College AlgebraCourse TextBarnett, Raymond A., Michael R.docx
1. College Algebra
Course Text
Barnett, Raymond A., Michael R. Ziegler, and Karl E. Byleen.
College Algebra, 8th edition,
McGraw-Hill, 2008, ISBN: 9780072867381 [find and buy the
text: Straighterline.com/
textbooks]
Course Description
This course provides a working knowledge of college-level
algebra and its applications.
Emphasis is placed upon the solution and the application of
linear and quadratic equations,
word problems, polynomials, and rational and radical equations.
Students perform
operations on real numbers and polynomials and simplify
algebraic, rational, and radical
expressions.
Arithmetic and geometric sequences are examined, and linear
equations and inequalities are
discussed. Students learn to graph linear, quadratic, absolute
value, and piecewise-defined
functions and solve and graph exponential and logarithmic
equations. Other topics include
solving applications using linear systems as well as evaluating
and finding partial sums of a
series.
4. Course Evaluation Criteria
StraighterLine does not apply letter grades. Students earn a
score as a percentage of
100%. A passing percentage is 70% or higher.
If you have chosen a Partner College to award credit for this
course, your final grade will be
based upon that college's grading scale. Only passing scores
will be considered by Partner
Colleges for an award of credit.
There are a total of 500 points in the course:
Topic Assessment Points Available
1 Graded Exam #1 75
4 Graded Exam #2 75
8 Graded Exam #3 75
13 Graded Exam #4 75
Review Final Graded Exam 200
Total 500
Course Topics and Objectives
Topic Lesson Subtopics Objectives
9. Formula and
Applications of
the Quadratic
Equations
● Write a
quadratic
equation in the
standard form.
● Solve quadratic
equations by
factoring.
● Solve quadratic
equations by
the square root
property.
● Solve quadratic
equations by
completing the
square.
● Solve quadratic
equations
by using the
quadratic
formula.
● Solve word
problems
involving
quadratic
equations.
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5 Functions and Graphs ● Rectangular
Coordinates and
the Graph of a
Line
● Use a table
of values to
graph linear
equations.
● Determine
when lines
are parallel or
perpendicular.
● Use linear
graphs in an
applied context.
● Identify
functions and
state their
domain and
range.
● Use function
notation.
● Write a linear
equation in
function form.
14. 6 Operations and
Functions
● The Algebra and
Composition
Functions
● One-to-One
and Inverse
Functions
● Compute a sum
or difference of
functions and
determine the
domain of the
result.
● Compose
two functions
and find the
domain.
● Identify one-to-
one functions.
● Find inverse
functions using
an algebraic
method.
● Graph a
function and its
inverse.
● Graph
16. Symmetry
● Tranformations
● State the
domain of a
piecewise-
defined
function.
● Evaluate
piecewise-
defined
functions.
● Graph functions
that are piece-
wise defined.
● Identify
different
symmetry
types.
● Use symmetry
as an aid to
graphing.
● Perform vertical
and horizontal
shifts of a basic
graph.
● Perform vertical
and horizontal
reflections of a
18. Polynomial
Functions
● Applications
of Polynomial
Functions
● Graph quadratic
functions by
completing
the square
and using
transformations
.
● Graph a general
quadratic
function using
the vertex
formula.
● Solve
applications
involving
quadratic
functions.
● Graph
polynomial
functions.
● Describe the
end behavior
of a polynomial
graph.
20. horizontal
and vertical
asymptotes.
● Use asymptotes
to graph
transformations
.
● Use asymptotes
to determine
the equation
of a rational
function from
its graph.
● Find the domain
of a rational
function.
● Find the
intercepts
of a rational
function.
● Graph general
rational
functions.
● Solve
applications
involving
rational
functions.
22. ● Solve certain
exponential
equations.
● Solve
applications
of exponential
equations.
● Write
exponential
equations in
logarithmic
form.
● Graph
logarithmic
functions
and find their
domains.
● Solve
applications
of logarithmic
functions.
● Evaluate and
graph base
exponential
functions.
● Evaluate
and graph
the natural
logarithm
functions.
24. ● Write
logarithmic and
exponential
equations in
simplified form.
● Solve
exponential
equations.
● Solve
logarithmic
equations.
● Solve
applications
involving
exponential
and logarithmic
equations.
● Use exponential
equations to
find the interest
compounded in
times per year.
● Use exponential
equations to
find the interest
compounded
continuously.
● Solve
exponential
26. ● Solve linear
systems by
graphing.
● Solve linear
systems by
substitution.
● Solve linear
systems by
elimination.
● Recognize
inconsistent
systems (no
solutions) and
dependent
systems
(infinitely many
solutions).
● Use a system
of equations to
mathematically
model and solve
applications.
13 Solving Linear
Systems Using
Augmented Matrices
● Matrices
● Solving Linear
Systems
27. using Matrix
Equations
● More
Applications of
Linear Systems
● State the size
of a matrix
and identify
entries in a
specified row
and column.
● Form the
augmented
matrix of a
system of
equations.
● Recognize
inconsistent
and dependent
systems.
