1. Unit 1 Introduction to Business
Business Statistics
Unit 1 Introduction to Business
Statistics

2. Business statistics topic 1
Learning Objectives
By the end of this topic you will be able to:
Define Sstatistics
Recognise the need for Statistics in business
Differentiate between descriptive & inferential
statistics
Identify different types of data and their sources
Gain an awareness of different methods of collecting data
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3. Business statistics topic 1
What is Statistics?
Statistics is a method of extracting useful information from a set of numerical data in order to make a more effective and informed decision.
A method or technique
Deal with data
Purpose is to make decision: more effective and informed
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4. The Need for Statistics in Business
Accounting, finance, management and marketing all use statistics:
Accounting
Uses statistics to select samples for auditing and to understand the cost drivers in cost accounting
Finance
Uses statistics to choose between alternative portfolio investments and to track the trends of financial measures over time.
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5. The Need for Statistics in Business
Management
Uses statistics to improve the quality of the products manufactured.
Marketing
Uses statistics to estimate the proportion of customers who prefer one product over another.
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6. Business statistics topic 1
Types of Statistics
There are two different types of statistics:
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7. Descriptive Statistics
These are statistical methods of organizing, summarizing and presenting numerical data in convenient forms such as graphs, charts and tables.
How to effectively to collect, organise and describe data.
Forms: graphs, charts and tables
Purpose: describe the various features of the data and make the effective decision.
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8. Examples Three examples of the tools used for this method are:
Surveys for collecting data: favorite food
Charts & tables for presenting data: month sales
Calculate Averages for characterizing data: average mark of a class
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9. Inferential statistics
Inferential statistics is defined as statistical methods used for drawing conclusions about a population based on samples.
making inferences about populations from samples
Methods or techniques
Infer from samples
The purpose is to draw conclusion
Inferential statistics focuses on trying to infer or reach conclusions about the data that reach beyond the data itself.
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10. Sample statistic (`X, Ps ) Business statistics topic 1
Inference Process
Population
Sample
Parameters
Estimates & tests
Sample statistic (`X, Ps ) ?
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11. Important definitions:
A population is a collection of all possible individuals, objects, or measurements of interest.
Expressed by µ
A sample is a portion, or part, of the population of interest.
Expressed by s
A summary measure of a population is a parameter:
A summary measure of a sample is a statistic.
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12. Business statistics topic 1
Examples
If the mean height of people in the sample is 1.7m, the mean height of people in the population is close to 1.7m.
population – a set of objects, of interest. (may be infinite or otherwise unobservable) Population of people, of haploid cells, of 100-item samples, of measurements of a person that you are interested in
sample – an observable subset of a population. 50 people, 60 haploids, person samples, 80 repeated measurements from the whole objects of interest
parameter – a property of a population. Greek letter (µ) or capital letter (P, N)
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13. Business statistics topic 1
Example of statistic
statistic – an observable property of a sample.
A numerical value, such as standard deviation or mean, that characterizes the sample or population from which it was derived. Any number calculated from sample data, describes a sample characteristic. A sample of class : average marks of their English test
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14. Business statistics topic 1
Why Use a Sample
It many not be possible to collect the entire data
Quicker to collect sample data
Cheaper
Easier to administer
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15. Business statistics topic 1
Simple Random Sample
A simple random sample of size n consists of n
individuals from the population chosen in such a way
that every set of n individuals has an equal chance to be the sample actually selected.
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16. Application of Statistical Inference
Three examples of the tools used for this
method are:
Estimation
Forecasting
Testing of hypotheses and decision making
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17. Business statistics topic 1
Data Sources
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Primary Data
Primary data is obtained first hand.
Ways of collecting data by the use of surveys, observation and/or experimentation.
Advantages:
Results are up to date
Can meet immediate needs
Disadvantages:
Collection of data can be time-consuming
It is an eexpensive process
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19. Business statistics topic 1
Secondary Data
Secondary data already exists or has been previously collected such as company accounts, or sales figures.
Issues with secondary data:
The data may have been collected for other purposes and may focus on irrelevant characteristics.
You might not know how the data was collected, over what time period and the source of the information.
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20. How to Search & Use Secondary Sources?
Documents - Bibliographic Skills, Use of Keywords, Boolean Operators
Published Statistics
Guide to Official Statistics
Digests & Abstracts
Primary Publication
Online resourse
Search on the internet
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21. Economic Statistics from White House
Unemployment Rate
Unemployment
Civilian Labor Force
Economic Statistics Briefing Room
Economic Statistics from White House
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22. Business statistics topic 1
Types Of Data
Data
Numerical
Categorical
Example:
Type of car owned
Colour of pens
Religion
Discrete
Continuous
Example:
Number of children.
Example:
Time taken for an exam.
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23. Business statistics topic 1
Numerical Data
Numerical data are numerical responses. Examples include the test score, balance of your bank account, and the number of students in our class.
Numerical data can be divided into two types : discrete (discontinuous) and continuous variables.
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Discrete Data
Discrete data: Numerical responses that arise from a counting process.
e.g How many children are in the family?
how many states are there in USA?
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Continuous Data
Continuous data: Numerical responses that arise from a measuring process.
e.g. How much do you weigh?
How fast does the train travel?
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Categorical Data
Categorical variables represent types of data which may be divided into groups. Examples of categorical variables are race, sex, age group, and educational level
Qualitative data can also include ccategorical responses, such as yes or no answers.
An example of a question for a categorical response:
“Would you be likely to study in Austria next year?”
Yes No
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27. Business statistics topic 1
Ethical Issues
Ethical considerations arise with respect to potential
errors that may occur when designing surveys that use samples.
the main errors that arise when we use samples rather than taking a census are as follows:
Coverage error
Nonresponse error
Sampling error
Measurement error
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28. Business statistics topic 1
Example of A Survey
An outlet of WalMart in Foshan conducts a survey to evaluate customer satisfaction.
Describe the population
Explain how a sample could be selected
Develop four questions for the survey
What type of error is most likely to occur?
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29. Business statistics topic 1
Answers (1)
Population:
All customers visiting the restaurant
Sample frame:
Pick at random from the entire list of registered customers
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30. Business statistics topic 1
Answers (2)
Possible questions for the survey:
Quality of food
Excellent Good Satisfactory Unsatisfactory
Cleanliness
Room Service
Reception
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31. Business statistics topic 1
Answers (3)
Coverage error is most likely to occur.
Dissatisfied customers are more likely to respond to the surveys than the satisfied customers.
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32. Business statistics topic 1
Summary
In this topic you have:
Reviewed the role of sstatistics in bbusiness
Distinguished between descriptive & inferential statistics
Identified different types of data
Identified methods of data collection.
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33. Business statistics topic 1
Assignment
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