5. INTRODUCTION
Statistics’ is used to refer to;
Numerical facts, such as the number of people
living in particular area.
The study of ways of collecting, analyzing
and interpreting the facts
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6. What is Statistics?
• The science of conducting
studies to collect, organize
, summarize, analyze and
draw conclusions from da
ta
• The systematic collection of n
umerical data and its interpret
ation.
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8. Chap 1-8
Population vs. Sample
Population Sample
All the items or individuals about
which you want to draw conclusion(s)
A portion of the population of
items or individuals
13. Key concepts used in statistics
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A variable
A variable is a measurable quantity which changes
over space or time eg Time, cost of goods sold,
number of suppliers, type of specification, volume
and value of stock, return on net assets
15. Types of Variables
Categorical (qualitative) variables have values
that can only be placed into categories, such as
“yes” and “no”; major; architectural style; etc.
Numerical (quantitative) variables have values
that represent quantities.
Discrete variables arise from a counting process
Continuous variables arise from a measuring
process
. Chap 1-15
16. Key concepts used in statistics
A constant. This is a characteristic that takes the
same value at every time eg no. of months in a
year
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18. STAGES INVOLVED IN STATISTICS
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Collection of Data
Presentation of data
Analysis of data
Interpretation of data
19. SCOPE OF STATISTICS
Human resource; Useful in the recruitment process
Economics; Forecasting, Demographics, Testing and validating
economic theories
Finance; Risk analysis, Useful in portfolio diversification and asset
allocation.
Marketing ; Useful in market research
Operations management; Design and Quality management
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20. • Comparisons
• Condensation.
• Formulation and testing hypotheses
• Forecasting and planning
• Policy Making
• Helps in deriving relationship between variables
• Measures Uncertainty
Application/Importance/ uses/ functions of statistics
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22. Branches/ Types of Statistics
Descriptive
Collecting,
summarizing, analyzing
& describing data
Inferential
Drawing conclusions
and/or making decisions
concerning a population
based only on sample
data
Statistics
31. DATA COLLECTION
Statistical investigation is a comprehensive process
Requires systematic collection of data about some group of
people or objects, describing and organizing the data,
analyzing the data
The validity and accuracy of final judgment is most crucial
This depends heavily on how well the data was collected in
the first place.
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32. By Nature:
Quantitative data; Data which can be expresse
d numerically or in terms of numbers eg no. of s
tudents
Qualitative data, can not be expressed numeric
ally
Types of data
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33. By timeframe:
Cross Section Data- Data values observed at a fixed
point in time
Time Series Data- Ordered data values observed ov
er time
Panel Data– Data observed over time from the same
units of observation
Types of data
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34. By Source: Primary or Secondary
Primary Data - data gathered for the first time
by the researcher
Secondary Data - Data taken by the researcher
from secondary sources, internal or external, Al
ready published records/compilation
Types of data
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35. Advantages of primary data
The data is original.
The information obtained is unbiased.
It provides accurate information and is more reliable.
It gives a provision to the researcher to capture the changes
occurring in the course of time.
It is up to date data, relevant and specific to the required
product
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36. Disadvantages of primary data
Time consuming to collect
It requires skilled researchers in order to be
collected.
It needs a big sample size in order to be accurate.
It’s more costly to collect
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37. Advantages of Secondary data
It’s economical as it saves expenses and efforts
It is time saving, since it is more quickly obtainable than
primary data.
It provides a basis for comparison for data collected by the
researcher.
It helps to make the collection of primary data more specific
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38. Disadvantages of Secondary data
Accuracy of secondary data is not known.
Data may be outdated.
It may not fit in the framework of the research factors
for example units used.
Users of such data may not have as thorough
understanding of the background as the original
researcher.
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39. Considerations to make before data collection
Statement of the purpose
should be clearly stated to avoid confusion
Only necessary information is collected
Scope of inquiry
based on space or time- geographical and time
Choice of statistical unit
DATA COLLECTION
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40. Data Sources
Data collection technique
Depends on time available, literacy of the re
spondents, language, availability of the reso
urces, the accuracy required
DATA COLLECTION
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Major Techniques for Collecting Data
1. Questionnaires
2. Interviews
3. Observation
4. Experimentation
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Using these data gathering methods
Each method has advantages and problems.
