Data analysis for business decisions

Data and Statistics, Data Mining, Data & Variables, Data Analysis, etc.

1. Data Analysis for Business Decisions By - Md Salman Ashrafi

2. DATA & STATISTICS Data is individual pieces of factual information recorded and used for the purpose of analysis. It is the raw information from which statistics are created. Statistics are the results of data analysis - its interpretation and presentation. In other words some computation has taken place that provides some understanding of what the data means. Statistics are often presented in the form of a table, chart, or graph to provide better view of information.

3. Data Mining and Data Analyzing Data Mining Exploration of data to get some result Trial and error Uncertainty Data Analyzing Objective Measurement Test to be applied

4. Data & Variables Data refers to a set of values, which are usually organized by variables and observational units and Variables are of different types and can be classified in many ways. Numerical and Categorical . Variable A variable is defined as anything that has a quantity or quality that varies. A variable is an attribute that describes a person, place, thing or idea. It may change from group to group, person to person, or even within one person.

5. Types of Variables Quantitative/Metric/Numerical It deals with numbers and things you can measure objectively: dimensions such as height, width, and length. Temperature and humidity. Prices. Area and volume. Qualitative/Non-Metric/Categorical It deals with characteristics and descriptors that can't be easily measured, but can be observed subjectively—such as smells, tastes, textures, attractiveness, and color.

6. Quantitative Variables Discrete It is a count that can't be made more precise. Typically it involves integers. For instance, the number of children (or adults, or pets) in your family is discrete data, because you are counting whole, indivisible entities: you can't have 2.5 kids, or 1.3 pets. Continuous It could be divided and reduced to finer and finer levels. For example, you can measure the height of your kids at progressively more precise scales—meters, centimeters, millimeters, and beyond—so height is continuous data.

7. Qualitative Variables Nominal Nominal variable is defined as data that is used for naming or labelling variables, without any quantitative value. Nominal data can be both qualitative and quantitative. However, the quantitative labels lack a numerical value or relationship (e.g., identification number). Names of people, gender, and nationality are just a few of the most common examples of nominal variables. Ordinal In Ordinal variable the values follow a natural order. One of the most notable features of ordinal variable is that the differences between the variable values cannot be determined or are meaningless. The Likert scale that you may find in many surveys is one example. The Likert scale lists the categories of the psychometric scale such as “Strongly Agree,” “Agree,” etc.

8. Ready for a quiz?

9. Scales Nominal Scale Ordinal Scale Interval Scale Ratio Scale Scales of Measurement

10. How likely you will recommend our services to your friends? Very Likely Likely Neutral Unlikely Very Unlikely Nominal Ordinal C) Interval D) Ratio

11. What color hair do you have? Brown Black White Pink Nominal Ordinal C) Interval D) Ratio

12. What's your age? Nominal Ordinal C) Interval D) Ratio …………….

13. What's your nationality? American Indian German Japanese Nominal Ordinal C) Interval D) Ratio

14. What's your monthly income? 0 - 50000 50000 - 100000 100000 - 150000 150000 - 200000 Nominal Ordinal C) Interval D) Ratio

15. THANKS