BUSINESS STATISTICS

Bijay Lal Pradhan, Ph.D.

MBA, Pokhara University

WHY BUSINESS STATISTICS

Most successful Manager and Decision makers understand the information and know how to use it effectively

COURSE CONTENT Introduction and Data Collection Summarization of Data

Grouping and Displaying Data Numerical Descriptive Measures

Basic Probability: Concepts and Applications. Probability Distributions Sampling Distribution and Estimation Hypothesis Testing Chi-Square Test and Analysis of Variance Correlation and Regression Analysis

BOOKBasic Books Levine, D. M., Krehbiel, T. C., Berenson, M. L., and

Viswanathan, P. K., Business Statistics (Fourth Edition), New Delhi: Pearson Education.

Levin, R. I. and Rubin, D. S., Statistics for Management (Seventh Edition), New Delhi: Prentice Hall.

References Siegel, A. F., Practical Business Statistics (Fourth

Edition), New York: Andrew F, Irwin. Anderson, D. R., Sweeney, D.J. and Williams, T. A.,

Statistics for Business and Economics (Eighth Edition), New Delhi: Thomson.

INTRODUCTION AND DATA COLLECTIONDefinition of statistics, Application in Business and Economics, Descriptive and Inferential Statistics, Types of Data (Categorical and Numerical), Classification of data (Crosssectional, Time series, Pooled), Sources of Data (Primary and Secondary), Census and Sampling, Parameter and Statistics, Data Collection Technique, Questionnaire Construction

DEFINITION OF STATISTICS In plural sense, the word statistics refer to

numerical facts and figures collected in a systematic manner with a definite purpose in any field of study. In this sense, statistics are also aggregates of facts which are expressed in numerical form. For example, Statistics on industrial production, statistics or population growth of a country in different years etc.

In singular sense, it refers to the science comprising methods which are used in collection, analysis, interpretation and presentation of numerical data. These methods are used to draw conclusion about the population parameter.

APPLICATION IN BUSINESS AND ECONOMICS

Accounting: Sample Audit, different tools Finance: price/earning ratio, dividend yield

(comparison with average or to other companies) Marketing: AC Nielsen (Worlds largest Chain

Market Researcher ) Production: Statistical Quality Control, Forecast,

Aggregate production planning. Economics: Forecast for future economy. Price

Index, Unemployment rate, capacity utilization.

BRANCH OF STATISTICS(1) Descriptive Statistics: In descriptive statistics, it deals with collection of data, its presentation in various forms, such as tables, graphs and diagrams and findings averages and other measures which would describe the data.For Example: Industrial statistics, population statistics, trade statistics etc Such as businessman make to use descriptive statistics in presenting their annual reports, final accounts, bank statements.

BRANCH OF STATISTICS(2) Inferential Statistics: In inferential statistics, it deals with techniques used for analysis of data, making the estimates and drawing conclusions from limited information taken on sample basis and testing the reliability of the estimates. For Example: Suppose we want to have an idea about the percentage of illiterates in our country. We take a sample from the population and find the proportion of illiterates in the sample. This sample proportion with the help of probability enables us to make some inferences about the population proportion. This study belongs to inferential statistics

Descriptive & Inferential Statistics

Statistics

Descriptive Inferential

Tabular Graphical

Estimation Hypothesis Testing

Point Interval Parametric Non-Parametric

The methods of inferential statistics are applicable when results areobtained from a random.Uncertainty always remains while generalizing results from a sampleto a population. The degree of uncertainty is measured in terms ofprobability in inferential statistics.

DATA AND ITS TYPE A characteristic or measurement that may

different from one entity to another or place to place or time to time is called Data, which is able to distinguish among them. For eg. The measurement for height, weight, income, expenditure, demand etc.

Data are collected for an investigation or research depending on the nature of the problem, they may relate to individuals, families, houses, village, business etc. The collected data are known as observations.

Observations may be measured out of the 4 type of physical measurement.

DATA AND ITS TYPE The distinguishing of the observations from one

outcome to other is called categorization. In other word categorization is a partition or a sub partition of total possible outcomes into different distinct groups or elements.

The data refereeing to a single time point or a single space point ( or any single factor of the variable/attribute is a cross section data.)

DATA AND ITS TYPES The data, which are collected according to time

variation (year, month, week, day, hours, minutes etc) (time series)

The data, which are collected according to place, area, region etc (geographical / spatial)

The data, which are placed to compare two or more variables, which is used to find out relationship between two or more variables and used for estimating one variable using known value of another variable. (Ordered data)

SOURCES OF PRIMARY AND SECONDARYDATAPrimary

Data collected by investigator from personal experimental studies for a specific research

First hand data Collected when secondary data are

unavailable and inappropriateSecondary

The data (published or unpublished form which has collected by others for their purpose) can be utilized for study of another investigator, such data is said to be secondary data.