No single method can fully measure the variable
Examples:
Questionnaires & surveys are open to self-report biases,
such as respondents’ tendency to give socially desirable
answers rather than honest opinions.
Observations are susceptible to observer biases, such as
seeing what one wants to see rather than what is actually
there.
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Use more than one
Because of the biases inherent in any data-collection
method, it is best to use more than one method when
collecting diagnostic data.
The data from the different methods can be compared,
and if consistent, it is likely the variables are being validly
measured.
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Questionnaires:
Questionnaires are one of the most efficient
ways to collect data.
They contain fixed-response questions about
various features of an organization.
These on-line or paper-and pencil measures
can be administered to large numbers of
people simultaneously.
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Questionnaires:
They can be analyzed quickly.
They can be easily be fed back to
employees.
Questionnaires can be standard based on
common research or they can be customized
to meet the specific data gathering need.
46. GUIDELINES FOR DRAFTING A
QUESTIONNAIRE
The size of the questionnaire should be small
The questions should be clear, brief, unambiguous, non-
offending etc
The questions should be logically arranged
The questions should be short, simple and easy to
understand
Avoid questions of personal nature
The questionnaire should be made to look attractive
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47. Sample questionnaire
Demographic statistics
1. Gender of the household head
2. Marital status of the household head
3. Education level of the household head
Male Female
Never married Married Divorced ???
Never studied Primary secondary Diploma
48. Sample questionnaire
1. I have understood the types of data
2. Statistics is easily understandable
3. I will pass elements of statistics with flying grades
STRONGLY
DISAGREE
DISAGREE NOT SURE AGREE STRONGLY
AGREE
STRONGLY
DISAGREE
DISAGREE NOT SURE AGREE STRONGLY
AGREE
51. Questionnaire (limitations/ draw backs)
•It is very costly and time consuming
•It is suitable only for intensive studies and not for extensive
enquiries
•Personal prejudice and bias are greater under this method.
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Questionnaires (drawbacks)
Responses are limited to the questions asked in
the instrument.
They provide little opportunity to probe for
additional data or ask for points of clarification.
They tend to be impersonal.
Often elicit response biases – tend to answer in a
socially acceptable manner.
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Interviews
Interviews are probably the most widely used
technique for collecting data
They permit the interviewer to ask the respondent
direct questions.
Further probing and clarification is possible as the
interview proceeds.
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Interviews
Interviews may be highly structured, resembling
questionnaires, or highly unstructured, starting with
general questions that allow the respondent to lead the
way.
Interviews are usually conducted one-to-one but can be
carried out in a group.
Group interviews save time and allow people to build on
other’s responses.
Group interviews may, however, inhibit respondent’s
answers if trust is an issue.
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Interviews / Focus Groups
Another unstructured group meeting conducted by a
manager or a consultant.
A small group of 10-15 people is selected representing a
larger group of people
Group discussion is started by asking general questions
and group members are encouraged to discuss their
answers in some depth.
The richness and validity of this information will depend
on the extent that trust exists.
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Drawback to interviews
They can consume a great deal of time if interviewers take full
advantage of the opportunity to hear respondents out and change their
questions accordingly.
Personal biases can also distort the data.
The nature of the question and the interactions between the
interviewer and the respondent may discourage or encourage certain
kinds of responses.
It take considerable skill to gather valid data.
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Observations
Observing organizational behaviors in their functional
settings is one of the most direct ways to collect data.
Observation can range from complete participant
observation, where the OD practitioner becomes a
member of the group under study to a more detached
observation using a casually observing and noting
occurrences of specific kinds of behaviors.
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Advantages to Observation:
They are free of the biases inherent in the self-report data.
They put the practitioner directly in touch with the behaviors in question.
They involved real-time data, describing behavior occurring in the present
rather than the past.
They are adapting in that they can be modified depending on what is being
observed.
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Problems with Observation
Difficulties interpreting the meaning underlying the observations.
Observers must decide which people to observe; choose time periods,
territory and events
Failure to attend to these sampling issues can result in a biased sample of
data.
60. Data collection methods
• Direct interview
• Many researchers believe that the best way to survey people is by
means of personal interviews
• Involves an interviewer soliciting information from a respond
ent by asking prepared questions.
• Observation
• This is data collected through direct observation.
• Experimentation
• A more expensive but better way to produce data is through exper
imentation.
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