What is this course all about?

To give you a basic level of computer application literacy primarily, Spreadsheets, and database Excel

Learning objectives:

Gain an understanding of information competency, the Information Processing Cycle, Basic Components of the Personal Computer, and Technology used in the Workplace.
Demonstrate the ability to Create and Edit Workbooks and Charts which utilize Functions and Formulas.
Understand and applying the fundamental database concepts to spreadsheet development such as Importing, Creating Tables, Sorting and Filtering, and using Conditional Formatting.
Use advanced spreadsheet concepts such as Working with Multiple Worksheets and Workbooks, applying Advanced Functions, Setting Validation, and Protecting Workbooks.
Develop an understanding and exposure to new and emerging technologies
Gain the ability to serve as an informed purchaser of technology (personal, commercial)
Prepare a capstone project which applies concepts and principles of course to a unique series of problems.

This textbook was written for a community college introductory course in spreadsheets utilizing Microsoft Excel. While the figures shown utilize Excel 2019, the textbook was written to be applicable to other versions of Excel as well. The book introduces new users to the basics of spreadsheets and is appropriate for students in any major who have not used Excel before. This textbook includes instructions for Excel for Mac also.

Communicating With Data has a distinctive structure and content, combining fundamental quantitative techniques of using data to make informed management decisions with illustrations of how real decision makers, even highly trained professionals, fall prey to errors and biases in their understanding. We present the fundamental concepts underlying the quantitative techniques as a way of thinking, not just a way of calculating, in order to enhance decision-making skills. Rather than survey all of the techniques of management science, we stress those fundamental concepts and tools that we believe are most important for the practical analysis of management decisions, presenting the material as much as possible in the context of realistic business situations from a variety of settings. Exercises and examples drawn from marketing, finance, operations management, strategy, and other management functions.

Good data organization is the foundation of any research project. Most researchers have data in spreadsheets, so it’s the place that many research projects start. We organize data in spreadsheets in the ways that we as humans want to work with the data, but computers require that data be organized in particular ways. In order to use tools that make computation more efficient, such as programming languages like R or Python, we need to structure our data the way that computers need the data. Since this is where most research projects start, this is where we want to start too! In this lesson, you will learn: Good data entry practices - formatting data tables in spreadsheets How to avoid common formatting mistakes Approaches for handling dates in spreadsheets Basic quality control and data manipulation in spreadsheets Exporting data from spreadsheets In this lesson, however, you will not learn about data analysis with spreadsheets. Much of your time as a researcher will be spent in the initial ‘data wrangling’ stage, where you need to organize the data to perform a proper analysis later. It’s not the most fun, but it is necessary. In this lesson you will learn how to think about data organization and some practices for more effective data wrangling. With this approach you can better format current data and plan new data collection so less data wrangling is needed.

Lesson on spreadsheets for social scientists. Good data organization is the foundation of any research project. Most researchers have data in spreadsheets, so it’s the place that many research projects start. Typically we organize data in spreadsheets in ways that we as humans want to work with the data. However computers require data to be organized in particular ways. In order to use tools that make computation more efficient, such as programming languages like R or Python, we need to structure our data the way that computers need the data. Since this is where most research projects start, this is where we want to start too! In this lesson, you will learn: Good data entry practices - formatting data tables in spreadsheets How to avoid common formatting mistakes Approaches for handling dates in spreadsheets Basic quality control and data manipulation in spreadsheets Exporting data from spreadsheets In this lesson, however, you will not learn about data analysis with spreadsheets. Much of your time as a researcher will be spent in the initial ‘data wrangling’ stage, where you need to organize the data to perform a proper analysis later. It’s not the most fun, but it is necessary. In this lesson you will learn how to think about data organization and some practices for more effective data wrangling. With this approach you can better format current data and plan new data collection so less data wrangling is needed.

How to Use Microsoft Excel: The Careers in Practice Series is an textbook appropriate for a course covering Microsoft Excel at a beginner to intermediate level. It is geared toward and will be accommodating for students and instructors with little to no experience in using Microsoft Excel. However, the approach is not at the expense of relevance.

This is a unit of study whose competency is to use ICT to support class administration through the keeping of a digital class record system using a spreadsheet package. The objective is to identify and understand different ICT tool used in the school and class administration.

Kent Treadgold's 7th grade science class uses a hands-on project to learn the abstract concept of density. They measure the mass and volume of different cylinders, create their own computerized spreadsheets for data, and enter the formula to calculate density. By the end of the project, they're able to conclude on their own that density will not change as the shape and size of an object changes, as long as the material it's made of stays the same.

The goal of this lesson is for students to test concepts they have already worked with; creating formulas and functions in a worksheet, and formatting for money. The assessment is a production work where students look at the candy bar sales from each class. It requires them to put in functions like minimum, maximum, totals, and figure revenue.  There is also an additional activity for review of revenue, formatting currency, and totals prior to the production test, if needed. 

This course will provide you with a comprehensive introduction to spreadsheets; it is designed for first-time users with very little or no exposure to the subject.

The goal of this lesson is for students to work with borders and basic formatting in a spreadsheet program so that it is useful and pleasing to the eye. This lesson encourages creativity with a maze creation and also collaboration in a shared spreadsheet that students then copy and format to make it pleasing to the eye.  It also offers students the chance to look at others’ creations and give feedback.

Students build on their existing air quality knowledge and a description of a data set to each develop a hypothesis around how and why air pollutants vary on a daily and seasonal basis. Then they are guided by a worksheet through an Excel-based analysis of the data. This includes entering formulas to calculate statistics and creating plots of the data. As students complete each phase of the analysis, reflection questions guide their understanding of what new information the analysis reveals. At activity end, students evaluate their original hypotheses and “put all of the pieces together.” The activity includes one carbon dioxide worksheet/data set and one ozone worksheet/data set; providing students and/or instructors with a content option. The activity also serves as a good standalone introduction to using Excel.