# EC255 Chapter Notes -Squared Deviations From The Mean, Standard Deviation, Kurtosis

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EC255 Week 1

1.1 STATISTICS IN BUSINES

Virtually every area of business uses statistics in decision making,

Several examples are as follows:

-Marketing

-Management

-Finance

-Operations and Supply Chain Management

-Economics

-Accounting

-Management Information Systems

1.2 BASIC STATISTICAL CONCEPTS

Statistics – a science dealing with the collection, analysis, interpretation, and presentation of numerical

data

Population – a collection of persons, objects, or items of interest

Census – gathering data from the whole population for a given measurement o interest

Sample – a portion of the whole

-The study of statistics can be organized in a variety of was

-Statistics can be subdivided into two branches: descriptive statistics and inferential statistics

Descriptive Statistics – Using data gathered on a group to describe or reach conclusions about that same

group

-Descriptive statistics can be used for batting averages, save percentages, and first downs because they

describe an individual or team effort

Inferential Statistics – Gathering data from a sample and using the statistics generated to reach

conclusions about the population from which the sample was taken

-The data gathered from the sample are used to infer something about the larger group

-Inferential statistics are sometimes referred to as inductive statistics

-One application of inferential statistics is in pharmaceutical research. Some new drugs are expensive to

produce, and therefore tests must be limited to small samples of patients

-Market researchers use inferential stats to study the impact of advertising on various market segments

-The advantage to using inferential statistics is that they enable the researcher to effectively study a

wide range of phenomena without having to conduct a census

Parameter – a descriptive measure of the population

Statistic – a descriptive measure of a sample

-Differentiation between the terms parameter and statistic is important only in the use of inferential

statistics. A business researcher often wants to estimate the value of a parameter or conduct tests

about the parameter. However, the calculation of parameters is usually either impossible or infeasible

because of the amount of time and money required to take a censure. In such cases, the business

EC255 Week 1

researcher can take a random sample of the population, calculate a statistic on the sample, and infer by

estimation the value of the parameter.

1.3 DATA MEASUREMENT

Nominal Level

-Numbers representing nominal-level data can be used only to classify or categorize

-Ex. Employee ID numbers, sex, religion, ethnicity, geographic location place of birth, SIN, telephone

numbers

-Statistical techniques that are appropriate for analyzing nominal data are limited

Ordinal Level

-Can be used to rank or order data

-With ordinal data, the distances between consecutive numbers are not always equal

Interval Level

-The distances between consecutive numbers have meaning and the data are always numerical

-Ex. Temperature

-The existence of 0 actually means something with interval level data

Ratio Level

-Have an absolute zero and the ratio of two numbers is meaningful

-The zero value in the data represents the absence of the characteristic being studied

-The value of zero cannot be arbitrarily assigned because it represents a fixed point

-Ex. Height, mass, time, volume, production cycle time, work measurement time, passenger distance,

etc.

-Statistical techniques can be separated into two categories: parametric statistics and nonparametric

statistics

Parametric statistics – require that data be interval or ratio

Nonparametric statistics – nominal or ordinal data

2.1 FREQUENCY DISTRIBUTIONS

Frequency distribution – a summary of data presented in the form of class intervals and frequencies

-Frequency distributions are relatively easy to construct – they vary in shape and design

Range – the difference between the largest and smallest number

-Select between 5 and 15 classes when making a frequency distribution chart

-The frequency distribution must start at a value equal to or lower than the lowest number of the

ungrouped data and end at a value equal to or lower than the lowest number and vice versa

-Class endpoints are selected so that no value of the data can fit into more than one class

## Document Summary

Virtually every area of business uses statistics in decision making, Statistics a science dealing with the collection, analysis, interpretation, and presentation of numerical data. Population a collection of persons, objects, or items of interest. Census gathering data from the whole population for a given measurement o interest. The study of statistics can be organized in a variety of was. Statistics can be subdivided into two branches: descriptive statistics and inferential statistics. Descriptive statistics using data gathered on a group to describe or reach conclusions about that same group. Descriptive statistics can be used for batting averages, save percentages, and first downs because they describe an individual or team effort. Inferential statistics gathering data from a sample and using the statistics generated to reach conclusions about the population from which the sample was taken. The data gathered from the sample are used to infer something about the larger group. Inferential statistics are sometimes referred to as inductive statistics.