BSc IT
Basic Mathematics
Semester - I

1

INTRODUCTION
• Analysis of data is one of the important stages for experimenter to test out his hypothesis, draw conclusions and take decisions. Stages involved are: Collection Tabulating & Analysing data

• i) ii) iii)

Data analysis
• Data analysis is a process of gathering, modeling, and transforming data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.

• Data • A collection of values to be used for statistical analysis • data as facts or figures from which conclusions may be drawn. Data may consist of numbers, words, or images, particularly as measurements or observations of a set of variables.

• Datum • Datum is the singular form of the noun data

Types of Data
• Qualitative data • Quantitative data • Qualitative data are nonnumeric. {Poor, Fair, Good, Better, Best}, colors (ignoring any physical causes), and types of material {straw, sticks, bricks} are examples of qualitative data. • Qualitative data are often termed categorical data. Some books use the terms individual and variable to reference the objects and characteristics described by a set of data. They also stress the importance of exact definitions of these variables, including what units they are recorded in. The reason the data were collected is also important.

• Qualitative data • Qualitative data are nonnumeric • Poor, Fair, Good, Better, Best, colors • categorical data

• Quantitative data • Quantitative data are numeric • discrete or continuous

• Quantitative data are numeric. Quantitative data are further classified as either discrete or continuous.
– Discrete data are numeric data that have a