1. Quantitative Techniques in Business

2. Quantitative Techniques in Business (QTB)
Quantitative Techniques are the techniques used to gather, sort, analyze and interpret numerical data in order to improve business decisions.
Numerical data
Numerical data (or quantitative data) is data measured or identified on a numerical scale. Numerical data can be analysed using statistical methods, and results can be displayed using tables, charts, histograms and graphs
Examples
Company sales (millions) , 12, 20, etc
Number of employees in company(hundreds) 15, 8, 5, etc

3. Why Study QTB Studying QTB is essential as it enables to
Gather, sort, analyze and interpret the data
Have needed, timely, accurate, yet relevant information.
Understand and compare different types of situations
Predict and forecast about the future needs of the business
Develop effective policies and business related strategies
Make effective decisions to achieve business goals efficiently
Research is based on QTB
Final thesis is based on QTB

4. Research Problem Examples
“Any problem or opportunity that needs to be addressed through research process of data collection and analysis is called Research Problem”
Examples
Human Resource manager wants to develop HR policies regarding employees turnover in order to reduce it.
Marketing manager wants to launch a new product successfully using advertisement as promotional tool
Finance manager needs to invest excessive money profitably

5. Problem Statement
A problem statement is a clear and concise description of any business issue that seeks for Description, Association or difference of two or more variables.
Example
Measure the annual turnover of employees in Higher educational sector of Pakistan
Does advertisement contribute to the sales of a new product in the market
Which of the two options i.e. stock market or real estate is better for investment.

6. Vary + able = Change + able
What is Variable?
Vary + able = Change + able
Variable is a characteristic of anything that can vary (Change).
Examples
Gender (Male, Female)
Age (20 years, 30 years, 50 years)
Motivation level (High, Medium, Low)
Constant is a characteristic that do not vary
e.g. If all students are male in a class then Gender will be constant

7. Types of Variable with respect to relation
Independent
Mediating
dependent
Budget
Advertisement
Sales
Awareness
Competitors product, price, packaging, placement
Moderating

8. Types of Variable with respect to data
Categorical
Nominal
Ordinal
Numerical
Discrete
Continuous
Gender
Male
Female
Motivation
Highly Motivated
Moderately Motivated
Less Motivated
No of students
No of chairs
Collar size
Height
Weight
speed

9. Categorical Variable
A variable whose values are not numerical in nature
Variables
Values
Gender
Male, female
Religion
Islam, christianity, Jews, etc
Motivation level
High, medium, low
Types of Categorical variable
Nominal variable
A categorical variable whose values are not ordered
Example
Gender Male, Female
2. Ordinal variable
A categorical variable whose values are in ordered
Education Metric, inter, graduation

10. Numerical Variable A variable whose values are numerical in nature
Variables
Values
Collar size
14, 14.5, 15, 15.5……….
Height
5.7, 5.8, 5.3
No of employees
23, 45, 69, 100
Types of Numerical variable
Discrete variable
A numerical variable whose values have same interval
Example
collar size 14.5, 15, 15.5……..
2. continuous variable
A numerical variable whose values don’t have same interval
speed , 45, 67……….

11. Research Question Example
Research problem needs to be translated into one or more research questions that are defined as
“A research question is an interrogative statement that seeks for the tentative relationship among variables and clarifies what the researcher wants to answer.”
Example
What is the impact of advertisement on sales of a new product in the market
What is the annual turnover of employees in Higher educational institutions of Pakistan
Does investing in stock market yield more return on investment as compare to investment in real estate.

12. Type of Research Question
Descriptive: A question that is answered through Summarising data about a single variable
E.g.: What is the annual turnover of employees in Higher educational institutions of Pakistan
Associational: A question that is answered through determining strength and direction of relationship between two or more variables
E.g.: What is the impact of advertisement on sales of a new product in the market
Difference: A question that is answered through comparing and contrasting two groups or variables
E.g.: Does investing in stock market yield more return on investment as compare to investment in real estate.

13. Research Hypotheses
“Research hypotheses are predictive statements about
the relationship between two variables”
Types of Hypothesis
There are two types of hypothesis
1. Null Hypothesis
Ho = There is no relationship between Advertising and Sales
2. Alternative Hypothesis
H1 = There is relationship between advertising and sales

14. Research Question Vs. Hypothesis
Interrogative statement
Simple statement
Non-Predictive
Predictive
Non-Directional
Directional

15. Activity In groups of four, use the variables provided to write:
An associational question
A difference question
A descriptive question

16. Set of raw facts figures is called Data
Example: Age- 16, 18, 20, 21, 23,
Nationality- Pakistani, Indian, American
Types of Data
Data
Nature
Qualitative
Quantitative
Time frame
Cross-sectional
Time-Series

17. Types of Variable with respect to data
Gender
Male
Female
Motivation
Highly Motivated
Moderately Motivated
Less Motivated
No of students
No of chairs
Collar size
Height
Weight
speed

18. Thank You!