SOURCES OF PRIMARY AND SECONDARYDATA Source of Primary data

Questionnaire survey (post, internet) Interview (personal/telephone) Focus group discussion Community forums and public hearing Observation Case studies Diaries Key informants interview

SOURCES OF PRIMARY AND SECONDARYDATA Source of Secondary data

Usual public sourcesNepal census of Household and Population,

agriculture, business, vital statistics etcGovernmental organization-national and district level

use for development of society (office of ministry, municipality, district development office etc)

Opinion and poll taken by othersHealth and microbial survey done by others INGOs, NGOs, UN publication

Unusual sources: Easily accessibleThe yellow pages, Newspapers, Bulletin Board, Films,

Post cards, old prints, Topographical maps etc

SOURCES OF PRIMARY AND SECONDARYDATAProblems in collecting primary data

Timeframe, budgetary Transportation Non response error Biasness of enumerator Lack of expertise in construction of questionnaire

and collection of dataProblems in collecting secondary data

Definition of terms and units If two set data comparison may make confusion Data may not be exact form of requirement Reliability and suitability

DATA COLLECTION TECHNIQUES

Method of data collection

Primary sources

Observation

Participants

Non Participants

interviewing

Structure Non Structure

Questionnaire

Mailed Question

naire

Collective

Questionnaire

Secondary Sources

Documents

Govt. PublicationEarlier Research

CensusPersonal RecordsClient HistoriesService records

OBSERVATION Participant observations: researcher participates in

the activities (as a member) with or without their knowledge that they are being observed. (involve as a prisoner to study the behavior & life of prisoners.

Non-participant observation: do not get involve in activities but remains a passive observer. (function carried out by nurse observed)

STRUCTURE INTERVIEW Pre-determined set of questions /Interview

schedule Face to face Telephone Other electronic media

UNSTRUCTURED INTERVIEW In-depth interview Focus group interview Narratives/ oral histories

QUESTIONNAIRE DESIGN Main instrument in survey Foundation of questionnaire is question It must translate research objective in to specific

question Answer to such question provide data for

hypothesis testing It must motivate the respondent so that

necessary information is obtained

THE MAJOR CONSIDERATION Content Structure (type) Format Sequence

CONTENT Factual

Background Environment Habits likes

Opinion Attitude Behaviour Idea inclination

TYPES OF QUESTIONS Closed end questions Open end questions Contingency questions

FORMAT OF QUESTION Rating question

Strongly agree, Agree, Disagree, strongly disagree, No opinion

Matrix question Large set of rating questions, has same response

categories Semantic differential

Bio polar rating Good -- -- -- -- -- -- -- Bad 3 2 1 0 1 2 3

Ranking question Placing objects according to relative order

ORDER OF QUESTION Random order Logical progression

The Funnel Sequence Successive questions have narrower scope Is used when the topic itself motivate the respondent to give

answer. The Inverted Funnel Sequence

Narrower questions are followed by broader ones It is used when the topic of survey does not strongly

motivate the respondent to communicate

PITFALL IN QUESTIONNAIRE CONSTRUCTION Wording of question (simple and everyday language) Response set (similar pattern questions) Leading questions

Unemployment is increasing , is not it? Threatening questions (embarrassing) Presumption questions

How many cigarettes do you smoke in a day? Double barreled questions

How often and how much time do you spend in your visit? Does you organization have special recruitment policy for

minorities and women?

SOME MORE INFORMATION Cover letter

Should motivate to share the required information, include objectives and relevance of the study

Instructions Clear understanding of the questions and way of

giving answer

QUESTIONNAIRE Through post Through Enumerator Online Survey

You can use googledocs (free of cost) or monkeysurveydifferent online survey tools

THE SAMPLING PROCESS

POPULATION

SAMPLE

INFERENCE

REGARDING THE SAMPLE

POPULATION (N)

SAMPLE (n)

IS THE SAMPLE

REPRESENTATIVE?

REGARDING THE INFERENCE

POPULATION (N)

SAMPLE (n)

INFERENCE

IS THE

INFERENCE

GENERALIZABLE?

Sampling and its significance in research

Sampling consists of obtaining information from only a part of a large group or population; and it indicates about the whole population. The objective of sampling is thus to secure a sample which will represent the population and reproduce the important characteristics of the population under the study as closely as possible.

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The value calculated from a defined population, such mean (), standard deviation (), standard error of mean (s.e.) is called a parameter. It is a constant value because it covers all the members of the population. A value calculated from a sample is called statistic such as mean, Standard deviation and proportion.

