The Mathematics Department has adopted the following best practices for teaching this course: offering or awarding extra-credit is forbidden, the allowance of multiple attempts at exams is forbidden, and an approved on-site proctor for online course exams is required.
A. Introduction
B. Organizing Data
1. Grouping
2. Graphing
C. Descriptive Measures
1. Measures of central tendency.
2. Measures of dispersion.
3. Population vs. sample statistics.
D. Probability
1. Relative frequency.
2. Conditional probability.
3. Independence.
4. Graphical and computational approaches.
A. Discrete Random Variables
1. Distinguishing between discrete and continuous random variables.
2. Binomial coefficients and distribution.
B. Normal Distribution
1. Standard normal curve.
2. Normally distributed populations.
3. Normally distributed random variables.
C. Sampling Distribution of the Mean
H. Estimating Means and Proportions
1. Estimating population means.
2. Confidence intervals.
3. Determining sample size.
4. Estimating population proportions.
I. Hypothesis Testing: Means and Proportions
1. Null and Alternative hypotheses.
2. Z-test.
3. T-test.
4. Tests for population proportions.
J. Hypothesis Testing: Two Populations
1. Two population means.
2. Two population proportions.
K. Descriptive Methods in Linear Regression
1. Review of linear equations.
2. The regression equation.
3. Coefficient of determination.
4. Linear correlation.
5. Regression.
L. Analysis of Variance
1. Introduction of Fisher’s F-distribution.
2. One-way analysis of variance (ANOVA).
3. Two-way analysis of variance.
4. Discussion of two-factor problems.