● Model and solve
applications
using linear
systems.
● Solve a system
of equations
using row
operations.
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Business Statistics
Course Text
● Lind, Douglas A., Marchal, William A. and Samuel A.
Wathen. Basic Statistics
for Business and Economics, 7th edition, McGraw-Hill/Irwin,
2010, ISBN:
9780077384470 [find and buy the text:
Straighterline.com/textbooks]
Required Computing Software
Several types of computer software will perform the type
statistical analyses taught in this
class. For this course, the only required software is Microsoft
Excel.
Course Description
This course familiarizes students with the basic concepts of
business statistics and provides
a comprehensive overview of its scope and limitations. Students
perform statistical
analyses of samples, compute the measures of location and
31. dispersion, and interpret
these measures for descriptive statistics. Other sections review
linear regression, multiple
regression, and correlation analysis, as well as model building,
model diagnosis, and time
series regression using various models. After a review of the
basic concepts of probability,
students apply discrete and continuous distributions of
probability. Other topics include
constructing a hypothesis on one and two samples, performing
one-way and two-way
analyses of variance, and applying nonparametric methods of
statistical analysis.
Course Objectives
After completing this course, students will be able to:
● Define statistics and identify its scope and limitations.
● Describe and apply the basic concepts in statistics.
● Apply the sampling methods and the Central Limit Theorem
to perform statistical
analyses of samples and to predict population behavior.
● Compute and interpret measures of location and dispersion.
● Represent the statistical data in different forms and interpret
the different
representations.
● Perform linear regression and correlation analysis.
● Perform multiple regression and correlation analysis.
● Describe the basic concepts of probability.
● Describe and apply the discrete and continuous distributions
of probability.
● Conduct hypothesis tests based on one or two samples.
33. StraighterLine does not apply letter grades. Students earn a
score as a percentage of
100%. A passing percentage is 70% or higher. If you have
chosen a Partner College to
award credit for this course, your final grade will be based upon
that college's grading
scale. Only passing scores will be considered by Partner
Colleges for an award of credit.
There are a total of 1000 points in the course:
Topic Assessment Points Available
2 Graded Quiz 1 125
4 Graded Quiz 2 125
6 Graded Quiz 3 125
8 Graded Quiz 4 125
10 Graded Quiz 5 125
13 Graded Quiz 6 125
14 Final Graded Exam 250
Total 1000
Course Topics and Objectives
Topic Lesson Topic Subtopics Objectives
34. 1 Statistics: An
Introduction
and Basic
Concepts
● Use of
Statistics
● Types of
Variables
● Levels of
Measurement
● Ethics in
Statistics
● Software and
Statistics
● Graphical
Displays of
Categorical
Data
● Differentiate between the
word “statistics” and the
science of statistics.
● Describe the importance
of statistics and
situations where
statistics are used in
business and everyday
life; identify business
35. situations in which
statistics can be used
appropriately and
inappropriately.
● Identify qualitative versus
quantitative and discrete
versus continuous
variables.
● Discuss the levels of
measurement and
choose the most
appropriate level of
measurement for a
specified situation.
● Explain the role of
computer software in
statistical analysis and
identify some of the
most popular software
packages.
● Construct bar charts to
display categorical data.
2 Descriptive
Statistics:
Numerical
Measures
● Arithmetic
36. Mean
● Geometric
Mean
● Median and
Mode
● Measures of
Dispersion
● Chebyshev's
Theorem and
the Empirical
Rule
● Using Software
to Compute
Descriptive
Statistics
● Calculate the arithmetic
mean for a given set of
data.
● Calculate the geometric
mean for a given set of
data.
● Calculate the median and
mode for a given set of
data.
● Compute and interpret
the range, mean
deviation, variance, and
37. standard deviation for
data observations.
● Interpret data using
Chebyshev's theorem
and the Empirical rule.
● Understand how
software can be used
in computing various
measures of location and
dispersion.
3 Descriptive
Statistics:
Representation
al
● Dot Plot, Stem
Plot and
Histogram
● Quartiles,
Deciles, and
Percentiles
● Skewness
● Bivariate Data
● Create and interpret
dot plot, box plot, and
scatter diagrams.
● Define and compute
quartiles, deciles, and
percentiles.
38. ● Compute and interpret
the coefficient of
skewness.
● Construct a contingency
table.
4 Probability
● Probability
Approaches
● Probability
Calculations
● Tools of
Analysis
● computing
the Number
of Possible
Outcomes
● Discuss the objective and
subjective approaches to
probability analysis.
● Calculate probability using
the rules of addition and
multiplication.
● Use and interpret
contingency tables,
39. Venn diagrams, and tree
diagrams.
● Compute the number
of possible outcomes
for combinations and
permutations using
formulae and Excel
functions.
5 Discrete and
Continuous
Probability
Distributions
● Discrete
Progrability
Distributions
● Binomial
Probability
Distributions
● Poisson
Probability
Distributions
● Uniform
Probability
Distributions
● Normal
Probability
Distributions
● Sampling
40. Distribution
of the Sample
Mean
● Central Limit
Theorem
● Explain the difference
between discrete and
continuous distribution.