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CENSUS VS SAMPLING ?? The data is the basic units in statistical analysis and

inference; is either collected by experimentation or by sampling methods. Method of collection of statistical data by complete enumeration of the population is census. If the data collected by a certain group or part of population is called sampling enquiry. The principal advantages of sampling as compared to complete enumeration of the population are:

Reduced cost Save time and speed up Greater scope and improved accuracy

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SOME TERMINOLOGY USED IN SAMPLING

a. Universe/Population: It is the set of object under study. In a census survey, all the universe or population is studied while in a sample survey an appropriate number of units called samples is selected and studied; the generalization is made for the universe or population from which the samples are drawn.

b. Finite population:The number of items or the units under the study is known.

c. Infinite population: The number of units of the items is unknown.

d.Element:Each and every unit of population or universe is called element. An element constitutes one case for analysis.

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SOME TERMINOLOGY USED IN SAMPLINGe. Sampling unit:

The smallest unit of population to be sampled is called sampling unit and on which observations can be made.

f. Sample and sample size:An element or sampling unit from which information is collected is

called a sample. A sample should be optimum, effective, representative, reliable and flexible. The term sample size refers to the number of items to be selected from the universe to constitute a sample. This is the number of respondents or units in the population included in a sample for studying the population.

g. Sampling Frame or source listA list of all the units of population from which a sample is selected is called sampling frame.

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SOME TERMINOLOGY USED IN SAMPLINGh.Parameter

A coefficient or value for the population that corresponds to particular statistic from a sample is called parameter. A parameter is characteristic of population. For instance, mean, standard deviation, etc.

i. StatisticIt is characteristics of a sample and is hence computed from the actual data.

j. RespondentA sampling unit from which information is collected is called respondent.

k.Non- respondentThose respondents who were included in the sample but failed to respond because they refused, could not reach, or some other responses.

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40

Define Population

Specify the Sampling frame

Specify the sampling unit

Selection of sampling method

Determine the sample size

Specify the sampling plan

Select the sample

The

sam

plin

g m

etho

d

TYPES OF SAMPLING Random sampling1. Simple random sampling

a. Lottery methodb. Use of random

number2. Stratified sampling 3. Cluster sampling 4. Systematic sampling 5. Multistage sampling 41

Non Random sampling1. Judgmental sampling2. Convenient sampling 3. Quota sampling 4. Snow ball sampling 5. Purposive sampling

SIMPLE RANDOM SAMPLING

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Lottery MethodUse of Random Numbers

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within class homogeneous; between class heterogeneous

If the population is heterogeneous then srs may not give representative data

Stratified Random samplingEach class is said to be strata

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within class heterogeneous; between class homogeneous

If the population is heterogeneous then srs may not give representative

data

Cluster samplingEach class is said to be cluster

45

Systematic Sampling

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3

2

Sampling of households

1st 2nd 3rd 4th 5th

5 developmental Region of Nepal

A study of attitude of Nepalese people towards the Family Planning

4th1st

Development Region

Different Anchal

Multistage Sampling

Similarly Some districts can be taken as sample from the

selected anchal Likewise VDC, Municipality ward number and

house no can be taken as sample In this way there is Nepal Development region zone District VDC Municipality Ward no

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Non random sampling

Judgmental sampling: choice of sample items depends exclusively on the judgment of the investigator

Convenience sampling: A sample obtained from readily available lists

Quota sampling: In quotas are setup according to some specified characteristics and sample will be taken according to specified quota. Sampling will be depend upon the field representative

Snow ball methodAssumption of this method is that if small ball is let roll from the top of snow-peak, it gathers substantial amount of snow and looks like a big ball when it arrives at the bottom of snow hill.

SAMPLING ERRORSIt is the error of representativenessIt is the difference between total population value and the sampling valueThe degree to which sample characteristics approximate the characteristics of total population.Sapling error = Statistics Parameter

1

Parameter20 years

Statistic19 years

Statistic21 yearsStatistic24 years

Business StatisticsWhy Business StatisticsCourse ContentBookIntroduction and Data CollectionDefinition of StatisticsApplication in Business and EconomicsBranch of StatisticsBranch of StatisticsSlide Number 10Data And Its TypeData and its typeData and its typesSources of Primary and Secondary DataSources of Primary and Secondary DataSources of Primary and Secondary DataSources of Primary and Secondary DataData Collection TechniquesObservationStructure InterviewUnstructured interviewQuestionnaire designThe major considerationContentTypes of questionsFormat of questionOrder of questionPitfall in questionnaire constructionSome more informationQuestionnaireThe sampling processRegarding the sampleRegarding the inferenceSampling and its significance in researchSlide Number 35Census Vs sampling ??Some terminology used in samplingSome terminology used in samplingSome terminology used in samplingSlide Number 40Types of SamplingSIMPLE RANDOM SAMPLINGSlide Number 43Slide Number 44Slide Number 45Slide Number 46Slide Number 47Slide Number 48Slide Number 49Slide Number 50Sampling errors