decision-making.

➢ Set of methods of organizing and presenting data. Methods include

Graphical and Numerical techniques.

➢ Describe the data that’s being analyzed, but doesn’t allow us to draw

conclusions about the data.

• Inferential statistics: a set of methods used to draw conclusions about

characteristics of a population based on sample data.

➢ set of methods, but it is used to draw conclusions or inferences about

Subset

Inference

Parameter

Pop. Has Parameters

Statistic

Samples have Statistics

find more resources at oneclass.com

find more resources at oneclass.com

###### You're Reading a Preview

Unlock to view full version