CSCI N207 Data Analysis Using Spreadsheets

Course Information

Name
N207 Data Analysis Using Spreadsheets
Prereq
Math 111
Lecture
BS 2006 Mon Weds 3:30pm - 5:30pm
Lab
SL 251 Tues 3:30pm - 5:30pm
Book
Computational Data Analysis using Spreadsheets
Harris and Chin
ISBN 0-07-236928-0
Office Hours
Mon - Weds
2:30 - 3:30 pm
Contact
aharris@cs.iupui.edu

Grades

I use the following breakdown for grades:

all projects average 40%
midterm exam 20%
final exam 20%
final project 20%
total 100%

Objectives

Course Description
Summary of basic computing topics. An introduction to data analysis using spreadsheets. Emphasis on the application of computational problem solving techniques. Lecture and Laboratory. P: Math 111.
Purpose of This Course:
This course consists of two major topics. The first major topic provides an introduction to the principles of computing. It will cover essential principles of computation to include how computers work, how to solve problems with computers, and examples of common applications. The second major topic focuses on data analysis and its applications. Emphasis is placed on understanding basic concepts of data analysis with the aid of computers. CSCI 207 is not open to Computer Science majors for credit toward a CS degree.
Expectations
This class is designed for students with some formal computer experience and, therefore, students are expected to feel comfortable with electronic technology. Students who have little or no experience with electronic technology or/and are fearsome of computers are strongly urged to consider taking CSCI N100, "Introduction to Computers and Computing" as a beginning course. It covers essentially the first major topics at a slower and more leisurely pace.
Upon successfully completing this course, a student should...
  • ... understand what a number system is
  • ... understand why the binary number system is important in computing
  • ... know how to convert numbers from one number system to another
  • ... understand the difference between digital and analog
  • ... understand what the main pieces of computer hardware are and some important facts about each
  • ... have a good understanding of how the Internet works
  • ... know how to create an HTML page with a general text editor
  • ... understand what a database is
  • ... understand the relational database model
  • ... know how to create a basic database with a few related tables
  • ... know how to create a basic Excel spreadsheet
  • ... know the difference between absolute and relative referencing
  • ... know how to format data in Excel cells
  • ... understand what a function is
  • ... know when, how, and why to use a function
  • ... know how to create a chart using data in the spreadsheet
  • ... be able to select the correct chart type based on the data needing to be displayed
  • ... be able to calculate the mean of a dataset
  • ... be able to calculate the median of a dataset
  • ... be able to calculate the range of a dataset
  • ... be able to calculate the skewness of a dataset
  • ... be able to calculate the variance of a dataset
  • ... be able to calculate the standard deviation of a dataset
  • ... be able to recognize the similarities and differences between the univariate calculations
  • ... understand why standard deviation is important and why the formula is what it is
  • ... be able to determine if two datasets are correlated
  • ... understand the difference between positive and negative correlation
  • ... be able to calculate the equation of the regression line for two datasets
  • ... be able to calculate the residual for a given point
  • ... be able to determine how good the regression line is using the sum of the square residuals
  • ... be able to use extrapolation to determine the theoretical y value for an x value outside the range of observed x values
  • ... be able to use interpolation to determine the theoretical y value for an x value within the range of observed values

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