● Compute the mean
and the standard
deviation for a uniform
distribution.
● Calculate the mean,
variance, and standard
deviation of a probability
distribution.
● Compute probabilities
using the binomial
probability distribution.
● Compute probabilities
using the uniform
distribution.
● Calculate areas under a
normal curve using the
Empirical Rule.
● Compute probabilities
using the Poisson
probability distribution.
41. ● Compute probabilities
using the normal
probability distribution.
● Select a sample and
construct a sampling
distribution of the mean.
● Explain the importance of
the central limit theorem
and how it applies to
sample distributions.
6 Sampling
Methods
● Sampling a
Population
● Sampling
Errors
● Define the terms
population and sample.
● Explain the need for
sampling.
● Use a simple random
sampling technique to
select members of the
general populate.
42. ● Understand more complex
sampling techniques,
such as stratified,
cluster, and systematic
random sampling.
● Identify sampling errors
in a given situation.
7 Using
confidence
Intervals in
the Sampling
Process
● Large Sample
Confidence
Intervals
● Small Sample
Confidence
Intervals
● Proportions
● Sample Size
● Define the terms
confidence interval,
point estimate, and
degrees of freedom, and
explain how they are
involved in the sampling
process.
● Demonstrate the ability
to compute a confidence
43. interval for a large
sample experiment.
● Compute a confidence
interval for a small
sample experiment.
● Compute a confidence
interval for a proportion.
● Determine an appropriate
sample size for small,
large, and proportion
experiments.
8 Tests of
Hypothesis
● Hypothesis
Testing: An
Introduction
● Decision
Making in
Hypothesis
Testing
● Hypothesis
Testing with
Proportions
● Two-Sample
Test of
Hypothesis
44. ● Formulate null and
alternate hypotheses,
and test the hypothesis
using the five steps of
the hypothesis testing
procedure.
● Discuss Type I and Type
II errors on a test of
hypothesis.
● Perform a one-tailed
and a two-tailed test of
hypothesis.
● Perform a test of
hypothesis on the
difference between two
population means using
the z and t statistics.
● Perform a test of
hypothesis on a
population proportion
using the z statistic.
9 Analysis of
Variance
● Using the F
Distribution
in Variance
Analysis
● Analysis of
45. Variance
(ANOVA)
● Computing
the Analysis
of Variance
(ANOVA)
- Sum of
Squares
● Analyzing the
Variance
● Use of
Software
in Variance
Analysis
● Discuss the general idea
of analysis of variance
and analyze the given F
distribution.
● Test a hypothesis to
determine whether
the variances of two
populations are equal.
● Test a hypothesis about
three or more treatment
means and develop
confidence intervals for
the difference between
treatment means.
● Perform an analysis of
46. variance (ANOVA).
● Understand how to use
statistical software in
variance analysis.
10 Regression
Analysis
● Correlation
Analysis
● Coefficient of
● Discuss the difference
between correlation and
causation.
Correlation
● Regression
Analysis
● Confidence
Interval and
Prediction
Intervals
● ANOVA Table
● Analyze the correlation
between two variables in
specified situations.
47. ● Calculate and interpret
the coefficient
of correlation,
the coefficient of
determination, and the
standard error.
● Calculate and interpret
the linear regression
line.
● Construct and interpret a
confidence interval and
prediction interval for a
dependent variable.
● Use an ANOVA table data
to compute statistics.
11 Multiple
Regression
Analysis
● Multiple
Regression
Analysis
Equation
● Analyzing
ANOVA Table
Output
● Analyzing
Individual
Independent
Variables
48. ● Analyze the relationships
between several
independent variables
and a dependent
variable.
● Test to determine
whether the regression
coefficient for each
independent (or
explanatory) variable
has a significant
influence upon the
dependent variable.
● Calculate and interpret
multiple regression
analysis.
● Compute variance of
regression using the
standard error of
estimate and the ANOVA
table.
● Calculate and interpret
the coefficient of
determination and the
correlation matrix.
● Identify the violation
of assumptions:
49. homoscedasticity and
autocorrelation.
12 Nonparametric
Methods
● Chi-Square
Test
● Contingency
Table
Analysis
● Test a hypothesis
comparing an observed
set of frequencies to
an expected set of
frequencies using the
chi-square test.
● Identify the limitation of
the chi-square test in a
specified situation.
● Analyze relationships in
statistical data using a
contingency table.
13 Process
Improvement
Using Control
Charts
● Statistical
Process
Control
50. ● Creating
Control
Charts
● Analyzing
Control
Charts
● Natural
Tolerance
Limits
● p Chart
● Identify the causes of
process variation and
apply statistical process
control to reduce
process variation.
● Sample a process and use
rational sub-grouping to
control process.
● Use statistical software
to create X-bar and R-
charts.
● Interpret information
presented in control
charts and R-charts
to identify assignable
causes and analyze
patterns.
51. ● Calculate and analyze
the upper and lower
natural tolerance limits
to evaluate whether a
process is capable of
meeting specifications.
● Construct p chart for
fraction nonconforming.
14 Review
● Course Review ● None