Quantitative Techniques in Business

1. Quantitative TechniquesinBusiness

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) 18, 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 “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. 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 Variablewith respect to relation Mediating Independent dependent Advertisement Sales Budget Awareness Competitors product, price, packaging, placement Moderating

8. Types of Variablewith respect to data 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 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 Example Education Metric, inter, graduation

10. Numerical Variable A variable whose values are numerical in nature 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 Example speed 40.1, 45, 67……….

11. Research Question 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

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

16. Data Set of raw facts figures is called Data Example: Age- 16, 18, 20, 21, 23, Nationality- Pakistani, Indian, American Types of Data

17. Types of Variablewith 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!