Objective- Students will learn how to start working with MS Excel right from basics to Tables, and advanced in data manipulation with database management system.
Course Outcomes (COs):
Course outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
Students will be able to: CO6. Use spreadsheets to perform statistical computations and display numerical and graphical summaries of data sets. CO7. Use sensitivity analysis on data. CO8. Use and identify the descriptive statistics for different problems. CO9. Use of predefined functions in analysis of datasets. CO10. Analyze the concept of database in data management. |
Approach in teaching: Interactive Lectures, Discussion, Demonstrations, Group activities, Teaching using advanced IT audio-video tools Learning activities for the students: Effective assignments, Giving tasks.
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Assessment Strategies Class test, Semester end examinations, Quiz, Practical Assignments, Individual and group projects
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Data Tabulation in Excel
Creating a Table, Adding, Deleting new rows or columns, Moving a Table, Removing duplicate rows from a table. Sorting and filtering a table, auto filter, advanced filter, formatting of table.
series, auto fill series, Cell referencing (Relative, Absolute, Mixed).
Data from other sources: Importing external data from different database files. Creating Custom Views of your Worksheet.
Functions:Functions and its parts, some useful mathematical and statistical Functions in spreadsheet (eg. SUM, COUNT, MAX, MIN, IF, COUNTIF, CEILING, FLOOR, TRUNC, ABS, FACT, INT, LOG, MOD, POWER, ROUND, EXP), logical functions(IF,AND,OR).Date & Time functions (NOW, DATE, TIME, DAY, MONTH, YEAR, HOUR, MINUTE, SECOND).
Decision Making & Advance Spread-Sheet Tools: Financial Functions (PV, NPV, IPR, Rate, FV, PMT, NPER), Vlookup, Hlookup. What if analysis (Data tables, Scenario, Goal seek,Sub-total, Pivot Table), Macros, Protection.
Graphical methods: line graph, bar graph, pie chart, histogram, scatter plot.
Descriptive Statistics (mean, median, mode, standard deviation, sample variance, Range).
Introduction: Database Management Systems
Definition, Characteristics of DBMS, Architecture & Security, Types of Data Models, Concepts and constraints of RDBMS, Introduction to Structured Query Language, MySql Installer, Download sample Database, Loading Sample Database.
Data definition and Manipulation
SQL Process, SQL Commands – DDL, DML, DCL, DQL, SQL Constraints, Data Integrity, Data Types, SQL Operators, Expressions, Querying Database, Retrieving result sets, Sub Queries, Syntax for various Clauses of SQL, Functions and Joins.
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