4. Statistics:
• Latin word, ‘Status’ which means, ‘‘knowledge about state.’’
• Plural of statistics is ‘statistic’
• Branch of science that deals with the scientific method is called statistics.
• i.e. Arm forces, Population, Graphical area etc.
• A single numerical quantity computed from sample is defined as statistic.
5. Scientific Method
• A method of research in which a problem is identified, relevant data is
gathered.
6. History of Statistics
• In past, kings and rulers used Statistics.
• Information about lands and population of state
• Gottfried Achenwall (1719-1772)
• Sir Ronald Aylmer Fisher (1890-1962)
• Modern statistics
• Francis Galton
Std. deviation
Correlation
Regression
7. Applications of Statistics
• Engineering
• Economics
• Business
• Environment
• Physics
• Chemistry
• Biology
• Medical and so on.
8. Importance in daily life
• Every day we are bombarded with different type of data
• If you can't distinguish good from faulty reasoning, then you do manipulation
• Statistics provides tools that you need in order to react the information
H.G. Wells says that,
“Statistical thinking will one day as necessary for citizenship as the ability to read and
write”
9. Characteristics of Statistics
• Statistics of aggregate facts
• Statistics of numerical expressed
• Statistics are affected by variety of causes
• Statistics are collected in systematic manners
• Statistics are placed in the relation to each other
11. Population
• Totality of objects under a particular place is called population.
• Population size denoted by ‘‘N’’
• Population mean is denoted by ‘‘µ’’
12. Examples:
• All students studying at UOG
• All registered voters in Pakistan
• All parts produced today
13. Sample
• Sub and representative part of population is called sample.
• Sample size is denoted by ‘n’
• Sample mean is denoted by ‘‘X̅’’
Examples:
• 100 voters at random for interview
• Only students of Management of Sciences Departments
19. Why we need descriptive statistics?
• Visualize what the data was showing
• Present data in a more meaningful way
• Simpler interpretation of data
20. Types of Descriptive Statistics
• Measure of frequency:* Count, percent, frequency...
• Measure of Central tendency:* mean, median, mode...
• Measure of Dispersion or Variation:*Range, Variance, Standard Deviation…
• Measure of Position:* Percentile Ranks, Quartiles Ranks…
21. Inferential Statistics
• Data collecting from a small group
• draw conclusion about a larger group
Examples:
• Accounting department of a large firm will select a sample of the invoices to
check for a accuracy for all the company
22. Why we need inferential statistics?
• To infer from the sample data
• To make judgment of probability that an observe difference between groups
27. Qualitative Variables:
• Assume only verbal response
• Also called Categorical variables
• It describes data that fits into categories
• Examples
Eye colors (blue, green, red, etc.)
Grades (A+, A, B+, B, B-, etc.)
Blood groups (O+, O-, A+, A-, etc.)
Gender (Male and Female)
28. Quantitative Variables:
• Assume only numerical response
• They represent a measureable quantity
• Examples
Height
Weight
Age
Temperature
29. Types of quantitative variables:
• Two types
Discrete variables
Continuous variables
30. Discrete variables:
• Assume only rounded digits
• Examples
Numbers of employments
Numbers of students
Numbers of siblings
33. What is level of measurements?
• Developed by Psychologist S.S Stevens
• Describes the nature of Information within the values assigned to variables
• Also called Scales Of Measure
34. Historical Background:
• He proposed his typology in 1946 titled as “On The Theory Of Scales Of
Measurements”
• He claimed that “That all measurement in science was conducted using four
different types of scales”
35. Scales:
• There are four scales
Level of Measurements
Nominal Scale Ordinal Scale Interval Scale Ratio Scale
36. 1. Nominal Scale
• Used to measure Qualitative Data
• Differentiate b/w items or subjects based only on there names or categories
• Numbers may be used to represent variable but Numbers don’t have
numerical values
42. 4. Ratio Scale
• Used for measurement of quantitative data
• Kind of interval scale
• Ratios are defined
• A ratio scale possesses a meaningful (unique and non-arbitrary) zero value
45. What is data ?
• Collection of raw facts and figures
• Process of collecting relevant information
46. Types of data collection
• There are two types :
• Primary data
• Secondary data
47. Primary data
• Information collected at first round
• Did not undergo any statistical treatment
Methods include in this type are:
1. Direct personal investigation
2. By observing
3. By questioner method
48. Significance of primary data
• Reliability
• Availability of wide range of techniques
• Control
Limitations
1. Cost
2. Time
3. Large data
49. Secondary method
• Already collected
• Undergone through statistical treatment
Ways to access :
• Official government data
i.e. NADRA
• Semi-official
i.e. banks
