Econ-ADMN #1 - a summary for the first chapter - Basic Statistics for Business and Economics PDF

Preview

Summary

a summary for the first chapter ...

Description

Econ-Admn 2200 Chapter #1

there are at least three reasons for studying statistics: 1 data are collected everywhere and require statistical knowledge to make the information useful. 2 statistical techniques are used to make professional and personal decisions. 3 no matter what your career, you will need a knowledge of statistics to understand the world and to be conversant in your career. An understanding of statistics and statistical methods will help you make more effective personal and professional decisions.



1. 2. 3. 4. 5.

you will find yourself faced with decisions where an understanding of data analysis is helpful. To make an informed decision, you will need to be able to:

Determine whether the existing information is adequate or additional information is required. Gather additional information, if it is needed, in such a way that it does not provide misleading results. Summarize the information in a useful and informative manner. Analyze the available information. Draw conclusions and make inferences while assessing the risk of an incorrect conclusion.

what are statistics?

- statistic is a number used to communicate a piece of information. what is statistics? - Statistics is the set of knowledge and skills used to organize, summarize, and analyze data. - The results of statistical analysis will start interesting conversations in the search for knowledge that will help us make decisions.

TYPES OF STATISTICS a. descriptive statistics b. inferential statistics A. descriptive statistics -

Methods of organizing, summarizing, and presenting data in an informative way.

-

It is used to summarize and present a past information, but is not used to estimate a future data

B. inferential statistics -

the method used to estimate a property of a population, based on a sample

TYPES OF VARIABLES A. qualitative variable - characteristic being studied is non-numeric, it is called a qualitative variable or an attribute. - Examples of qualitative variables are gender, beverage preference, type of vehicle owned, country of birth and eye colour. B. quantitative variable. - When the variable can be reported numerically - Examples of quantitative variables are the balance in your chequing account



Quantitative variables are either discrete or continuous.

1. Discrete variables - can assume only certain values, and there are “gaps” between the values. - Examples of discrete variables are the number of bedrooms in a house

2. continuous variable - can assume any value within a specific range. - Examples of continuous variables are the air pressure in a tire, and the weight of a shipment of tomatoes.

LEVELS OF MEASUREMENT There are four levels of measurement: 1. Nominal 2. Ordinal 3. Interval 4. ratio.

1. Nominal: - The variable of interest is represented as names or labels. - There is no order. They can only be classified and counted. 2. Ordinal:

- Data recorded is based on a relative ranking or rating of items based on a defined attribute or qualitative variable.

- Variables based on this level of measurement are only ranked or counted. 3. Interval: - Data classifications are ordered according to the amount of the characteristic they possess.

- Equal differences in the characteristic are represented by equal differences in the measurements.

4. Ratio: - Data classifications are ordered according to the amount of the characteristics they possess.

- Equal differences in the characteristic are represented by equal differences in the numbers assigned to the classifications.

- The zero point is the absence of the characteristic and the ratio between two numbers is meaningful....