DETERMINACY ANALYSIS The basic concepts, Statistical criteria, Applications in psychology
01 - Basic Statistical Concepts
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Transcript of 01 - Basic Statistical Concepts
Business MathematicsTotal Marks: 100 (60 Theory + 40 Internal)
Internal Marks BreakupAttendance & Class
Participation10
Test 20
Assignment 10
Statistics
Statistics
• Statistics is the science of dealing with numbers.
• It is used for Collection, Summarization, Presentation and Analysis of DATA
Application of Statistics
• Marketing : Market research, choosing appropriate marketing strategy, etc
• Finance: Forecasting, ascertaining risks, etc
• Operations: Inventory management, manufacturing and distribution of manufactured item, etc
• Human Resources: Staff evaluation, ratings, compensation structure, etc
Limitations of Statistics
• Only quantifiable data is captured• Sampling is used so result may not be
accurate• Statistics reveal the average behaviour• Statistics in not 100% accurate
Subdivisions within Statistics
• Descriptive Statistics : Summarising the given data, bringing out their important features
• Inferential Statistics : Use of quantitative techniques that enable us to make approximate generalisations
Population and Sample
• A population is a collection of all elements under statistical investigation about which we are trying to draw some conclusion
• Small representative portion of population is called as Sample
Types of Data
Data can be classified in various ways as follows
1.Primary and Secondary2.Qualitative and Quantitative3.Discrete and Continuous
Primary and Secondary
• Primary data is collected for some specific purpose or study
• Secondary data is the data derived through some media like reports, newspapers, hand books, magazines, etc.
Qualitative and Quantitative
• Qualitative data is expressed by a non numerical property– Ex: satisfaction of a customer , opinion about a
product
• Quantitative data is numerically expressed– Ex: weight, height, income, etc
Discrete and Continuous
• Variable is said to be discrete if it assumes only some specific values in a given range.– Ex: number of customers visiting an outlet
• Variable is said to be continuous when some sort of measurement is involved– Ex: height, weight,
Presentation of Data
The first step in statistical analysis is to presentdata in an easy way to be understood.
The two basic ways for data presentation are• Tabular form– List, Frequency distribution.
• Graphical form– Bar chart, pie chart, histogram, etc
List Tables
• A table consisting of two columns, the first giving an identification of the observational unit and the second giving the value of variable for that unit.
Example : number of patients in each hospital department are
Department Number of patients
Surgery 50
ENT 15
Ophthalmology 10
Frequency Distribution Tables
• Ex: Assume we have a group of 20 individuals whose blood groups were as follows : A, AB, AB, O, B, A, A, B, B, AB, O, AB, AB, A, B, B, B, A, O, A.
We want to present these data by table.
Type of data??
Frequency Distribution Tables
Blood Group Frequency
A 6
B 6
AB 5
O 3
Total 20
Frequency Distribution Table
Ex: The Following data are Blood Pressure measurements (mmHg) of 30 patients with hypertension. Present these data in frequency table
150, 155, 160, 154, 162, 170, 165, 155, 190, 186, 180, 178, 195, 200, 180,156, 173, 188, 173, 189, 190, 177, 186, 177, 174, 155, 164, 163, 172, 160
Type of data??
Frequency Distribution Table
Blood Pressure Frequency
150 – 160 6
160 – 170 6
170 – 180 8
180- 190 6
190 – 200 3
200 – 210 1
Total 30
Graphical Representation
• Simple • Easy to understand• Save a lot of words• Self explanatory
Bar Charts
• It is used for presenting discrete data• It represent the measured value by separated
rectangles of constant width and its lengths proportional to the frequency
• Type:• Simple • Multiple • Sub Divided
Simple Bar Charts
• Ex: The following data gives the distribution of 200 MBA students at a management institute according to their educational qualifications
Qualification Number of Students
B.E. 55
B.Com 70
BMS/BMM 40
Others 35
0
20
40
60
80
Subdivided Bar Chart
• A subdivided bar chart is a chart wherein each bar is divided into further components.
Qualification Number of
Students
Metro Large Medium
B.E. 55 25 10 20
B.Com 70 40 15 15
BMS/BMM 40 20 10 10
Others 35 10 15 10
Multiple Bar Chart
• Multiple bar chart: Each observation has more than one value represented, by a group of bars. Percentage of males and females in different countries, percentage of deaths from heart diseases in old and young age, etcName Nov Dec
Lakshmi Mittal 20 32
Mukesh Ambani 7 15
Anil Ambani 5.5 18.2
Azim Premji 11 17.1
010203040
Lakshmi Mittal
Mukesh Ambani
Anil Ambani
Azim Premji
Pie Chart
• Consist of a circle whose area represents the total frequency (100%) which is divided into segments.
• Each segment represents a proportional composition of the total frequency.
Pie Chart
• Angle at the centre is calculated by formula
Qualification Number of
Students
% Angle
B.E. 55 28 99
B.Com 70 35 126
BMS/BMM 40 20 72
Others 35 17 63
0360100
xangle
Histogram
• It is very similar to the bar chart with the difference that the rectangles or bars are adherent (without gaps).
• It is used for presenting class frequency table (continuous data).
• Each bar represents a class and its height represents the frequency (number of cases), its width represent the class interval.
Histogram
Class Frequency
2000 – 3000 2
3000 – 4000 5
4000 – 5000 6
5000 – 6000 4
6000 – 7000 3
Frequency Polygon
• The polygon formed by joining the midpoints of the rectangles of histogram is known as the frequency polygon
Line Graph
• It is a visual presentation of a set of data values joined by straight lines.
Ex: Following is the data of business per employee in some banks
Bank Business Per Employee2005 - 06
Business Per Employee2001 – 02
Andhra Bank 426.75 195.96
Indian Bank 295 156
Canara Bank 441.57 214.88
Dena Bank 364 221
Bank of India 381 218.74
Line Graph
Summary
• Basics of Statistics• Types of data
End of Session 1