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